ARTICLE | doi:10.20944/preprints202303.0183.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Cyber-physical security; Human activity recognition; GoogleNet; BiLSTM; Deep Learning; Algorithm
Online: 10 March 2023 (02:07:09 CET)
Cyber-physical security is vital for protecting key computing infrastructure against cyber attacks. Individuals, corporations, and society can all suffer considerable digital asset losses due to cyber attacks, including Data loss, theft, financial loss, reputation harm, company interruption, infrastructure damage, ransomware attacks, and espionage. A cyber-physical attack harms both digital and physical assets. Cyber-physical system security is more challenging than software-level cyber security because it requires physical inspection and monitoring. This paper proposes an innovative and effective algorithm to strengthen Cyber-Physical Security (CPS) with minimal human intervention. It is a Human Activity Recognition (HAR)-based approach where a GoogleNet-BiLSTM network hybridization has been used to recognize suspicious activities in cyber-physical infrastructure perimeter. The proposed HAR-CPS algorithm classifies suspicious activities from real-time video surveillance with an average accuracy of 73.15%. It incorporates Machine Vision at the IoT Edge (Mez) technology to make the system latency tolerant. Dual-layer security has been ensured by operating the proposed algorithm and GoogleNet-BiLSTM hybrid network from a cloud server, which ensures the security of the proposed security system. The innovative optimization scheme makes it possible to strengthen cyber-physical security with $4.29 per month only.
REVIEW | doi:10.20944/preprints202208.0235.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Malware; cyber security; cyber-attacks; two factor authentication; software; targeting; privacy; causes of cyber attacks
Online: 12 August 2022 (10:33:03 CEST)
Background: Cyber Security is to protect online data and software from cyber threats. These cyberattacks are typically intended to gain access to, change, or delete sensitive information; extort money from users; or disrupt regular corporate activities. It is difficult to keep up a regular follow up with new technologies so it is necessary to keep the important data safe from cyber threats. There are many types of cyber threats; malware, ransom-ware, social engineering, phishing etc. To prevent cyber-attacks one can use password manager tools like LastPass and others. People also use two factor authentication for double security on their accounts. Methods: Boards such as the National Institute of Standards and Technology (NIST) are developing frameworks to assist firms in understanding their security risks, improving cybersecurity procedures, and preventing cyber assaults. The fight against cybercrimes and attack, rganisations needed a strong base there are 5 types of cyber securities; Critical Infrastructure Security, application security, network security, cloud security and (IoT) Security. In the modern time US is highly based on computers and on different software so it is really important for US to be more conscious about the security as they get many threats almost everyday for hacking their data and accounts.Results and Conclusion: Nowadays, even small businesses rarely recover their loss from the cyber-attacks and many back-off from continuing their businesses after being target of hackers. The first cybercrime attack was recorded on 1988 by a graduate student. Now that large companies and even small businesses are aware of cyber-attacks so they try their best to take every precaution to prevent the hacking with double security and password manager tools.
REVIEW | doi:10.20944/preprints202211.0371.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Cyber security; privacy; awareness; impact; cyber-attacks; benefits of cyber security.
Online: 21 November 2022 (04:43:25 CET)
Background: Cyber security is used to save the important data from getting hacked, took by some unknown access. It makes our environment a safe place for us to work out or share our information and since privacy is almost everyone’s top priority, there must be the surety of saving the private information. Methods: In today’s world cyber security is really important as there are now many devices, websites, new technology which makes it a lot easier for hackers to get into anyone’s files which stores crucial data. However, many steps can be reserved to protect the data such as; educating your employees with how to prevent your files or computers from getting hacked, avoid clicking on websites that don’t seem safe, use firewalls, antimalware system and most importantly make sure to keep passwords that are hard to guess and try to go for a face recognition instead of pins and passcodes. Results and Conclusion: This all does not only makes using technology safe but also favors your business for the safety of employees working within the organization. The customers being assured about their data being safe, improves productivity since viruses can slow down computers which may trigger the focus of staff during the working hours. It could save your system from adware; the links of websites are also prevented from slow internet speeds. There is no denying at the fact that cyber security is a major requirement for everyone who is indulged with technology today.
ARTICLE | doi:10.20944/preprints202304.0923.v1
Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Artificial Intelligence with respect to Cyber security; Artificial Intelligence and Cyber security; AI and Cybersecurity; Importance of AI with respect to Cyber security
Online: 25 April 2023 (10:35:26 CEST)
Artificial Intelligence has transformed the cyber security industry by enabling organizations to systematize and enlarge outdated safety procedures. AI can provide more effective threat detection and response capabilities, enhance vulnerability management, and improve compliance and governance. AI technologies such as machine learning, natural language processing, behavioral analytics, and deep learning can enhance cyber security defenses and protect against a wide range of cyber threats, including malware, phishing attacks, and insider threats.Theoretical underpinnings of AI in cyber security, such as machine learning, natural language processing, behavioral analytics, and deep learning, are discussed. The advantages of using AI in cyber security are discussed including speed and accuracy, continuous learning and adaptation, and efficiency and scalability. It's important to note that AI is not a silver bullet for cyber security and should be used in conjunction with other security measures to provide a comprehensive defense strategy.AI has transformed the way cyber security operates in today's digital age. By analyzing vast amounts of data quickly and accurately it has become a valuable tool for organizations looking to protect their assets from cyber threats.
ARTICLE | doi:10.20944/preprints202004.0481.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: cybersecurity; cyber-attacks; anomaly detection; intrusion detection system; machine learning; network behavior analysis; cyber decision making; cybersecurity analytics; cyber threat intelligence.
Online: 27 April 2020 (08:10:53 CEST)
Cyber security has recently received enormous attention in today’s security concerns, due to the popularity of the Internet-of-Things (IoT), the tremendous growth of computer networks, and the huge number of relevant applications. Thus, detecting various cyber-attacks or anomalies in a network and building an effective intrusion detection system that performs an essential role in today’s security is becoming more important. Artificial intelligence, particularly machine learning techniques, can be used for building such a data-driven intelligent intrusion detection system. In order to achieve this goal, in this paper, we present an Intrusion Detection Tree (“IntruDTree”) machine-learning-based security model that first takes into account the ranking of security features according to their importance and then build a tree-based generalized intrusion detection model based on the selected important features. This model is not only effective in terms of prediction accuracy for unseen test cases but also minimizes the computational complexity of the model by reducing the feature dimensions. Finally, the effectiveness of our IntruDTree model was examined by conducting experiments on cybersecurity datasets and computing the precision, recall, fscore, accuracy, and ROC values to evaluate. We also compare the outcome results of IntruDTree model with several traditional popular machine learning methods such as the naive Bayes classifier, logistic regression, support vector machines, and k-nearest neighbor, to analyze the effectiveness of the resulting security model.
REVIEW | doi:10.20944/preprints202101.0457.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity; artificial intelligence; machine learning; cyber data analytics; cyber-attacks; anomaly; intrusion detection; security intelligence
Online: 25 January 2021 (09:19:10 CET)
Artificial Intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (Industry 4.0), which can be used for the protection of Internet-connected systems from cyber-threats, attacks, damage, or unauthorized access. To intelligently solve today's various cybersecurity issues, popular AI techniques involving Machine Learning (ML) and Deep Learning (DL) methods, the concept of Natural Language Processing (NLP), Knowledge Representation and Reasoning (KRR), as well as the concept of knowledge or rule-based Expert Systems (ES) modeling can be used. Based on these AI methods, in this paper, we present a comprehensive view on "AI-driven Cybersecurity" that can play an important role for intelligent cybersecurity services and management. The security intelligence modeling based on such AI methods can make the cybersecurity computing process automated and intelligent than the conventional security systems. We also highlight several research directions within the scope of our study, which can help researchers do future research in the area. Overall, this paper's ultimate objective is to serve as a reference point and guidelines for cybersecurity researchers as well as industry professionals in the area, especially from an AI-based technical point of view.
REVIEW | doi:10.20944/preprints202102.0082.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: identity theft; cyber-crime; identity fraud; types; techniques
Online: 2 February 2021 (10:31:24 CET)
Online identity-based theft is known to be one of the most serious and growing threats to victims, such as individuals and organizations, over the last 10 years due to the enormous economic damage these crimes have caused. The availability of personal information on the Internet has increased the chances of this cyber-crime. Online identity theft crime is the result of a combination of cyber-crimes on the one hand and lack of awareness and training of users on the other hand to protect personal data on the other. Education and awareness, which also contributes to early detection, is the strongest tool for consumers to safeguard themselves from online identity fraud. This paper provides a comprehensive explanation of online identity theft, the various approaches that thieves use to attack individuals and organizations and the types of fraud involved in this cyber-crime. The aim of this research is to evaluate the need for a reformulation of the concept of identity theft in order to be compatible with the evolution of behaviors and fraud.
ARTICLE | doi:10.20944/preprints201811.0045.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: Cyber-Physical Systems; Automotive; Cyber-Physical Attack; Integrity; Sensor Attack Detection; Speed Estimation; Deep learning
Online: 2 November 2018 (10:16:50 CET)
The violation of data integrity in automotive Cyber-Physical Systems (CPS) may lead to dangerous situations for drivers and pedestrians in terms of safety. In particular, cyber-attacks on the sensor could easily degrade data accuracy and consistency over any other attack, we investigate attack detection and identification based on a deep learning technology on wheel speed sensors of automotive CPS. For faster recovery of a physical system with detection of the cyber-attacks, estimation of a specific value is conducted to substitute false data. To the best of our knowledge, there has not been a case of joining sensor attack detection and vehicle speed estimation in existing literatures. In this work, we design a novel method to combine attack detection and identification, vehicle speed estimation of wheel speed sensors to improve the safety of CPS even under the attacks. First, we define states of the sensors based on the cases of attacks that can occur in the sensors. Second, Recurrent Neural Network (RNN) is applied to detect and identify wheel speed sensor attacks. Third, in order to estimate the vehicle speeds accurately, we employ Weighted Average (WA), as one of the fusion algorithms, in order to assign a different weight to each sensor. Since environment uncertainty while driving has an impact on different characteristics of vehicles and cause performance degradation, the recovery mechanism needs the ability adaptive to changing environments. Therefore, we estimate the vehicle speeds after assigning a different weight to each sensor depending on driving situations classified by analyzing driving data. Experiments including training, validation, and test are carried out with actual measurements obtained while driving on the real road. In case of the fault detection and identification, classification accuracy is evaluated. Mean Squared Error (MSE) is calculated to verify that the speed is estimated accurately. The classification accuracy about test additive attack data is 99.4978%. MSE of our proposed speed estimation algorithm is 1.7786. It is about 0.2 lower than MSEs of other algorithms. We demonstrate that our system maintains data integrity well and is safe relatively in comparison with systems which apply other algorithms.
ARTICLE | doi:10.20944/preprints202304.0691.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: Cyber physical systems; Cyber attacks; Artificial Intelligence; Machine learning; Deep learning
Online: 21 April 2023 (08:35:15 CEST)
Importance and need for cyber security have increased in folds since a decade. Indirectly, the country’s security depends on the country’s cyber-physical systems. Attackers are becoming more innovative, and attacks are becoming undetectable, causing huge risks to the systems. In this scenario, intelligent and evolving detection methods should be introduced to replace the basic and outworn ones. This article discusses about new-age intelligence and smart techniques dealing with artificial intelligence (AI) models. Artificial intelligence for cyber security is reviewed, and the performance of machine learning models (ML) and deep learning (DL) models are analysed. A real-time case study of stealthy local covert attacks with false data injection attacks is implemented on the DC-DC converter. A deep learning model is designed to mitigate cyber attacks, and its performance is evaluated.
ARTICLE | doi:10.20944/preprints201903.0111.v1
Subject: Engineering, Control And Systems Engineering Keywords: Industry 4.0., Internet of Things, case study, cyber security framework
Online: 8 March 2019 (15:27:11 CET)
This research article reports the results of a qualitative case study that correlates academic literature with five Industry 4.0 cyber trends, seven cyber risk frameworks and two cyber risk models. While there is a strong interest in industry and academia to standardise existing cyber risk frameworks, models and methodologies, an attempt to combine these approaches has not been done until present. We apply the grounded theory approach to derive with integration criteria for the reviewed frameworks, models and methodologies. Then, we propose a new architecture for the integration of the reviewed frameworks, models and methodologies. We therefore advance the efforts of integrating standards and governance into Industry 4.0 and offer a better understanding of a holistic economic impact assessment model for IoT cyber risk.
REVIEW | doi:10.20944/preprints202211.0128.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Cyber security threats; Cyber security threats to educational institutes; growing concern for the new era of cybersecurity; New Era of cybersecurity
Online: 7 November 2022 (14:37:03 CET)
Background: The outbreak of the Covid-19 pandemic has significantly affected the operations of higher education institutions. Due to the limited use of video conferencing and cloud computing in these facilities, distance learning became the only option available to them. Objective: The study focused on identifying the most common types of attacks that can affect e-learning assets. Results: There was a lack of clear cybersecurity policies for educational institutes and universities in 2020, according to a report by Microsoft Security Intelligence. The report showed that the education industry was the most targeted sector for malware attacks in the last 30 days. Conclusion: The recommendations for improving the security of e-learning systems. Some of these include implementing policies that restrict access to the resources and applications, updating security patches, and using cryptographic protocols.
Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: smartphones; balloons, internet of things; cyber-physical systems
Online: 8 September 2021 (12:34:09 CEST)
A smartphone plummeted from a stratospheric height of 36 km (~119,000 feet), providing a complete record of its rapid descent and abrupt deceleration when it hit the ground. The smartphone was configured to collect internal sensor data at high rates. We discuss the state-of-the-art of smartphone environmental and sensing capabilities at the closing of year 2020 and present a flexible mobile sensor data model. The associated open-source application programing interface (API) and python software development kit (SDK) used in this work is transportable to any hardware platform and operating system.
ARTICLE | doi:10.20944/preprints201706.0113.v1
Subject: Engineering, Control And Systems Engineering Keywords: conceptual modeling; cyber-physical systems; cyber-physical gap; Object-Process Methodology; model-based systems engineering; Three Mile Island 2 Accident
Online: 26 June 2017 (04:59:29 CEST)
: The cyber-physical gap (CPG) is the difference between the 'real' state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is an inevitable issue in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach for capturing, explaining, and mitigating the CPG, on top of and in sync with the conventional system model, and as an inherent systems engineering activity. This approach enhances the systems engineer’s ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions, actions, and hazardous implications. CPGAME is a generic, conceptual approach, specified and demonstrated with Object Process Methodology (OPM). OPM is a holistic conceptual modeling paradigm for multidisciplinary, complex, dynamic systems, which is also ISO-19450. We analyze the 1979 Three Miles Island 2 nuclear accident as a prime example of the disastrous consequences of unmitigated CPGs in complex systems.
ARTICLE | doi:10.20944/preprints202103.0406.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: cyber security; secure development; prototyping; web security; internet of things; software security; digitalization; socio-technical security
Online: 16 March 2021 (09:24:24 CET)
Secure development is a proactive approach to cyber security. Rather than building a technological solution and then securing it in retrospect, secure development strives to embed good security practices throughout the development process and thereby reduces risk. Unfortunately, evidence suggests secure development is complex, costly, and limited in practice. This article therefore introduces security-focused prototyping as a natural precursor to secure development that embeds security at the beginning of the development process, can be used to discover domain specific security requirements, and can help organisations navigate the complexity of secure development such that the resources and commitment it requires are better understood. Two case studies–one considering the creation of a bespoke web platform and the other considering the application layer of an Internet of Things system–verify the potential of the approach and its ability to discover domain specific security requirements in particular. Future work could build on this work by conducting case studies to further verify the potential of security-focused prototyping and even investigate its capacity to be used as a tool capable of reducing a broader, socio-technical, kind of risk.
ARTICLE | doi:10.20944/preprints201811.0323.v1
Subject: Computer Science And Mathematics, Information Systems Keywords: cyber-physical systems; WBAN security; biometric authentication; medical systems
Online: 14 November 2018 (08:03:19 CET)
A Wireless Body Area Network (WBAN) is a network of wirelessly connected sensing and actuating devices. WBANs used for recording biometric information and administering medication are classified as part of a Cyber Physical System (CPS). Preserving user security and privacy is a fundamental concern of WBANs, which introduces the notion of using biometric readings as a mechanism for authentication. Extensive research has been conducted regarding the various methodologies (e.g. ECG, EEG, gait, head/arm motion, skin impedance). This paper seeks to analyze and evaluate the most prominent biometric authentication techniques based on accuracy, cost, and feasibility of implementation. We suggest several authentication schemes which incorporate multiple biometric properties.
ARTICLE | doi:10.20944/preprints201810.0468.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: cyber physical systems; dual output inverter; rapid control prototype
Online: 22 October 2018 (05:27:36 CEST)
This paper presents a configuration of dual output single phase current source inverter with 6 switches for microgrid applications. The inverter is capable of delivering power to two independent set of loads of equal voltages or different voltages at the load end. The control strategy is based on Integral Sliding Mode Control (ISMC). The remote monitoring of the inverter is performed with cyber infrastructure. The cyber physical test bench is developed based on Reconfigurable I/O processor (NI MyRIO-1900) for control and monitoring of the inverter. The inverter prototype is tested in cyber physical test bench in laboratory conditions. The performance of the inverter is analyzed and monitored through the remote system. Also, the inverter is analyzed with different voltage conditions.
ARTICLE | doi:10.20944/preprints201706.0119.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: emulation; network threat; network attack; network services; network topology; cyber defence exercises
Online: 27 June 2017 (05:16:41 CEST)
This paper outlines a tool developed with the purpose of creating a simple configurable emulated network environment that can be used in cyber defence exercises. Research has been conducted into the various related subject areas: cyber defence exercises, network threats, network emulation, network traffic replay, network topologies, and common network services. From this research a requirements specification was produced to encapsulate the features required to create this tool. A network, containing many of the aspects researched, was designed and implemented using Netkit-NG to act as a blueprint for the tool and to further knowledge in the construction of an emulated network. Following this the tool was developed and tested to ensure requirements were met.
ARTICLE | doi:10.20944/preprints202305.1492.v1
Subject: Computer Science And Mathematics, Computer Networks And Communications Keywords: Cloud security; Cloud computing; machine learning; industrial cyber security
Online: 22 May 2023 (09:57:21 CEST)
Cloud computing has revolutionized how industries store, process, and access data. However, the increasing adoption of cloud technology has also raised concerns regarding data security. Machine learning (ML) is a promising technique to enhance cloud computing security. This paper focuses on utilizing ML techniques (Support Vector Machine, XGBoost, and Artificial Neural Networks) to progress cloud computing security in the industry. The selection of 11 important features for the ML study satisfies the study's objectives. This study focused on identifying gaps in utilizing ML techniques in cloud cyber security. Moreover. this study aims at developing a practical strategy for predicting the employment of machine learning in an Industrial Cloud environment regarding trust and privacy issues. The efficiency of the employed models is assessed by applying validation matrices of Precision, Accuracy, Recall values, F1 score, R.O.C. curves, and Confusion matrix. The results demonstrated that the X.G.B. model outperformed in terms of all the matrices with an Accuracy of 97.50 %, 97.60 % Precision, 97.60 % Recall values, and 97.50 % F1 score. This research highlights the potential of ML algorithms in enhancing cloud computing security for industries. It emphasizes the need for continued research and development to create more advanced and efficient security solutions for cloud computing.
Subject: Business, Economics And Management, Accounting And Taxation Keywords: cyber-physical systems; digital twin; subject orientation; agent-based systems
Online: 7 December 2020 (09:00:51 CET)
Cyber-Physical Systems form the new backbone of digital ecosystems. Their design can be coupled with engineering activities to facilitate dynamic adaptation and (re-)configuration. Behavior-oriented technologies enable highly distributed and while coupled operation of systems. Utilizing them for digital twins as self-contained design entities with federation capabilities makes them promising candidates to develop and run highly functional CPS. In this paper we discuss mapping CPS components to behavior-based digital twin constituents mirroring integration and implementation through subject-oriented models. These models, inspired by agent-oriented system thinking can be executed and increase transparency at design and runtime. Patterns recognizing environmental factors and operation details facilitate configuration of CPS. Subject-oriented runtime support enable dynamic adaptation and federated use.
ARTICLE | doi:10.20944/preprints202004.0167.v1
Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: cyber physical systems; industry 4.0; human machine interaction; sustainable production
Online: 10 April 2020 (07:46:10 CEST)
In current efforts to digitize manufacturing and move it into the fourth stage of the industrial revolution, a wide range of integration solutions is being considered to enable manufacturing to adapt to change. In transforming a factory into a self-organized, autonomous factory, companies are currently struggling with rapidly changing requirements and production factors, among other things. This is a particular problem for the human being as an actor within the factory, as the amount of new technologies and protocols increases the training effort. Proprietary interfaces of the control providers, a wide range of different communication protocols, complicate the understanding of the production processes, the evaluation and testability of new use cases and increase the danger of creating silos of knowledge as well as building collaboration barriers. As a solution to these problems, we propose an open software platform and define a way to model use case driven domain specific asset representation (DSA) that focuses on the human being and his needs for representing the factory in a way that it meets his requirements for the current production needs. We therefore conducted research on google scholar on human factors in industry 4.0 and used technologies as well as already existing platforms and their architecture.
REVIEW | doi:10.20944/preprints202303.0497.v1
Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Cyber physical systems 1; Cyber attacks 2; Artificial Intelligence 3; Machine learning 4; 8 Deep learning 5
Online: 29 March 2023 (02:48:39 CEST)
Importance and need for cyber security have increased in folds since a decade. Indirectly, the country’s security depends on the country’s cyber-physical systems. Attackers are becoming more innovative, and attacks are becoming undetectable, causing huge risks to the systems. In this scenario, intelligent and evolving detection methods should be introduced to replace the basic and outworn ones. This article discusses about new-age intelligence and smart techniques dealing with artificial intelligence (AI) models. Artificial intelligence for cyber security is reviewed, and the performance of machine learning models (ML) and deep learning (DL) models are analysed.
ARTICLE | doi:10.20944/preprints202303.0135.v1
Subject: Computer Science And Mathematics, Information Systems Keywords: Cyber Risk Assessment; Evaluation; cyber-physical systems; ATT&CK; FMECA; maritime; energy; autonomous passenger ship; digital substation
Online: 7 March 2023 (14:57:52 CET)
In various domains such as energy, manufacturing, and maritime, cyber-physical systems (CPS) have seen increased interest. Both academia and industry have focused on the cybersecurity aspects of such systems. The assessment of cyber risks in CPS is a popular research area with many existing approaches that aim to suggest relevant methods and practices. However, few works have addressed the extensive and objective evaluation of the proposed approaches. In this paper, a standard-aligned evaluation methodology is presented and empirically conducted to evaluate a newly proposed cyber risk assessment approach for CPS. The approach, which is called FMECA-ATT&CK is based on Failure Mode, Effects & Criticality Analysis (FMECA) risk assessment process and enriched with the semantics and encoded knowledge in the Adversarial Tactics, Techniques, and Common Knowledge framework (ATT&CK). Several experts were involved in conducting two risk assessment processes, FMECA-ATT\&CK and Bow-Tie, against two use cases in different application domains, particularly an autonomous passenger ship (APS) as a maritime use case and a digital substation as an energy use case. This allows for the evaluation of the approach based on a group of characteristics, namely, applicability, feasibility, accuracy, comprehensiveness, adaptability, scalability, and usability. The results highlight the positive utility of FMECA-ATT&CK in model-based, design-level, and component-level cyber risk assessment of CPS with several identified directions for improvements. Moreover, the standard-aligned evaluation method and the evaluation characteristics have been demonstrated as enablers for the thorough evaluation of cyber risk assessment methods.
ARTICLE | doi:10.20944/preprints201903.0094.v1
Subject: Engineering, Control And Systems Engineering Keywords: Internet of Things; Cyber Physical Systems; Digital Economy; Industrial Internet of Things; Industry 4.0; empirical analysis; cyber risk assessment; cyber risk target state
Online: 7 March 2019 (12:25:15 CET)
The world is currently experiencing the fourth industrial revolution driven by the newest wave of digitisation in the manufacturing sector. The term Industry 4.0 (I4.0) represents at the same time: a paradigm shift in industrial production, a generic designation for sets of strategic initiatives to boost national industries, a technical term to relate to new emerging business assets, processes and services, and a brand to mark a very particular historical and social period. I4.0 is also referred to as Industrie 4.0 the New Industrial France, the Industrial Internet, the Fourth Industrial Revolution and the digital economy. These terms are used interchangeably in this text. The aim of this article is to discuss major developments in this space in relation to the integration of new developments of IoT and cyber physical systems in the digital economy, to better understand cyber risks and economic value and risk impact. The objective of the paper is to map the current evolution and its associated cyber risks for the digital economy sector and to discuss the future developments in the Industrial Internet of Things and Industry 4.0.
ARTICLE | doi:10.20944/preprints202303.0331.v1
Subject: Engineering, Chemical Engineering Keywords: Cyber-physical system; Internet of things; Security pattern; Security solution frame
Online: 20 March 2023 (02:12:35 CET)
Sensors and actuators are fundamental units in Cyber-Physical and Internet of Things systems. Because they are included in a variety of systems, using many technologies, it is very useful to characterize their functions abstractly by describing them as Abstract Entity Patterns (AEPs), that are patterns that describe abstract conceptual entities. For concreteness, we study them here in the context of autonomous cars. An autonomous car is a complex system because, in ad-dition to its own complex design, it interacts with other vehicles and with the surrounding in-frastructure. To handle these functions, it must incorporate various technologies from different sources. An autonomous car is an example of a Cyber-Physical System, where some of its func-tions are performed by Internet of Things units. Sensors are extensively used in autonomous cars to measure physical quantities; actuators are commanded by controllers to perform appro-priate physical actions. From AEPs we can derive concrete patterns, a structure combining re-lated AEPs is an Entity Solution Frame (ESF). Both sensors and actuators are susceptible to mali-cious attacks due to the large attack surface of the system where they are used. Our work is in-tended to make autonomous cars more secure, which also increases their safety. Our final objec-tive is to build a Security Solution Frame for sensors and actuators of autonomous cars that will facilitate their secure design. A Security Solution Frame is a solution structure that groups to-gether and organizes related security patterns. This article is the first stage of a secure unit that can be used to design not only secure autonomous cars but also any system where sensors and actuators are used. This paper concentrates on AEPs and ESFs for sensors and actuators; that is, on the functional aspects of these devices.
ARTICLE | doi:10.20944/preprints202005.0384.v1
Subject: Engineering, Industrial And Manufacturing Engineering Keywords: 5G Wireless Technology; Artificial Intelligence; Blockchain; Cloud Computing; Cyber-Physical System
Online: 24 May 2020 (16:10:26 CEST)
The landscape of centralized cloud computing is now changing to distributed and decentralized clouds with promising impacts on energy consumption, resource availability, resilience, and customer experience. This research highlights the impacts of emerging IT trends, namely, 5G wireless technology, blockchain, and industrial Artificial Intelligence (AI) in development and realization of the next generation of cloud computing. Integration of these technologies in cyber-physical system and cloud manufacturing paradigms is explained and a unified edge-fog-cloud architecture is proposed for successful implementation in manufacturing systems.
ARTICLE | doi:10.20944/preprints201905.0099.v1
Subject: Engineering, Industrial And Manufacturing Engineering Keywords: Real-Time Networks; Scheduling; Time-Triggered; SMT Solvers; Cyber-Physical Systems
Online: 8 May 2019 (11:53:33 CEST)
Future cyber-physical systems may extend over broad geographical areas, like cities or regions, thus requiring the deployment of large real-time networks. A strategy to guarantee predictable communication over such networks is to synthesize an offline time-triggered communication schedule. However, this synthesis problem is computationally hard (NP-complete), and existing approaches do not scale satisfactorily to the required network sizes. This article presents a segmented offline synthesis method which substantially reduces this limitation, being able to generate time-triggered schedules for large hybrid (wired and wireless) networks. We also present a series of algorithms and optimizations that increase the performance and compactness of the obtained schedules while solving some of the problems inherent to segmented approaches. We evaluate our approach on a set of realistic large-size multi-hop networks, significantly larger than those considered in the existing literature. The results show that our segmentation reduces the synthesis time up to two orders of magnitude.
REVIEW | doi:10.20944/preprints201804.0066.v1
Subject: Computer Science And Mathematics, Information Systems Keywords: cyber physical systems; cybercrime; risk mitigation; risk management; industrial control systems
Online: 5 April 2018 (06:10:06 CEST)
Cyber Physical Systems (CPS) is the integration of computation and physical process that makes a complete system such as the physical components, networked systems, embedded computers and software and linking together of devices and sensors for information sharing. Cyber Physical Systems are Smart Systems that comprises of the merging and integration of Industry Control Systems, Critical Infrastructures, Internet of Things (IoT) and Embedded Systems. Major industries such as the Chemical and Industrial Plants, Aviation Systems, National Grid, the Stock Exchange, Military Systems, and others depends heavily on these Cyber Physical Systems for financial and economic growth. The benefits of CPS nationally and globally are in the areas of Manufacturing, Energy, Transport, Healthcare and Communication. Cyber Physical Systems incorporates Physical systems, Digital systems and Human elements on network infrastructures to provide interactive systems. However, these three key components the Physical systems, Digital systems and Human elements may have inherent threats and vulnerabilities on them that may run the risk of being compromise, exploited, attacked or hacked. Cybercriminals in their quest to bring down these systems and may cause disruption of services either for fame, revenge, political motive, economic war, cyber terrorism and cyber war. The study seeks to review the risks that are associated with these three key components Physical systems, Digital systems and Human elements. The study considered four main risk mitigation goals for this purpose, and these are Business Value, Organizational Requirements, Threat Agent and Impact based on the review results. We used Analytical Hierarchical Process (AHP) to determine the relative importance of these goals that contributes to developing cybercrime and rich in CPS. For the results, the prioritized goals are then used to assess the risks using a semi-quantitative approach to determine the net threat level.
ARTICLE | doi:10.20944/preprints202304.0657.v1
Subject: Engineering, Telecommunications Keywords: Intelligent reflecting surface; Cognitive radio; Physical layer security; Transmit beamforming; Artificial noise
Online: 21 April 2023 (02:27:26 CEST)
Abstract- Cognitive radio (CR) play an important role in improving spectral efficiency (SE) of wireless communication, meanwhile, intelligent reflecting surface (IRS) is an effective technology to improve the secrecy performance of wireless communication system by adjusting the phase shift and amplitude of channel. Thus, we consider an IRS-aided multiple-input single-output (MISO) CR systems to enhance secrecy rate, which is consists of a single eavesdropping link, a primary network containing the primary receiver (PR), and secondary network including secondary receiver (SR) and the SR transmitter (SR-TX). Specifically, we minimize the transmit power of SR subject to secrecy capacity constraint and interference temperature (IT) constraint on PR, by jointly optimizing the beamforming vector and artificial noise (AN) constraints matrix at SR-TX as well as the phase shift matrix of IRS. Numerical results show that the different values of transmit antennas at the SR-TX and the number of IRS elements can significantly decrease the transmit power under the condition of ensuring secure communication.
ARTICLE | doi:10.20944/preprints201910.0032.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: computerized revenue collection; machine learning; cyber security; software defined networks; object-oriented programming; online database management
Online: 3 October 2019 (01:45:11 CEST)
The need for the most accurate and flexible system of revenue collection from internal sources has become a matter of extreme urgency and importance in e-governance. This need underscores the eagerness on the part of the Government to look for a new principle and policy of revenue collection or to become aggressive and innovative in the mode of collecting revenue from existing sources using the present system. The Boards of some Governments in Africa, even up to the moment are facing a lot of setbacks in performing their tasks due to the manual system of revenue collection from the public. This can be improved through an effective collection of revenue using the most accurate and flexible system. Tax is usually collected in the form of specific sales tax, general sales tax, corporate income tax, individual income tax, property tax and inheritance tax. Problems such as high cost of collection, fraud, underpayment, leakage in revenue, poor access to information, poor tracking of defaulters is at the increase. As a result of this, there is need to computerize the revenue collection system. Computerized systems have proven to introduce massive efficiencies and quick collection of revenue from the public. This research work demonstrates how to design and implement an automated system of revenue collection and how to maintain a secured database for collected tax information. This research delves into the study of how machine learning algorithms and Software-defined Networks improve the security of such automated systems.
ARTICLE | doi:10.20944/preprints201910.0368.v2
Subject: Engineering, Electrical And Electronic Engineering Keywords: directional modulation; physical layer security; polarization sensitive array; multi-beam
Online: 5 December 2019 (11:59:29 CET)
Directional modulation (DM), as an emerging promising physical layer security (PLS) technique at the transmitter side with the help of an antenna array, has developed rapidly over decades. In this study, a DM technique using a polarization sensitive array (PSA) to produce the modulation with different polarization states (PSs) at different directions is investigated. A PSA, as a vector sensor, can be employed for more effective DM for an additional degree of freedom (DOF) provided in the polarization domain. The polarization information can be exploited to transmit different data streams simultaneously at the same directions, same frequency, but with different PSs in the desired directions to increase the channel capacity, and with random PSs off the desired directions to enhance PLS. The proposed method has the capability of concurrently projecting independent signals into different speciﬁed spatial directions while simultaneously distorting signal constellation in all other directions. The symbol error rate (SER), secrecy rate, and the robustness of the proposed DM scheme are analyzed. Design examples for single- and multi-beam DM systems are also presented. Simulations corroborate that 1) the proposed method is more effective for PLS; 2) the proposed DM scheme is more power-efﬁcient than the traditional artiﬁcial noise aided DM schemes; and 3) the channel capacity is signiﬁcantly improved compared with conventional scalar antenna arrays.
Subject: Social Sciences, Education Keywords: digital competence; teacher education; privacy; cyber security; Internet; teachers; university; initial training; Competencia digital; formación del profesorado; privacidad; seguridad cibernética; Internet; docentes; universidad; formación inicial
Online: 17 October 2019 (12:22:39 CEST)
The use of technologies and the Internet poses problems and risks related to digital security. This article presents the results of a study on the evaluation of the digital competence of future teachers in the DigCompEdu European framework. 317 undergraduate students from Spain and Portugal answered a questionnaire with 59 items, validated by experts, in order to assess the level and predominant competence profile in initial training (including knowledge, uses and interactions and attitudinal patterns). The results show that 47% of the participants belong to the profile of teachers at medium digital risk, evidencing habitual practices that involve risks such as sharing information and digital content inappropriately, not using strong passwords, and ignoring concepts such as identity, digital “footprint” and digital reputation. The average valuations of each item in the seven categories show that future teachers have an average competence in the area of digital security. They have good attitudes toward security but less knowledge and fewer skills and practices related to the safe and responsible use of the Internet. Future lines of work are proposed, aimed at responding to the demand for a better prepared and more digitally competent citizenry. The demand for education in security, privacy and digital identity is becoming increasingly important, and these elements form an essential part of initial training.
REVIEW | doi:10.20944/preprints202208.0272.v1
Subject: Social Sciences, Sociology Keywords: agroecology; physical reproduction; social reproduction; agency; sub-Saharan Africa; smallholder agriculture
Online: 16 August 2022 (03:31:35 CEST)
This paper investigates how agroecology in Africa is researched for two purposes. First, we present evidence of links between agroecology and food and nutrition security in sub-Saharan Africa. Second, we investigate which pathways of influence are dominant in the existing research and which pathways are under-represented. To achieve these objectives we anchor our analysis within feminist economics, thereby making use of the concepts of social reproduction and agency in our analysis of the literature. By employing a systematic literature review of empirical studies from African countries, starting from 1996 to 2020, we consolidate evidence that agroecology has contributed to food and nutrition security by acting toward sustainability at the farm level. However, our review shows in a second step that social and household dimensions of agroecology at the level of households and territories are not well documented in research linking agroecology to food security and nutrition in sub-Saharan Africa. Given that sustainable production practices such as agroecological practices are not mutually exclusive from the social activities of farmers and cultural contexts in which farmers are embedded, it is important to consider social and ecological processes concomitantly when assessing the value of Agroecology programs.
REVIEW | doi:10.20944/preprints202209.0230.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: artificial intelligence; autonomous vehicles; connected vehicles; CAV; security; cyber-attacks; In-tra-/inter-vehicle system; cloud; sustainable city application
Online: 15 September 2022 (11:04:34 CEST)
Connected and Autonomous Vehicle (CAV) combines technologies of autonomous vehicle (AV) and connected vehicles (CV) to develop quicker, more reliable and safer traffic. Artificial Intelligence (AI) based CAV solutions play significant roles in sustainable city. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on driver; increased connectivity increases the exposures of vehicles vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles vulnerabilities to negatively impact the performance and operations of CAV. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAV, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAV is elaborated from both viewpoints of intra-vehicle system and inter-vehicle system. We pointed out that securing the perception and operations of CAV would be the top requirement to enable CAV to be applied safely and reliably in practice. Also, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAV.
REVIEW | doi:10.20944/preprints202203.0087.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Things; cyber-attacks; anomalies; machine learning; deep learning; IoT data analytics; intelligent decision-making; security intelligence
Online: 7 March 2022 (02:39:58 CET)
The Internet of Things (IoT) is one of the most widely used technologies today, and it has a significant effect on our lives in a variety of ways, including social, commercial, and economic aspects. In terms of automation, productivity, and comfort for consumers across a wide range of application areas, from education to smart cities, the present and future IoT technologies hold great promise for improving the overall quality of human life. However, cyber-attacks and threats greatly affect smart applications in the environment of IoT. The traditional IoT security techniques are insufficient with the recent security challenges considering the advanced booming of different kinds of attacks and threats. Utilizing artificial intelligence (AI) expertise, especially machine and deep learning solutions, is the key to delivering a dynamically enhanced and up-to-date security system for the next-generation IoT system. Throughout this article, we present a comprehensive picture on IoT security intelligence, which is built on machine and deep learning technologies that extract insights from raw data to intelligently protect IoT devices against a variety of cyber-attacks. Finally, based on our study, we highlight the associated research issues and future directions within the scope of our study. Overall, this article aspires to serve as a reference point and guide, particularly from a technical standpoint, for cybersecurity experts and researchers working in the context of IoT.
ARTICLE | doi:10.20944/preprints201808.0482.v1
Subject: Engineering, Industrial And Manufacturing Engineering Keywords: inverse problem; industrial tomography; machine learning, sensors, cyber-physical system, Industry 4.0
Online: 29 August 2018 (05:56:49 CEST)
The article presents a cyber-physical system for acquiring, processing and reconstructing images from measurement data. The technology was based on process tomography, intelligent measurement sensors, machine learning, Big Data, Cloud Computing, Internet of Things as a solution for Industry 4.0. Industrial tomography enables observation of physical and chemical phenomena without the need of internal penetration and allows real-time monitoring of production processes. The application includes specialized intelligent devices for tomographic measurements and dedicated algorithms for solving the inverse problem. The work focuses mainly on electrical tomography and image reconstruction using deterministic methods and machine learning, the reconstruction results were compared, different measurement models were used. The researches were carried out for synthetic data and laboratory measurements. The main advantage of the proposed system is the possibility of spatial data analysis and their high processing speed. The presented research results show that the process tomography gives the possibility to analyse the processes taking place inside the facility without disturbing the production, analysis and detection of obstacles, defects and various anomalies. Knowing the characteristics of a given solution, the application allows you to choose the appropriate method to reconstruct the image.
ARTICLE | doi:10.20944/preprints202001.0303.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Things (IoT); physical layer attack; routing security; Average Packet Transmission
Online: 26 January 2020 (03:57:09 CET)
Through the Internet of Things (IoT) the internet scope is established by the aid of physical objects integration to classify themselves to mutual things. A physical object can be created by this inventive perception to signify itself in the digital world. Regarding the physical objects that are related to the internet, it is worth to mention that considering numerous theories and upcoming predictions, they mostly require protected structures, moreover, they are at risk of several attacks. IoTs are endangered by particular routing disobedience called physical layer attack owing to their distributed features. The physical layer attack as a security warning makes possible for the invader to abuse the resources and bandwidth of the network through overloading the network via unimportant packets. This protocol is called LSFA-IoT consisting of two key sections of the physical layer detection system and misbehavior detection system. The first section is utilized in stabilizing the status of the network. The second section is in charge of discovering the misbehavior sources within the IoT network through , the Average Packet Transmission RREQ. By detecting a malicious node, the status of the node is checked by LSFA-IoT prior to sending a data packet and in case detecting the node as malicious, no packet is sent to that node and that node is added to the detention list. Here, the technique is assessed through wide simulations performed within the NS-3 environment. Based on the results of the simulation, it is indicated that the IoT network behaviour metrics are enhanced based on the detection rate, false-negative rate, false-positive rate, and packet delivery rate.
REVIEW | doi:10.20944/preprints202206.0134.v1
Subject: Engineering, Control And Systems Engineering Keywords: smart factory; advanced manufacturing; intelligent manufacturing; Cyber Manufacturing; Cyber Physical Systems; Internet of Things; Industry 4.0; Artificial Intelligence; data driven manufacturing
Online: 9 June 2022 (04:05:14 CEST)
In a dynamic and rapidly changing world, customers’ often conflicting demands plus fluid economic requirements, often driven by geo-politics, have continued to evolve, out-striping the capability of existing production systems. With its inherent shortcomings, the traditional factory has proven to be incapable of addressing these modern-day manufacturing challenges. Recent advancements in Industry 4.0 have catalyzed the development of new manufacturing paradigms (or smart factory visions) under different monikers (e.g., Smart factory, Intelligent factory, Digital factory, Cloud-based factory etc.) would help fix these challenges. Due to a lack of consensus on a general nomenclature for these manufacturing paradigms, the term Future Factory (or Factory of the Future) is here used as a collective euphemism, without prejudice. The Future Factory constitutes a creative convergence of multiple technologies, techniques and capabilities that represent a significant change in current production capabilities, models, and practices. It is a data-driven manufacturing approach and system that harnesses intelligence from multiple information streams i.e., assets (including people), processes, and subsystems to help create new forms of production efficiency and flexibility. Serving both as a review monograph and reference companion, this paper details the meanings, characteristics, and technological underpinnings of the Future Factory. It also elucidates on the architectural models that guide the structured deployment of these modern factories with particular emphasis on three advanced communication technologies capable of speeding up advancements in the field. It not only highlights the relevance of communication between assets but also lays out mechanisms to achieve these interactions using the Administration shell. Finally, the paper also discusses the key enabling technologies that are typically embedded into bare bone factories to help improve their visibility, resilience, intelligence, and capacity, in addition to how these technologies are being deployed and to what effect. At the onset of the study, we were interested in developing a monograph which would serve as a comprehensive but concise review of general principles, fundamental concepts, major characteristics, key building blocks and implementation guidelines for the Future Factory within the overall context of the manufacturing ecosystem, in the age of Industry 4.0. Our hope is that this paper would enrich the extant literature on advanced manufacturing, help shape policy and research, and provide insights on how some of the identified pathways can be diffused into industry.
ARTICLE | doi:10.20944/preprints202008.0603.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: secure boot; cyber-physical system security; embedded systems; FPGA; hardware primitives; IoT security
Online: 27 August 2020 (08:49:02 CEST)
Reconfigurable computing is becoming ubiquitous in the form of consumer-based Internet of Things (IoT) devices. Reconfigurable computing architectures have found their place in safety-critical infrastructures such as the automotive industry. As the target architecture evolves, it also needs to be updated remotely on the target platform. This process is susceptible to remote hijacking, where the attacker can maliciously update the reconfigurable hardware target with tainted hardware configuration. This paper proposes an architecture of establishing Root of Trust at the hardware level using cryptographic co-processors and Trusted Platform Modules (TPMs) and enable over the air updates. The proposed framework implements secure boot protocol on Xilinx based FPGAs. The project demonstrates the configuration of the bitstream, boot process integration with TPM and secure over-the-air updates for the hardware reconfiguration.
ARTICLE | doi:10.20944/preprints202005.0213.v1
Subject: Engineering, Architecture, Building And Construction Keywords: BIM; construction; critical infrastructure; cybersecurity; cyber-physical systems; digital twin; EPCIP; Industry 4.0
Online: 12 May 2020 (12:44:01 CEST)
The umbrella concept for the current efforts to digitize construction is known as Construction 4.0. One of its key concepts is cyber-physical systems. The construction industry is not only creating increasingly valuable digital assets (in addition to physical ones) but also the buildings and built infrastructures are increasingly monitored and controlled using digital technology. Both make construction a vulnerable target of cyber-attacks. While the damage to digital assets, such as designs and cost calculations, may result in economic damage, attacks on digitally-controlled physical assets may damage the well-being of occupants and, in worst-case scenarios, even damage (or death) to the users. The problem is amplified by the emerging cyber-physical nature of the systems, where the human checks may be left out. We propose that construction learns from the work done in the context of critical infrastructures (CI). First, a lot of CI is construction-related, and the process of designing and building it must be secured accordingly. Second, while most assets may not be critical in the CI sense, they are critical to the operations of a business and the lives of citizens. In the end, we recommend some steps so that well-established processes of critical infrastructure protection trickle down to make Construction 4.0 and the built environment more cyber-secure. With that in mind, we describe the possible inclusion of Construction 4.0 considerations into existing critical infrastructure protection (CIP) frameworks with minimum frictions. We also propose some suggestions regarding possible future courses of action to improve the increasingly vulnerable cyber-security environment of the built environment across all life cycle phases - design, construction, operation, maintenance, and end of life.
Subject: Engineering, Industrial And Manufacturing Engineering Keywords: Cloud manufacturing, Computer Numerical Control (CNC), Control as a Service, Cyber-physical system
Online: 28 May 2019 (10:25:13 CEST)
Cloud-based CNC is an emerging paradigm of Industry 4.0 where computer numerical control (CNC) functionalities are moved to the cloud and provided to manufacturing machines as a service. Among many benefits, C-CNC allows manufacturing machines to leverage advanced control algorithms running on cloud computers to boost their performance at low cost, without need for major hardware upgrades. However, a fundamental challenge of C-CNC is how to guarantee safety and reliability of machine control given variable Internet quality of service, especially on public Internet networks. We propose a three-tier redundant architecture to address this challenge. We then prototype tier one of the architecture on a 3D printer successfully controlled via C-CNC over public Internet connections, and discuss follow-on research opportunities.
ARTICLE | doi:10.20944/preprints202008.0598.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: physical unclonable function; bloom filter; hardware security; PUF; memristor
Online: 27 August 2020 (08:05:03 CEST)
Because the development of the internet of things (IoT) requires technology that transfers information between objects without human intervention, the core of IoT security will be secure authentication between devices or between devices and servers. Software-based authentication may be a security vulnerability in IoT, but hardware-based security technology can provide a strong security environment. A physical unclonable functions (PUFs) are a hardware security element suitable for lightweight applications. PUFs can generate challenge-response pairs(CRPs) that cannot be controlled or predicted by utilizing inherent physical variations that occur in the manufacturing process. In particular, pulse width memristive PUF (PWM-PUF) improves security performance by applying different write pulse widths and bank structures. Bloom filter (BF) is probabilistic data structures that answer membership queries using small memories. Bloom filter can improve search performance and reduce memory usage and are used in areas such as networking, security, big data, and IoT. In this paper, we propose a structure that applies Bloom filters based on the PWM-PUF to reduce PUF data transmission errors. The proposed structure uses two different Bloom filter types that store different information and that are located in front of and behind the PWM-PUF, improving security by removing challenges from attacker access. Simulation results show that the proposed structure decreases the data transmission error rate and reuse rate as the Bloom filter size increases, the simulation results also show that the proposed structure improves PWM-PUF security with a very small Bloom filter memory.
ARTICLE | doi:10.20944/preprints202007.0409.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: Demand Side Management; Demand Response; Cyber-Physical Systems; Dynamic Pricing; Load Forecasting; Attack Detection
Online: 19 July 2020 (11:14:01 CEST)
Demand-Side Management (DSM) is an essential tool to ensure power system reliability and stability. In future smart grids, certain portions of a customer’s load usage could be under the automatic control of a cyber-enabled DSM program, which selectively schedules loads as a function of electricity prices to improve power balance and grid stability. In this scenario, the security of DSM cyberinfrastructure will be critical as advanced metering infrastructure and communication systems are susceptible to cyber-attacks. Such attacks, in the form of false data injections, can manipulate customer load profiles and cause metering chaos and energy losses in the grid. The feedback mechanism between load management on the consumer side and dynamic price schemes employed by independent system operators can further exacerbate attacks. To study how this feedback mechanism may worsen attacks in future cyber-enabled DSM programs, we propose a novel mathematical framework for (i) modeling the nonlinear relationship between load management and real-time pricing, (ii) simulating residential load data and prices, (iii) creating cyber-attacks, and (iv) detecting said attacks. In this framework, we first develop time-series forecasts to model load demand and use them as inputs to an elasticity model for the price-demand relationship in the DSM loop. This work then investigates the behavior of such a feedback loop under intentional cyber-attacks. We simulate and examine load-price data under different DSM-participation levels with three types of random additive attacks: ramp, sudden, and point attacks. We conduct two investigations for the detection of DSM attacks. The first studies a supervised learning approach, with various classification models, and the second studies the performance of parametric and nonparametric change point detectors. Results conclude that higher amounts of DSM participation can exacerbate ramp and sudden attacks leading to better detection of such attacks, especially with supervised learning classifiers. We also find that nonparametric detection outperforms parametric for smaller user pools, and random point attacks are the hardest to detect with any method.
ARTICLE | doi:10.20944/preprints201612.0135.v1
Subject: Engineering, Industrial And Manufacturing Engineering Keywords: context sensitivity; cyber physical systems; flexible manufacturing system; process optimization; self-learning systems; SOA
Online: 28 December 2016 (11:13:22 CET)
Highly flexible manufacturing systems require continuous run-time (self-) optimization of processes with respect to various parameters, e.g. efficiency, availability, energy consumption etc. A promising approach for achieving (self-) optimization in manufacturing systems is the usage of the context sensitivity approach. Thereby the Cyber-Physical Systems play an important role as sources of information to achieve context sensitivity. In this paper it is demonstrated how context sensitivity can be used to realize a holistic solution for (self-) optimization of discrete flexible manufacturing systems, by making use of Cyber-Physical System integrated in manufacturing systems/processes. A generic approach for context sensitivity, based on self-learning algorithms, is proposed aiming at a various manufacturing systems. The new solution is propos encompassing run-time context extractor and optimizer. Based on the self-learning module both context extraction and optimizer are continuously learning and improving their performance. The solution is following Service Oriented Architecture principles. The generic solution is developed and then applied to two very different manufacturing processes. This paper proposes a holistic solution to achieve context sensitivity for Flexible Manufacturing Systems, whereby the knowledge created by applying the context sensitivity approach can be used for (self-) optimization of manufacturing processes.
ARTICLE | doi:10.20944/preprints201903.0104.v1
Subject: Engineering, Control And Systems Engineering Keywords: cyber risk; Internet of Things; cyber risk impact assessment; cyber risk estimation; cyber risk insurance
Online: 8 March 2019 (08:50:49 CET)
In this paper we present an understanding of cyber risks in the Internet of Things (IoT), we explain why it is important to understand what IoT cyber risks are and how we can use risk assessment and risk management approaches to deal with these challenges. We introduce the most effective ways of doing Risk assessment and Risk Management of IoT risk. As part of our research, we also developed methodologies to assess and manage risk in this emerging environment. This paper will take you through our research and we will explain: what we mean by the IoT; what we mean by risk and risk in the IoT; why risk assessment and risk management are important; the IoT risk management for incident response and recovery; what open questions on IoT risk assessment and risk management remain.
ARTICLE | doi:10.20944/preprints202303.0499.v1
Subject: Medicine And Pharmacology, Other Keywords: Internet of Medical Things; Arbiter PUF; security and privacy; physical unclonable function; machine learning; authentication framework
Online: 29 March 2023 (03:25:19 CEST)
The Internet of Medical Things (IoMT) is playing a pivotal role in the healthcare sector by allowing faster and more informed hospital care, personalized treatment, and medical solutions. A very effective and trustworthy solution for resource-constrained medical devices is provided by Physical Unclonable Functions (PUF) - based identity and authentication systems, however they are not yet entirely reliable. This paper proposes VXorPUF, a Vedic Principles - Based Hybrid XOR Arbiter PUF. Modeling attacks were performed on the proposed architecture and an accuracy of 49.80 % was achieved. Uniqueness, Reliability and Randomness were the figures of merit used to evaluate PUF.
REVIEW | doi:10.20944/preprints202208.0483.v1
Subject: Computer Science And Mathematics, Computer Science Keywords: Digital Twins; Cyber-Physical Systems; Control; Communication; Computation; 5G; Artificial Intelligence; Machine Learning; Computational Intelligence
Online: 29 August 2022 (09:51:49 CEST)
Cyber-Physical Systems (CPS) are integrations of computation and physical processes. Physical processes are monitored and controlled by embedded computers and networks, which frequently have feedback loops where physical processes affect computations and vice versa. To ease the analysis of a system, the costly physical plants can be replaced by high-fidelity virtual models that provide a framework for Digital-Twins (DT). This paper aims to briefly review the state-of-the-art and recent developments in DT and CPS. Three main components in CPS, including communication, control, and computation, are reviewed. Besides, the main tools and methodologies required for implementing practical DT are discussed by following the main applications of DT in the fourth industrial revolution through aspects of smart manufacturing, sixth wireless generation (6G), health, production, energy, and so on. Finally, the main limitations and ideas for future remarks are talked about followed by a short guideline for real-world application of DT towards CPS.
ARTICLE | doi:10.20944/preprints202303.0324.v2
Subject: Computer Science And Mathematics, Logic Keywords: physical unclonable functions; true-random number generator; hardware security; key generation; reconfigurable devices; embedded systems
Online: 20 March 2023 (02:40:31 CET)
The proliferation of devices for the Internet of Things (IoT) and their implication in many activities of our lives have led to a considerable increase in concern about the security of these devices, posing a double challenge for designers and developers of products. On the one hand, the design of new security primitives, suitable for resource-limited devices, that can facilitate the inclusion of mechanisms and protocols to ensure the integrity and privacy of the data exchanged over the Internet. On the other hand, the development of techniques and tools to evaluate the quality of the proposed solutions as a step prior to their deployment, as well as to monitor their behavior once in operation against possible changes in operating conditions arising naturally or as a consequence of a stress situation forced by an attacker. To address these challenges, this paper first describes the design of a security primitive that plays an important role as a component of a hardware-based root of trust, as it can act as a source of entropy for true random number generation (TRNG) or as a physical unclonable function (PUF) to facilitate the generation of identifiers linked to the device on which it is implemented. The work also illustrates different software components that allow carrying out a self-assessment strategy to characterize and validate the performance of this primitive in its dual functionality, as well as to monitor possible changes in security levels that may occur during operation as a result of device aging and variations in power supply or operating temperature. The designed PUF/TRNG is provided as a configurable IP module, which takes advantage of the internal architecture of the Xilinx Series-7 and Zynq-7000 programmable devices and incorporates an AXI4-based standard interface to facilitate its interaction with soft- and hard-core processing systems. Several test systems that contain different instances of the IP have been implemented and subjected to an exhaustive set of on-line tests to obtain the metrics that determine its quality in terms of uniqueness, reliability, and entropy characteristics. The results obtained prove that the proposed module is a suitable candidate for various security applications. As an example, an implementation that uses less than 5% of the resources of a low-cost programmable device is capable of obfuscating and recovering 512-bit cryptographic keys with virtually zero error rate.
Subject: Engineering, Control And Systems Engineering Keywords: Industrial Internet of Things; Cyber Physical Systems; Internet of Everything; Industry 4.0; Digital Industry; Digital Economy
Online: 14 September 2020 (05:47:48 CEST)
This article conducts a literature review of current and future challenges in the use of artificial intelligence (AI) in cyber physical systems. The literature review is focused on identifying a conceptual framework for increasing resilience with AI through automation supporting both, a technical and human level. The methodology applied resembled a literature review and taxonomic analysis of complex internet of things (IoT) interconnected and coupled cyber physical systems. There is an increased attention on propositions on models, infrastructures and frameworks of IoT in both academic and technical papers. These reports and publications frequently represent a juxtaposition of other related systems and technologies (e.g. Industrial Internet of Things, Cyber Physical Systems, Industry 4.0 etc.). We review academic and industry papers published between 2010 and 2020. The results determine a new hierarchical cascading conceptual framework for analysing the evolution of AI decision-making in cyber physical systems. We argue that such evolution is inevitable and autonomous because of the increased integration of connected devices (IoT) in cyber physical systems. To support this argument, taxonomic methodol- ogy is adapted and applied for transparency and justifications of concepts selection decisions through building summary maps that are applied for designing the hierarchical cascading conceptual framework.
ARTICLE | doi:10.20944/preprints202009.0630.v1
Subject: Computer Science And Mathematics, Computer Networks And Communications Keywords: Cyber security; cyber attacks; Covid-19; attack vulnerabilities
Online: 26 September 2020 (12:47:42 CEST)
In this COVID-19 pandemic, the use and dependency on Internet has grown exponentially. The number of people doing online activities such as e-learning, remote working, online shopping and others have increased. This has also led to increased vulnerability to cyber crimes. Cyber security attacks have become a serious problem. The common types of cyber security attacks are phishing, malware, ransomware, social engineering, identity theft and denial-of-service. The attackers target the victims in order to get their credential information or financial benefits. Those people who are doing online activities are vulnerable to cyber threats. This is because the network is not safe. The attackers are able to code according to the weaknesses of the Internet. Once the attackers hack into the devices, they have the root access and can do whatever they want to do with the device. In this research paper, the concept of cyber security attack and detailed research about real attacks are discussed. This is followed by detailed review about the recent cyber security attacks with a critical analysis. Moreover, the research paper will be proposing the latest research contribution of cyber security during COVID-19 and the implementation scenario which will give the examples about how the companies maintain privacy as well as the limitations. Then, the paper will be discussing the reasons that people are vulnerable to cyber security and the unique solution to the problems stated. Finally, this paper will conclude with an in-depth analysis and future direction for cyber security research.
ARTICLE | doi:10.20944/preprints201804.0369.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: row hammer; dynamic random access memory (DRAM); physical unclonable function (PUF); run-time accessible; security primitive
Online: 28 April 2018 (12:03:36 CEST)
Physical Unclonable Functions (PUFs) based on the retention times of the cells of a Dynamic Random Access Memory (DRAM) can be utilised for the implementation of cost-efficient and lightweight cryptographic protocols. However, as recent work has demonstrated, the times needed in order to generate their responses may prohibit their widespread usage. In order to address this issue, the Row Hammer PUF has been proposed by Schaller et al. , which leverages the row hammer effect in DRAM modules to reduce the retention times of their cells and, therefore, significantly speed up the generation times for the responses of PUFs based on these retention times. In this work, we extend the work of Schaller et al. by presenting a run-time accessible implementation of this PUF and further reducing the time required for the generation of its responses. Additionally, we also provide a more thorough investigation of the effects of temperature variations on the the Row Hammer PUF and briefly discuss potential statistical relationships between the cells used to implement it. As our results prove, the Row Hammer PUF could potentially provide an adequate level of security for Commercial Off-The-Shelf (COTS) devices, if its dependency on temperature is mitigated, and, may therefore, be commercially adopted in the near future.
ARTICLE | doi:10.20944/preprints201903.0110.v1
Subject: Computer Science And Mathematics, Information Systems Keywords: IoT Cyber Risk, IoT risk analysis, IoT cyber insurance, IoT MicroMort, Cyber Value-at-Risk
Online: 8 March 2019 (15:24:59 CET)
This paper is focused on mapping the current evolution of Internet of Things (IoT) and its associated cyber risks for the Industry 4.0 (I4.0) sector. We report the results of a qualitative empirical study that correlates academic literature with 14 - I4.0 frameworks and initiatives. We apply the grounded theory approach to synthesise the findings from our literature review, to compare the cyber security frameworks and cyber security quantitative impact assessment models, with the world leading I4.0 technological trends. From the findings, we build a new impact assessment model of IoT cyber risk in Industry 4.0. We therefore advance the efforts of integrating standards and governance into Industry 4.0 and offer a better understanding of economics impact assessment models for I4.0.
ARTICLE | doi:10.20944/preprints202205.0352.v1
Subject: Computer Science And Mathematics, Applied Mathematics Keywords: Quality real-time systems; Automated Machine Learning; Real-time embedded control systems; Cyber-physical systems; Neural Networks
Online: 25 May 2022 (11:17:19 CEST)
A correct system design can be systematically obtained from a specification model of a real-time system that integrates hybrid measurements in a realistic industrial environment, this has been carried out through complete Matlab / Simulink / Stateflow models. However, there is a widespread interest in carrying out that modeling by resorting to Machine Learning models, which can be understood as Automated Machine Learning for Real-time systems that present some degree of hybridization. An induction motor controller which must be able to maintain a constant air flow through a filter is one of these systems and it is discussed in the paper as a study case of closed-loop control system. The article discusses a practical application of ML methods that demonstrates how to replace such closed loop in industrial control systems with a Simulink block generated from neural networks to show how the proposed procedure can be applied to derive complete hybrid system designs with artificial neural networks (ANN). In the proposed ANN-based method to design a real-time hybrid system with continuous and discrete components, we use a typical design of a neural network, in which we define the usual phases: training, validation, and testing. The generated output of the model is made up of reference variables values of the cyber-physical system, which represent the functional and dynamic aspects of model. They are used to feed Simulink/Stateflow blocks in the real target system.
ARTICLE | doi:10.20944/preprints201912.0003.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: physical layer security (PLS); cooperative relay transmission; non-orthogonal multiple access (NOMA); fuzzy logic; feed forward neural networks (FFNN); secrecy capacity
Online: 2 December 2019 (04:30:17 CET)
Cooperative non-orthogonal multi access communication is a promising paradigm for the future wireless networks because of its advantages in terms of energy efficiency, wider coverage and interference mitigating. In this paper, we study the secrecy performance of a downlink cooperative non-orthogonal multi access (NOMA) communication system under the presence of an eavesdropper node. Smart node selection based on feed forward neural networks (FFNN) is proposed in order to improve the physical layer security (PLS) of a cooperative NOMA network. The selected cooperative relay node is employed to enhance the channel capacity of the legal users, where the selected cooperative jammer is employed to degrade the capacity of the wiretapped channel. Simulations of the secrecy performance metric namely the secrecy capacity ($C_S$) are presented and compared with the conventional technique based on fuzzy logic node selection technique. Based on our simulations and discussions the proposed technique outperforms the existing technique in term the of secrecy performance.
ARTICLE | doi:10.20944/preprints202301.0115.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Artificial Intelligence (AI); Machine Learning (ML); Cyber security; Uses of Cyber security; Future in Cyber security; AI and ML in Cyber security
Online: 6 January 2023 (04:39:20 CET)
Although, Artificial intelligence (AI) helps experts with crime analysis, research, and understanding, it has a favourable influence on cyber security. It strengthens the tools that businesses use to safeguard their networks, clients, and workers against dangerous online behaviour. However, artificial intelligence is infamous for requiring a lot of resources. It may not, however, always be relevant. Additionally, it can provide hackers a new tool and advance their abilities. Actually, the VPN industry benefits from AI in the same way. The threat posed by machine learning in AI to user data privacy may be lessened by using a VPN on all of your devices. Because they use machine learning algorithms, VPNs are better equipped to shield their users from internet-based threats. Artificial intelligence (AI) has reportedly being investigated as a means of enhancing internet security for a considerable amount of time, according to Smart Data Collective. We anticipated that AI and machine learning will have a substantial impact on the future of cyber security around two years ago.
REVIEW | doi:10.20944/preprints201808.0053.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: Smart grid; Monitoring System; Distribution System State Estimation, Information and Communication Technology, Distribution Management Systems, Distributed Energy Sources, Cyber-Physical Systems, Energy Management System, Energy Storage Systems, Cyber Security
Online: 2 August 2018 (17:25:01 CEST)
Electric power systems are experiencing relevant changes involving the growing penetration of distributed generation and energy storage systems, the introduction of electric vehicles, the management of responsive loads, the proposals for new energy markets and so on. Such evolution is pushing for a paradigm shift: the management must move from traditional planning and manual intervention to full “smartization” of medium and low voltage networks. Peculiarities and criticalities of future power distribution networks originate from the complexity of the system that includes both the physical aspects of electric networks and the cyber aspects, like data elaboration, feature extraction, communication, supervision and control; only fully integrated advanced monitoring systems can foster this transition towards network automation. The design and development of such future networks require distinct kinds of expertise in the industrial and information engineering fields. In this context, this paper provides a comprehensive review of current challenges and multidisciplinary interactions in the development of smart distribution networks.
CONCEPT PAPER | doi:10.20944/preprints202107.0557.v1
Subject: Computer Science And Mathematics, Information Systems Keywords: Industry 4.0; Cyber-Physical Systems (CPS); Internet of Things (IoT); Human factors; Automated production Systems; Social interactions; Social Networks
Online: 26 July 2021 (09:47:59 CEST)
Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap where human factor was seen as an important source of errors and disruptions. Today the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised the awareness about the central role humans have to play in manufacturing systems, to the design of which they must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different Human dimensions associated with CPS and IoT and focuses on their conceptual evolution of automatization to improve the sociability of such automated production systems and consequently puts again the human in the loop. Hereby, our aim is to take stock of current research trends, and to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. As results, different models of sociability as way to integrate human into the broad sense and/or the development of future automated production systems, were identified from the literature and analysed.
ARTICLE | doi:10.20944/preprints201804.0228.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: smart grid, cyber physical co-simulation, information and communication technology, 4g long term evolution - lte, network reconfiguration, fault management
Online: 17 April 2018 (16:36:34 CEST)
Simulation tools capturing the interactions of communication and electrical system operation represent a powerful support for fully assessing the potential benefits and impacts of ICT in future smart power distribution network. A strong interest is upon the possibility of exploiting the last generation communication systems for supporting the transition of distribution network towards a smart grid scenario. Having in mind the above, the authors propose a numerical co-simulation tool useful to thoroughly understand the impact of the communication networks on the performance of whole power system dynamics. The co-simulation tool has been purposely developed to simulate the highly time-critical smart grid application of fault management and network reconfiguration and permits reproducing and evaluating the behavior of the public mobile telecommunication system 4G Long Term Evolution (LTE), as communication technology for smart grid applications. Results of the paper demonstrates that LTE provides good performances for supporting the data communication required to perform fault location, extinction and a subsequent network reconfiguration in smart power distribution networks.
ARTICLE | doi:10.20944/preprints201907.0311.v1
Subject: Engineering, Automotive Engineering Keywords: Cyber-Physical Systems; reliability assessment; Internet-of-Things; LiDAR sensor; driving assistance; obstacle recognition; reinforcement learning; Artificial Intelligence-based modelling
Online: 28 July 2019 (12:38:28 CEST)
Currently, the most important challenge in any assessment of state-of-the-art sensor technology and its reliability is to achieve road traffic safety targets. The research reported in this paper is focused on the design of a procedure for evaluating the reliability of Internet-of-Things (IoT) sensors and the use of a Cyber-Physical System (CPS) for the implementation of that evaluation procedure to gauge reliability. An important requirement for the generation of real critical situations under safety conditions is the capability of managing a co-simulation environment, in which both real and virtual data sensory information can be processed. An IoT case study that consists of a LiDAR-based collaborative map is then proposed, in which both real and virtual computing nodes with their corresponding sensors exchange information. Specifically, the sensor chosen for this study is a Ibeo Lux 4-layer LiDAR sensor with IoT added capabilities. Implementation is through an artificial-intelligence-based modeling library for sensor data-prediction error, at a local level, and a self-learning-based decision-making model supported on a Q-learning method, at a global level. Its aim is to determine the best model behavior and to trigger the updating procedure, if required. Finally, an experimental evaluation of this framework is also performed using simulated and real data
REVIEW | doi:10.20944/preprints201901.0285.v1
Subject: Engineering, Control And Systems Engineering Keywords: cyber physical systems; industry 4.0; MDE; lifetime verification & validation; dependability; correctness; flexibility; real-time self-adaptation, self-management; self-healing
Online: 29 January 2019 (04:45:47 CET)
Cyber Physical Systems (CPS) has been a popular research area in the last decade. The dependability of CPS is still a critical issue, and rare survey has been published in this domain. CPS is a dynamic complex system, which involves various multidisciplinary technologies. To avoid human error and to simplify management, self-management CPS (SCPS) is a wise choice. And to achieve dependable self-management, systematic solution is necessary to verify the design and to guarantee the safety of self-adaptation decision, as well as to maintain the health of SCPS. This survey first recalls the concepts of dependability, and proposes a generic environment-in-loop processing flow of self-management CPS, and then analyzes the error sources and challenges of self-management through the formal feedback flow. Focus on reducing the complexity, we first survey the self-adaptive architecture approaches and applied dependability means; then we introduce a hybrid multi-role self-adaptive architecture, and discuss the supporting technologies for dependable self-management at the architecture level. Focus on dependable environment-centered adaption, we investigate the verification and validation (V&V) methods for making safe self-adaptation decision and the solutions for processing decision dependably. For system-centered adaption, the comprehensive self-healing methods are summarized. Finally, we analyze the missing pieces of the technology puzzle and the future directions. In this survey, the technical trends for dependable CPS design and maintenance are discussed, an all-in-one solution is proposed to integrate these technologies and build a dependable organic SCPS. To the best of our knowledge, this is the first comprehensive survey on dependable SCPS building and evaluation.
ARTICLE | doi:10.20944/preprints202011.0508.v2
Subject: Computer Science And Mathematics, Algebra And Number Theory Keywords: Deep Learning; Convolutional Neural Network; IoT Networks; Cyber-attack detection; Cyber-attack Classification
Online: 17 December 2020 (12:14:00 CET)
With the rapid expansion of intelligent resource-constrained devices and high-speed communication technologies, Internet of Things (IoT) has earned a wide recognition as the primary standard for low-power lossy networks (LLNs). Nevertheless, IoT infrastructures are vulnerable to cyber-attacks due to the constraints in computation, storage, and communication capacity of the endpoint devices. From one side, the majority of newly developed cyber-attacks are formed by slightly mutating formerly established cyber-attacks to produce a new attack tending to be treated as a normal traffic through the IoT network. From the other side, the influence of coupling the deep learning techniques with cybersecurity field has become a recent inclination of many security applications due to their impressive performance. In this paper, we provide a comprehensive development of a new intelligent and autonomous deep learning-based detection and classification system for cyber-attacks in IoT communication networks leveraging the power of convolutional neural networks, abbreviated as (IoT-IDCS-CNN). The proposed IoT-IDCS-CNN makes use of the high-performance computing employing the robust CUDA based Nvidia GPUs and the parallel processing employing the high-speed I9-Cores based Intel CPUs. In particular, the proposed system is composed of three subsystems: Feature Engineering subsystem, Feature Learning subsystem and Traffic classification subsystem. All subsystems are developed, verified, integrated, and validated in this research. To evaluate the developed system, we employed the NSL-KDD dataset which includes all the key attacks in the IoT computing. The simulation results demonstrated more than 99.3% and 98.2% of cyber-attacks’ classification accuracy for the binary-class classifier (normal vs anomaly) and the multi-class classifier (five categories) respectively. The proposed system was validated using k-fold cross validation method and was evaluated using the confusion matrix parameters (i.e., TN, TP, FN, FP) along with other classification performance metrics including precision, recall, F1-score, and false alarm rate. The test and evaluation results of the IoT-IDCS-CNN system outperformed many recent machine-learning based IDCS systems in the same area of study.
REVIEW | doi:10.20944/preprints202110.0312.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Cyber Security; Internet of Things
Online: 21 October 2021 (14:01:19 CEST)
Nowadays, people live amidst the smart home domain, business opportunities in the industrial smart city and health care, though, along with concerns about security. Security is central for IoT systems to protect sensitive data and infrastructure, whilst security issues become increasingly expensive, in particular in Industrial Internet of Things (IIoT) domains. Nonetheless, there are some key challenges for dealing with those security issues in IoT domains: Applications operate in distributed environments such as Blockchain, varied smart objects are used, and sensors are limited in what comes to machine resources. In this way, traditional security does not fit in IoT systems. In this vein, the issue of cyber security has become paramount to the Internet of Things (IoT) and Industrial Internet of Things (IIoT) in mitigating cyber security risk for organizations and end users. New cyber security technologies / applications present improvements for IoT security management. Nevertheless, there is a gap on the effectiveness of IoT cyber risk solutions. This review article discusses the, trends around opportunities and threats in cyber security for IIoT.
ARTICLE | doi:10.20944/preprints201903.0109.v2
Subject: Engineering, Control And Systems Engineering Keywords: Cyber risk; Internet of Things cyber risk; Digital Economy Risk Assessment; Economic Impact Assessment.
Online: 9 April 2019 (12:26:13 CEST)
We present an updated design process for adapting and integrating existing cyber risk assessment approaches for impact assessment for the risk from IoT to the digital economy. The new design process includes a set of changes to the original standards (e.g. NIST) that are adapted for the IoT cyber risk in this paper. This paper also presents a new framework for impact assessment of IoT cyber risk, specific for the digital economy.
ARTICLE | doi:10.20944/preprints202110.0364.v1
Subject: Engineering, Energy And Fuel Technology Keywords: Artificial Intelligence; Machine Learning; Explainable Artificial Intelligence; Soft Sensors; Industry 4.0; Smart Manufacturing; Cyber-Physical System; Crude Oil Distillation; Debutanization; LPG Purification
Online: 25 October 2021 (15:43:08 CEST)
Refineries execute a series of interlinked processes, where the product of one unit serves as the input to another process. Potential failures within these processes affect the quality of the end products, operational efficiency, and revenue of the entire refinery. In this context, implementation of a real-time cognitive module, referring to predictive machine learning models, enables to provide equipment state monitoring services and to generate decision-making for equipment operations. In this paper, we propose two machine learning models: 1) to forecast the amount of pentane (C5) content in the final product mixture; 2) to identify if C5 content exceeds the specification thresholds for the final product quality. We validate our approach by using a use case from a real-world refinery. In addition, we develop a visualization to assess which features are considered most important during feature selection, and later by the machine learning models. Finally, we provide insights on the sensor values in the dataset, which help to identify the operational conditions for using such machine learning models.
ARTICLE | doi:10.20944/preprints201903.0080.v1
Subject: Engineering, Control And Systems Engineering Keywords: Internet of Things; Micro Mart model; Goal-Oriented Approach; transformation roadmap; Cyber risk regulations; empirical analysis; cyber risk self-assessment; cyber risk target state
Online: 6 March 2019 (11:47:04 CET)
The Internet-of-Things (IoT) enables enterprises to obtain profits from data but triggers data protection questions and new types of cyber risk. Cyber risk regulations for the IoT however do not exist. The IoT risk is not included in the cyber security assessment standards, hence, often not visible to cyber security experts. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. The outcome of such self-assessment needs to define a current and target state, prior to creating a transformation roadmap outlining tasks to achieve the stated target state. In this article, a comparative empirical analysis is performed of multiple cyber risk assessment approaches, to define a high-level potential target state for company integrating IoT devices and/or services. Defining a high-level potential target state represent is followed by a high-level transformation roadmap, describing how company can achieve their target state, based on their current state. The transformation roadmap is used to adapt IoT risk impact assessment with a Goal-Oriented Approach and the Internet of Things Micro Mart model.
REVIEW | doi:10.20944/preprints202102.0340.v1
Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity; Deep Learning; Artificial Neural Network; Artificial Intelligence; Cyber-Attacks; Cybersecurity Analytics; Cyber Threat Intelligence
Online: 16 February 2021 (15:31:02 CET)
Deep learning (DL), which is originated from an artificial neural network (ANN), is one of the major technologies of today's smart cybersecurity systems or policies to function in an intelligent manner. Popular deep learning techniques, such as Multi-layer Perceptron (MLP), Convolutional Neural Network (CNN or ConvNet), Recurrent Neural Network (RNN) or Long Short-Term Memory (LSTM), Self-organizing Map (SOM), Auto-Encoder (AE), Restricted Boltzmann Machine (RBM), Deep Belief Networks (DBN), Generative Adversarial Network (GAN), Deep Transfer Learning (DTL or Deep TL), Deep Reinforcement Learning (DRL or Deep RL), or their ensembles and hybrid approaches can be used to intelligently tackle the diverse cybersecurity issues. In this paper, we aim to present a comprehensive overview from the perspective of these neural networks and deep learning techniques according to today's diverse needs. We also discuss the applicability of these techniques in various cybersecurity tasks such as intrusion detection, identification of malware or botnets, phishing, predicting cyber-attacks, e.g. denial of service (DoS), fraud detection or cyber-anomalies, etc. Finally, we highlight several research issues and future directions within the scope of our study in the field. Overall, the ultimate goal of this paper is to serve as a reference point and guidelines for the academia and professionals in the cyber industries, especially from the deep learning point of view.
ARTICLE | doi:10.20944/preprints201707.0044.v1
Subject: Engineering, Control And Systems Engineering Keywords: cyber physical systems; industry 4.0; MDE; hardware and software co-design; lifetime verification & validation; dependability; correctness; flexibility; self-management; self-adapting; self-healing
Online: 17 July 2017 (10:27:33 CEST)
Though Cyber Physical Systems (CPS) become very popular in last the decade, dependability of CPS is still a critical issue and related survey is rare. We try to spell out the jigsaw of technologies and figure out the technical trends of dependable self-managing CPS. This survey first recalls the motivation and the similar concepts. By analyzing four generic architectures, we summarize the common characteristics and related assurance technologies, and propose a more generic environment-in-loop processing flow of CPS and a formal interaction flow between physical space and cyber space. Further, the similarity between correctness and dependability is formally analyzed and the new five research questions of dependable self-managing CPS are presented. Then we review the critical technologies and related correctness verification & validation (V&V) methods, the architectures for dependable self-managing CPS. Further, the detail dependability management and V&V technologies are surveyed, which covers the areas of running-time fault management methods and whole life cycle V&V technologies, maintenance and available tool sets. For holistic CPS development, Modeling techniques and MDE (model driven engineering) based V&V methods are analyzed in detail. Then we complete the jigsaw of technologies and figure out the missing part. Further, we propose the technical challenges and the further direction. To our best knowledge, this is the first comprehensive survey on dependable self-managing CPS development and evaluation.
REVIEW | doi:10.20944/preprints202003.0139.v1
Subject: Computer Science And Mathematics, Software Keywords: education; cyber threats; gamification; phishing; survey; taxonomies
Online: 8 March 2020 (16:14:56 CET)
Phishing is a set of devastating techniques which lure target users to provide critical resources. They are successful because they rely on human weaknesses. Gamification which is a recent and non-traditional learning method with purpose to motivate and engage user to carry out activities, is more and more applied to prevent such cyber threats. This paper provides the first survey of gamified solutions dedicated to educate against phishing from 2007 to 2019. The investigation is conducted on eight proposals in terms of core concepts, game mechanics and learning process. We provide three taxonomies of dimensions to systematically characterize researches on gamified solutions, discuss lacks of surveyed works and opens further orientations to enhance this research area. Some key results are: solutions do not consider elementary level of knowledge and do no offer basic notions; solutions are not adapted to general audience and therefore not reliably applicable in different contexts; platforms partially educate about phishing; learners are evaluated predictably and within a short period. This study constitutes a cornerstone to understand and enhance research on phishing education.
Subject: Engineering, Automotive Engineering Keywords: functional dependency; network-based linear dependency modelling; internet of things; micro mort model; goal-oriented approach; transformation roadmap; cyber risk regulations; empirical analysis; cyber risk self-assessment; cyber risk target state.
Online: 25 December 2020 (11:35:48 CET)
The Internet-of-Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state-of-the-art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.
ARTICLE | doi:10.20944/preprints202209.0377.v1
Subject: Biology And Life Sciences, Anatomy And Physiology Keywords: aging; immunosenescence; physical fitness; physical activity; obesity; sex
Online: 26 September 2022 (05:00:15 CEST)
Cardiorespiratory fitness (CRF) is essential for sustained work ability in good health, but declines with aging as does the functionality of the immune system, the latter process commonly referred to as immunosenescence. This study aimed to compare the capacity of immunosenescence biomarkers with chronological age for predicting low CRF in a cross-sectional sample recruited from the regional working population. CRF was determined by submaximal bicycle ergometer testing in a cross-sectional sample of 597 volunteers aged 20–70 years from the ’Dortmund Vital Study’ (DVS, ClinicalTrials.gov Identifier: NCT05155397). Low CRF was scored, if the ergometer test was not completed due to medical reasons or if the power output projected to a heart rate of 130 bpm divided by body mass was below sex-specific reference values of 1.25 W/kg for females and 1.5 W/kg for males, respectively. In addition to established biomarkers of immunosenescence, we calibrated a comprehensive metric of immune age to our data and compared its predictive capacity for low CRF to chronological age while adjusting our analysis for the influence of sex, obesity, and level of regular physical activity by applying univariate and multiple logistic regression. While obesity, low physical activity, chronological and immune age were all associated with increased probability for low CRF in univariate analyses, multiple logistic regression revealed that obesity and physical activity together with immune age, but not chronological age, were statistically significant predictors of low CRF outcome. Sex was non-significant due to the applied sex-specific reference values. These results demonstrate that biological age assessed by our immunological metric can outperform chronological age as a predictor for CRF and indicate a potential role for immunosenescence in explaining the inter-individual variability of the age-related decline in cardiorespiratory fitness.
REVIEW | doi:10.20944/preprints202102.0403.v1
Subject: Business, Economics And Management, Accounting And Taxation Keywords: physical education; physical activity; pedagogical models; sustainability development
Online: 18 February 2021 (09:44:11 CET)
The Sustainable Development Goals (SDGs) is a global strategy that aims to obtain a more equitable and just world. These objectives are organized in 17 SDGs, which are detailed in 169 targets. Different international institutions have emphasized education's relevance to developing citizens who contribute to the SDGs' achievement for 2030. However, a review focused on Physical Education exclusively has not been performed yet. Therefore, the objective of this work is double. First, to analyze and select the specific goals of the SDGs that can be implemented in the subject of Physical Education. And second, to relate these specific goals to the different models based on Physical Education practices. This review showed how three institutional documents have previously related sport, physical exercise and physical education to the specific goals of the SDGs. Based on the search done, this document selects those goals that could be integrated into the educational context through Physical Education. The bibliographic and narrative analysis carried out in this research shows that of the 169 specific goals proposed in the SDGs, only 24 could be worked on in Physical Education. In addition, after this previous analysis, a proposal for the relationship between the practice-based models and these 24 goals is presented. The contributions made in this paper will allow teachers to establish links between PE sessions and SDGs while raising awareness to develop students who contribute to a more sustainable world.
REVIEW | doi:10.20944/preprints202109.0461.v1
Subject: Engineering, Control And Systems Engineering Keywords: cyber-attacks; honeypots; internet of things; IoT; scada
Online: 28 September 2021 (10:21:26 CEST)
In recent years, due to their frequent use and widespread use, IoT (Internet of Things) devices have become an attractive target for hackers. As a result of their limited network resources and complex operating systems, they are vulnerable to attacks. Using a honeypot can, therefore, be a very effective way of detecting malicious requests and capturing samples of exploits. The purpose of this article is to introduce honeypots, the rise of IoT devices, and how they can be exploited by attackers. Various honeypot ecosystems will be investigated further for capturing and analyzing information from attacks against these IoT devices. As well as how to leverage proactive strategies in terms of IoT security, it will provide insights on the attack vectors present in most IoT systems, along with understanding attack patterns.
BRIEF REPORT | doi:10.20944/preprints202106.0621.v1
Subject: Computer Science And Mathematics, Computer Networks And Communications Keywords: cyber-criminal; organization; Advanced Persistent Threat; undercover activities
Online: 25 June 2021 (12:13:47 CEST)
as the growth and popularity of technology has become simultaneous ascend in both impacts and numbers of cyber criminals thanks to the web. For many years, the organization has strived in ways of preventing any attacks from cyber-criminal with advanced techniques. Cybercriminals and intruders are developing a more advanced way to breach the security surface of an organization. Advanced Persistent Threats are also known as APT are new and a lot more sophisticated version for multistep attack scenarios that are known and are targeted just to achieve a goal most commonly undercover activities. this report, there will cover everything I know that tells us about APT with more word and brief explanations
ARTICLE | doi:10.20944/preprints201806.0425.v2
Subject: Computer Science And Mathematics, Information Systems Keywords: Adversarial Deduplication; Machine Learning Classifiers; Cyber Threat Intelligence
Online: 23 July 2018 (12:21:00 CEST)
In traditional databases, the entity resolution problem (which is also known as deduplication), refers to the task of mapping multiple manifestations of virtual objects to its corresponding real-world entity. When addressing this problem, in both theory and practice, it is widely assumed that such sets of virtual object appear as the result of clerical errors, transliterations, missing or updated attributes, abbreviations, and so forth. In this paper, we address this problem under the assumption that this situation is caused by malicious actors operating in domains in which they do not wish to be identified, such as hacker forums and markets in which the participants are motivated to remain semi-anonymous (though they wish to keep their true identities secret, they find it useful for customers to identify their products and services). We are therefore in the presence of a different, even more challenging problem that we refer to as adversarial deduplication. In this paper, we study this problem via examples that arise from real-world data on malicious hacker forums and markets arising from collaborations with a cyber threat intelligence company focusing on understanding this kind of behavior. We argue that it is very difficult---if not impossible---to find ground truth data on which to build solutions to this problem, and develop a set of preliminary experiments based on training machine learning classifiers that leverage text analysis to detect potential cases of duplicate entities. Our results are encouraging as a first step towards building tools that human analysts can use to enhance their capabilities towards fighting cyber threats.
ARTICLE | doi:10.20944/preprints201804.0144.v1
Subject: Computer Science And Mathematics, Information Systems Keywords: big data; SIEM; correlation analysis; cyber crime profiling
Online: 11 April 2018 (08:39:02 CEST)
The number of SIEM introduction is increasing in order to detect threat patterns in a short period of time with a large amount of structured/unstructured data, to precisely diagnose crisis to threats, and to provide an accurate alarm to an administrator by correlating collected information. However, it is difficult to quickly recognize and handle with various attack situations using a solution equipped with complicated functions during security monitoring. In order to overcome this situation, new detection analysis process has been required, and there is an effort to increase response speed during security monitoring and to expand accurate linkage analysis technology. In this paper, reflecting these requirements, we design and propose profiling auto-generation model that can improve the efficiency and speed of attack detection for potential threats requirements. we design and propose profiling auto-generation model that can improve the efficiency and speed of attack detection for potential threats.
ARTICLE | doi:10.20944/preprints202210.0407.v1
Subject: Public Health And Healthcare, Public Health And Health Services Keywords: public health; physical activity; rural resident; physical exercise; epidemiology
Online: 26 October 2022 (09:51:36 CEST)
Physical inactivity is a well-known risk factor for various non-communicable diseases (NCDs). Sufficient physical activity (PA) is essential for the prevention of NCDs and thus it is imperative to study the current status of PA and its influencing factors among rural residents in China. A population-based survey was conducted in rural areas of Shandong, Shanxi and Yunnan Provinces using a stratified random sampling method. The International Physical Activity Questionnaire Short Form (IPAQ-S) was used to collect the data on PA. A total of 3780 rural residents participated in the survey. The result showed that 22.2% of rural residents were physical inactivity. The proportion of rural residents reporting practice of physical exercise was 54.4%. The most frequently performed physical exercise was walking/brisk walking(78.3%).Binary logistic regression analyses showed that being female, people at age between 15 to 34 years or 60 years old and above, employees of governmental departments/retirees, school students, the unemployed, people with NCDs were risk factors of PA and ethnic minority groups,smoking and alcohol consumption were risk factors of physical exercise. Health promotion programme aiming at increasing people’s PA in rural China is needed and it should focus on the populations groups of the female, people at age 60 years and above ,school students, the unemployed, and people with NCDs.
ARTICLE | doi:10.20944/preprints202103.0766.v1
Subject: Social Sciences, Psychology Keywords: healthy life style; physical activity; physical and mental health
Online: 31 March 2021 (12:28:13 CEST)
The purpose of this article was to check the effects on health of various types of physical activities, diet, BMI, smoking and alcohol consumption and their interrelationships with control for age, sex and level of education. The study was based on epidemiological data (9617 participants from 19 to 81 years old for whom we have health indicators over a period of 11 years) together with questionnaires about diet, alcohol, tobacco and the frequency of different types of physical activities. Descriptive statistics and non-parametric correlational analysis of epidemiological data was performed with use of SPSS v.19. Our results indicate the existence of the significant relationship between leading a healthy life style (type of physical activities, limitations of fats consume and weight maintenance). However, the different categories of physical activities were analysed separately and showed slight differences on health indicators impacts. Our findings confirm that leading a healthy life style (all types of physical activities, limitations of fats consume and weight maintenance) is an important issue since it has a significant relationship with physical and mental health indicators, but outdoor physical activities and practicing sport in group have shown slightly higher impact on health.
ARTICLE | doi:10.20944/preprints202102.0148.v1
Subject: Computer Science And Mathematics, Algebra And Number Theory Keywords: IIoT; IoT; Industry 4.0; Protocols; Cyber Threats; Attacks; Security
Online: 5 February 2021 (08:34:21 CET)
In today’s Industrial IoT (IIoT) environment, where different systems interact with the physical world, the state proposed by the Industry 4.0 standards can lead to escalating vulnerabilities, especially when these systems receive data streams from multiple intermediaries, requiring multilevel security approaches, in addition to link encryption. At the same time taking into account the heterogeneity of the systems included in the IIoT ecosystem and the non-institutionalized interoperability in terms of hardware and software, serious issues arise as to how to secure these systems. In this framework, given that the protection of industrial equipment is a requirement inextricably linked to technological developments and the use of the IoT, it is important to identify the major vulnerabilities, the associated risks and threats and to suggest the most appropriate countermeasures. In this context, this study provides a description of the attacks against IIoT systems, as well as a thorough analysis of the solutions against these attacks, as they have been proposed in the most recent literature.
Subject: Computer Science And Mathematics, Security Systems Keywords: assessment framework; cyber security; GDPR; PCI-DSS; DSPT; NISD
Online: 9 May 2020 (04:35:03 CEST)
As organizations are vulnerable to cyber attacks, their protection becomes a significant issue. Capability Maturity Models can enable organizations to benchmark current maturity levels against best practices. Although many maturity models have been already proposed in the literature, a need for models that integrate several regulations exists. This article presents a light web-based model that can be used as a cybersecurity assessment tool for Higher Education Institutes (HEIs) of the UK. The novel Holistic Cybersecurity Maturity Assessment Framework incorporates all security and privacy regulations and best practices that HEIs must be compliant to and can be used as a self-assessment or a cybersecurity audit tool.
REVIEW | doi:10.20944/preprints201610.0092.v2
Subject: Engineering, Electrical And Electronic Engineering Keywords: communication standards; cyber security; intrusion detection system; smart grid; topology control; Wireless sensor networks
Online: 27 October 2016 (11:26:10 CEST)
An existing power grid is going through a massive transformation. Smart grid technology is a radical approach for improvisation in prevailing power grid. Integration of electrical and communication infrastructure is inevitable for the deployment of Smart grid network. Smart grid technology is characterized by full duplex communication, automatic metering infrastructure, renewable energy integration, distribution automation and complete monitoring and control of entire power grid. Wireless sensor networks (WSNs) are small micro electrical mechanical systems which are accomplished to collect and communicate the data from surroundings. WSNs can be used for monitoring and control of smart grid assets. Security of wireless sensor based communication network is a major concern for researchers and developers. The limited processing capabilities of wireless sensor networks make them more vulnerable to cyber-attacks. The countermeasures against cyber-attacks must be less complex with an ability to offer confidentiality, data readiness and integrity. The address oriented design and development approach for usual communication network requires a paradigm shift to design data oriented WSN architecture. WSN security is an inevitable part of smart grid cyber security. This paper is expected to serve as a comprehensive assessment and analysis of communication standards, cyber security issues and solutions for WSN based smart grid infrastructure.
ARTICLE | doi:10.20944/preprints202211.0403.v1
Subject: Biology And Life Sciences, Endocrinology And Metabolism Keywords: cardiovascular diseases; physical activity; physical exercise; sedentarism; quality of life
Online: 22 November 2022 (03:39:54 CET)
Obesity is related to the establishment of chronic inflammation and metabolic diseases, but it can be positively influenced by the regular practice of physical activity. The study aimed to compare the anthropometric, metabolic, and inflammatory parameters of physically active Military Police Officers (MPOs) with those who are less physically active. Sixty male MPOs, low activity (n=28) and physically active (n=32) participated. The following parameters were measured: plasma cytokine levels, C-reactive protein (CRP) levels, circulating glucose triglyceride (TAG) and high-density lipoprotein cholesterol (HDL-C) levels, and plasma glutamic oxalacetate transaminase (GOT), glutamic-pyruvate transaminase (GPT), and gamma-glutamyl transferase (GGT) activities. The physically active group presented lower body fat and reduced TAG and IL-8 levels compared to the low activity group. Moreover, a negative correlation between SPE and SBP, DBP, BPM was detected for the physically active group (p<0.05) but not in the low activity group. Furthermore, the physically active group's work time (WT) values were not correlated with the important metabolic markers SBP, DBP, BPM, GLU, TAG (p>0.05) but could be in the low activity group (p<0.05). These findings highlight the fundamental protective role of physical activity in controlling body composition, subclinical inflammation, and cardiovascular risk in MPOs.
ARTICLE | doi:10.20944/preprints201811.0103.v1
Subject: Medicine And Pharmacology, Orthopedics And Sports Medicine Keywords: acute physical stress; sports performance; heart rate variability; physical exhaustion
Online: 5 November 2018 (10:35:01 CET)
Athletes are exposed to high-intensity loads to promote athletic performance, however without appropriate evaluation for its effects. This study investigates the effects of four types of exhaustion exercises on Heart Rate Variability (HRV) and Poincaré features as markers of central fatigue; Creatine Kinase (CK) and blood lactate concentrations ([LA-]b) as biomarkers of peripheral fatigue. To achieve this purpose, ten healthy volunteers were exposed to exhaustive exercise using isotonic-, isometric-, aerobic-, and anaerobic-fatigue protocols. HRV Poincaré features, standard deviation of instantaneous beat-to-beat R-R interval variability (SD1) and standard deviation of continuous long-term R-R interval variability (SD2) variables were collected. Central fatigue was tested through the sympathetic stress index (SS) and the sympathetic and parasympathetic index (SS/SD1). Blood samples were collected at the beginning and at the end of the exercises to determine CK and [LA-]b. The SD1 decreased in each exercise protocol, while the SS and SS/SD1 increased. [LA-]b and CK increased at the end of each protocol and correlated with SD1 and SS/SD1. HRV, CK, and [LA-]b are acute markers to detect, both central and peripheral fatigue; sensitive to the type, duration, and intensity of exercise, being HRV a novel noninvasive marker, simple and useful for sports coaches and athletes.
ARTICLE | doi:10.20944/preprints202104.0195.v1
Subject: Medicine And Pharmacology, Immunology And Allergy Keywords: doubly labeled water; total energy expenditure; physical activity level; lactate threshold, physical fitness; International Physical Activity Questionnaire
Online: 7 April 2021 (11:32:02 CEST)
Adequate energy intake is critical for the healthy longevity of older adults, and the estimated energy requirement is determined by total energy expenditure (TEE). We aimed to identify the relationship between measured aerobic capacity and TEE, activity energy expenditure (AEE) or physical activity level (PAL) with the doubly labeled water (DLW) methods in the advanced older adults. A total of 12 physically independent older adults (10 males and 2 females) aged between 81 to 94 years participated in this study. Aerobic capacity was evaluated according to the lactate threshold (LT). TEE under free-living conditions was assessed using the DLW method, and self-reported physical activity was obtained through the Japanese version of the International Physical Activity Questionnaire (IPAQ). LT was significantly positively correlated with TEE, AEE, and PAL after adjustment for age and sex (ρ= 0.77 (P<0.01), 0.86 (p<0.01), and 0.86 (p<0.01), respectively). We found the LT as an aerobic capacity is positively and independently correlated with TEE, AEE or PAL. The present results suggest that maintaining aerobic capacity is an important factor for preventing frailty, although further research is needed to multisite studies and many samples.
ARTICLE | doi:10.20944/preprints202305.0118.v1
Subject: Computer Science And Mathematics, Computer Science Keywords: CPS; IoT; software quality; physical dimension; physical orientation; formal verification; metaprogramming
Online: 3 May 2023 (08:47:27 CEST)
With the rise of Internet of Things (IoT) devices and Cyber-Physical Systems, the demand for more functional and high-quality software has increased tremendously. To meet this need, we must reengineer and reuse existing software, as well as develop new software formal verification methods. One such method is based on physical quantities defined by the System International, which have physical dimensions. The homogeneity of physical dimensions in software code enables us to check the software code in the space of base units, making it the first basis of the new software verification method. However, this method cannot check expressions with angles, angle speed, and other similar features. To address this, a transformation for physical value orientation introduced by Siano allows us to check software code for orientational, stabilization, and other related branches. This makes the orientational homogeneity the second basis of the new software verification method. To assess the effectiveness of the proposed method, we developed special software defect models based on the statistical characteristics of software code. We used a special statistical analysis tool to define the statistical characteristics of modern software and analyzed over 2 GB of C++ GITHUB code for drones. Based on the actual distribution of software characteristics, the proposed method can detect over 60% of latent software defects. Implementing this method can significantly reduce testing time, improve reliability, and enhance overall software quality.
ARTICLE | doi:10.20944/preprints201806.0018.v1
Subject: Social Sciences, Education Keywords: physical education; coeducation; equality
Online: 1 June 2018 (12:17:18 CEST)
Background: In PE, the methodology used to develop coeducation must consider the tastes and preferences of students. The purpose of this work was to analyze how teachers work with different aspects of PE classes and how their work is perceived by students. Methods: The sample was formed by 176 teachers and 1,136 secondary school students. The research design was descriptive. The Questionnaire of Coeducational Aspects in Physical Education for teachers and the Questionnaire of Perception of Equality and Discrimination in Physical Education for Students. Results: The different statistical analyses showed significant differences in how male and female teachers assigned responsibility to the students and their control of motor activity space. In regards to the students, significant differences were found between boys and girls in their opinions of how their teachers apply the same rules to all the students. Conclusions: No differences exist between male and female teachers in regards to their utilization neither of materials and sexist language or in their evaluation and feedback given to the students. In regards to the students, girls perceive to a greater extent than their male counterparts that the activities in PE classes promote equality in the improvement of their capacities.
ARTICLE | doi:10.20944/preprints202101.0355.v1
Subject: Business, Economics And Management, Accounting And Taxation Keywords: physical activity; self-determination theory; after-school period; physical fitness; sedentary time
Online: 18 January 2021 (15:11:08 CET)
Abstract: Increasing physical activity (PA) and personal and social values are two of the greatest demands in the current educational system. This study examined the effect of a hybrid pro-gramme based on the Personal and Social Responsibility Model and Gamification. A total of 58 students (13.89 years old, SD = 1.14) in two groups (Experimental and Control) participated dur-ing a complete academic year. Motivation, physical activity and sedentary behaviour were as-sessed though questionnaires. Physical fitness was evaluated using previously validated field tests. The results showed significant differences over time between EG and CG in afterschool physical activity (APA) at the weekend (p = 0.003), sedentary time (p = 0.04) and speed-agility (p = 0.04). There were no significant differences in motivation. Regarding the intervention, speed-agility (p = 0.000), strength (p = 0.000), agility (p = 0.000), cardiorespiratory fitness (p = 0.001), APA-weekend (p = 0.000), APA-week (p= 0.000) and sedentary time (p = 0.000) increased signifi-cantly in the EG. Speed-agility (p = 0.000), APA-weekend (p = 0.03) and sedentary time (p = 0.008) increased in the CG. The use of this hybrid program can be useful to produced improvements in physical fitness, physical activity and sedentary hevaviours. The use of a hybrid program based on teaching personal and social responsibility and gamification strategies, produced improvements in physical fitness, physical activity and sedentary behavior, but not in motivation variables. Further research is demanded in order to contrast this relevant findings due to the potential drawbacks and diversity found in the scientific literature among model-based practice.
ARTICLE | doi:10.20944/preprints202011.0507.v1
Subject: Business, Economics And Management, Accounting And Taxation Keywords: COVID-19; lockdown; online teaching; physical education; physical activity; teachers; secondary school
Online: 19 November 2020 (11:26:28 CET)
COVID-19 pandemic has drastically reduced physical activity (PA) behaviors of many people. Physical education (PE) is considered one of the privileged instruments to promote youths’ PA. We aimed to investigate the effects of lockdown on PE teachers’ behaviors promoting their students’ out-of-school PA and differences between three European countries. 1146 PE teachers (59.5% females) from France, Italy, and Turkey answered an online questionnaire about guiding students to engage in out-of-school PA, helping them to set PA goals, encouraging in self-monitoring PA, the pedagogical formats of these behaviors and feedback asked to students. RM-MANCOVAs were performed with a 2 Time (before and during the lockdown) × 3Country (France, Italy, Turkey) × 2 Gender factorial design, using teaching years and perceived health as covariates. A significant multivariate main effect Time×Country×Gender (p<.001) was reported for the behaviors promoting students’ PA, with French and Italian teachers increasing some behaviors, while Turkish teachers showing opposite trends. Significant multivariate main effects Time×Country were found for formats supporting the behaviors (p < .001) and for asked feedback formats (p<.001). The massive contextual change imposed by lockdown caused different reactions in teachers from the three countries. Findings are informative for PA promotion and PE teachers’ education.
ARTICLE | doi:10.20944/preprints201908.0146.v1
Subject: Medicine And Pharmacology, Orthopedics And Sports Medicine Keywords: health-oriented physical; immersive virtual reality; virtual reality; intensity of physical activity
Online: 12 August 2019 (14:02:12 CEST)
The aim of the study is to assess enjoyment and intensity of physical exercise while practicing physical activity (PA) in immersive virtual reality (IVR) using innovative training devices (omni-directional Omni treadmill and Icaros Pro flight simulator). The study also contains the results of subjective research on the usefulness of such a form of PA in the opinion of users. In total, 61 adults (10 women and 50 men) took part in the study. To assess the enjoyment level (EL) Interest/Enjoyment subscale of Intrinsic Motivation Inventory (IMI) was used. Exercise intensity was assessed during 10-minute sessions of active video games (AVGs) in IVR based on heart rate (HR). The average enjoyment level during physical exercise in IVR on the tested training devices was relatively high (Omni 5.74 points, Icaros 5.60 points). In the opinion of the majority of participants, AVGs on IVR training devices constitute a sufficiently useful form of movement to meet the needs of PA practiced in free time, and they can even replace some of the classic forms of movement. Intensity of PA during games on training devices was at the level recommended for health benefits for 92% (Omni) and 84% (Icaros Pro) of its duration. Based on the conducted research, it can be assumed that AVGs in IVR using a multi-directional treadmill and a flight simulator can be an effective tool for increasing participation in health-oriented PA.
ARTICLE | doi:10.20944/preprints202201.0454.v1
Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Ransomware; Behavior analysis; Cyber Security; Machine Learning; Ensemble model; Supervised classification
Online: 31 January 2022 (11:49:48 CET)
Ransomware is one of the most dangerous types of malware, which is frequently intended to spread through a network to damage the designated client by encrypting the client’s vulnerable data. Conventional signature-based ransomware detection technique falls behind because it can only detect known anomalies. When it comes to new and non-familiar ransomware traditional system unveils huge shortcomings. For detecting unknown patterns and sorts of new ransomware families,behavior-based anomaly detection approaches are likely to be the most efficient approach. In the wake of this alarming condition, this paper presents an ensemble classification model consisting of three widely used machine learning techniques that include Decision Tree (DT), RandomForest (RF), and K-nearest neighbor (KNN). To achieve the best outcome ensemble soft voting and hard voting techniques are used while classifying ransomware families based on attack attributes. Performance analysis is done by comparing our proposed ensemble models with standalone models on behavioral attributes based ransomware dataset..
ARTICLE | doi:10.20944/preprints202107.0120.v1
Subject: Engineering, Control And Systems Engineering Keywords: Information security; Cybercrime; cyber awareness; cybersecurity basics; cybersecurity hygiene; Blockchain technology
Online: 5 July 2021 (16:34:35 CEST)
The ignorance of or lack of knowledge about cybersecurity aspects causes a critical problem regarding confidentiality and privacy. This security problem will continue to exist even if the user possesses less expertise in information security. The modern IT technologies are well developed, and almost everyone uses the features of IT technologies and services within the Internet. However, people are being affected due to cybersecurity threats. People can adhere to the recommended cybersecurity guidelines, rules, adopted standards, and cybercrime preventive measures. However, it is not possible to entirely avoid cybercrimes. Cybercrimes often lead to sufficient business losses and spread forbidden themes (hatred, terrorism, child porn, etc.). Therefore, to reduce the risk of cybercrimes, a web-based Blockchain-enabled cybersecurity awareness program (WBCA) process is introduced in this paper. The proposed web-based cybersecurity awareness program trains users to improve their security skills. The proposed program helps with understanding the common behaviors of cybercriminals and improves user knowledge of cybersecurity hygiene, best cybersecurity practices, modern cybersecurity vulnerabilities, and trends. Furthermore, the proposed WBCA uses the Blockchain technology to protect the model from the potential threats. The proposed model is validated and tested using real-world cybersecurity topics with real users and cybersecurity experts. We anticipate that the proposed program can be extended to other domains, such as national or corporate courses, to increase the cybersecurity awareness level of users.
ARTICLE | doi:10.20944/preprints202301.0140.v1
Subject: Biology And Life Sciences, Behavioral Sciences Keywords: quality of life; physical activity; physical function; food and nutrition; older Japanese adults
Online: 9 January 2023 (06:32:36 CET)
Japan is experiencing a super-aging society faster than is anywhere else worldwide. Consequently, extending healthy life expectancy is an urgent social issue. To understand diet that supports the extension of healthy life expectancy, we studied the relationships among quality of life (QOL: SF-36 questionnaire), physical activity (number of steps and activity calculated using an accelerometer), physical function (muscle strength, movement function, agility, static balance, dynamic balance, and walking function) and dietary intake among 469 older adults living in the Tokyo metropolitan area (65–75 years old, men/women = 166/303) from February 23, 2017, to March 31, 2018. There was a significant positive association between physical QOL and steps, moderate-intensity activity, and high-intensity activity (p < 0.05), and a significant positive association (p < 0.05) between physical activity and movement, static balance, and walking functions, but no association with muscle strength. These three body functions were significantly positively correlated with intake of vegetables, seeds, fruits, and milk, and with magnesium, potassium, vitamin B6, and the dietary fibre/carbohydrate ratio and composition ratios (p < 0.05). Balancing food and nutrition may improve QOL in older adults through increased physical function and physical activity. Future verification of interventions is needed.
ARTICLE | doi:10.20944/preprints202202.0239.v1
Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: WRF; physical parameterization; sensitivity; Ethiopia
Online: 18 February 2022 (17:41:50 CET)
A 3-month (June-August) regime of the year 2002 summer rainfall (JJA2002) was simulated with 30 physics combinations using the Weather Research and Forecasting (WRF) model at 12-km horizontal grid resolution. The objective is to examine summer rainfall sensitivity to parameterization of microphysical, convective, and boundary layer processes and identify the best possible combination of parameterization options that perform relatively better in simulating the spatial and temporal distribution of summer rains over Ethiopia. The WRF simulated rainfall was evaluated against station data and satellite rainfall products (CHIRPS and ENACTS) using mean absolute error, Pearson and Pattern correlation coefficients (PCC), pattern correlation, and error in a number of rainy days as evaluation metrics. Summer rainfall is found to be most sensitive to the choice of cumulus parameterization and least sensitive to cloud microphysics. All simulations captured the spatial distribution of mean seasonal precipitation with PCC ranging from 0.89-0.94. However, all simulations overestimated precipitation amount and number of rainy days. Out of the 30, the simulations that use a combination of Grell-3D cumulus scheme, ACM2 boundary layer, Lin Microphysics, Dudhai shortwave radiation, and RRTM longwave radiation scheme ranked the top and provided the most realistic simulation in terms of amount and spatio-temporal distribution of summer rainfall.
COMMUNICATION | doi:10.20944/preprints202102.0306.v1
Subject: Public Health And Healthcare, Public, Environmental And Occupational Health Keywords: Quarantine; COVID-19; Physical activity
Online: 12 February 2021 (14:39:16 CET)
The COVID-19 pandemic which have affected every part of the world have been deemed a public health concern and classified as a pandemic. The government imposing travel bans and quarantine measures have been found to be effective in preventing and reducing the spread of COVID-19. A reduction in physical activity and increase in the consumption of unhealthy foods have been observed to be some of the major implications of quarantine. Adequate physical activity and increased access to healthy foods would help in improving the psychological wellbeing of individuals thereby preventing the development of cardiovascular diseases.
ARTICLE | doi:10.20944/preprints202301.0482.v1
Subject: Engineering, Electrical And Electronic Engineering Keywords: FMECA; Fuzzy Inference Systems; fuzzy-based FMECA, Risk assessment, cyber-power grids
Online: 26 January 2023 (16:10:15 CET)
In this paper, we introduce the application of Type-I fuzzy inference systems (FIS) as an alternative to improve the prioritization in the FMECA analysis applied in cyber-power grids. Classical FMECA assesses the risk level through the Risk Priority Number (RPN). The multiplication between three integer numbers computes this, called risk factors, representing the severity, occurrence, and detectability of each failure mode and are defined by a team of experts. The RPN does not consider any relative importance between the risk factors and may not necessarily represent the real risk perception of the FMECA team members, usually expressed by natural language; this is the main FMECA shortcoming criticized in the literature. Our approach considers fuzzy variables defined by FMECA experts to represent the uncertainty associated with the human language and a rule base consisting of 125 fuzzy rules to represent the risk perception of the experts. To test our approach, we select a cyber-power grid previously analyzed by the authors using the classical FMECA. The results reveal our proposed fuzzy approach as promissory to represent the uncertainty associated with expert knowledge and to perform an accurate prioritization of failure modes in the context of electrical power systems.
Subject: Computer Science And Mathematics, Information Systems Keywords: Intrusion Detection Systems; IDS; Cyber Security; Information Technology; Security Systems; Systems Security
Online: 15 June 2022 (09:28:49 CEST)
Intrusion Detection Systems (IDS) plays a part in modern cyber security, as a result of the increasing need for cyber security systems in the “real” world due to the increasing number of cyber attacks, more sophisticated systems are required in order to prevent these attacks - an IDS can provide this protection. Due to the sophistication of these systems, they must be properly understood, developed and analyzed - research papers can be used as a tool to improve IDS systems. This paper is composed of two main sections: a survey and a taxonomy, providing information, reviews and interpretations from relevant papers, a timeline of important papers, a discussion on the future of IDS and a classification on IDS and how to apply this.
ARTICLE | doi:10.20944/preprints202006.0065.v1
Subject: Computer Science And Mathematics, Information Systems Keywords: Cyber Attacks; Network Security; Network Performance; Network Traffic; Anomaly Detection; Signature Detection
Online: 7 June 2020 (07:58:18 CEST)
This paper incorporates the definition of Intrusion Detection Systems and the methodologies utilised by these systems. As well as this, this research paper also encompasses a taxonomy and a survey of IDS and the specific strategies and principles. Finally, this paper also includes a discussion amongst other authors for instance what the authors differ and agree on, along with the previously related studies.
ARTICLE | doi:10.20944/preprints202211.0240.v1
Subject: Social Sciences, Education Keywords: body expression; self-concept; pre-service training; physical activity; physical education; COVID-19 pandemic; emotions
Online: 14 November 2022 (06:23:17 CET)
Body Expression (BE) has been defined in the past decades as a discipline within Physical Education (PE) with very particular characteristics and a strong emotional component. In this study, a programme of this discipline was applied to university Physical Activity and Sports Sciences (PASS) students from six consecutive academic years: three prior to and three during the pandemic. A pre-post design was used to determine how the BE programme affected the university students' self-concept (SC). To do so, a questionnaire with a multidimensional approach to this construct was administered, whose dimensions were closely related to the BE programme's characteristics. The results revealed significant improvements in the final SC, compared to the initial SC. Men reported lower SC values than women before the programme implementation, but higher at the end. Therefore, the change was larger in men, so the programme may have had an equalising effect between groups. It was also verified that the pandemic had particularly affected women.
ARTICLE | doi:10.20944/preprints202209.0068.v1
Subject: Computer Science And Mathematics, Analysis Keywords: wearable device; physical activity; behavior; COVID-19; pandemic; exercise habits; analysis; objectively-measured physical activity
Online: 5 September 2022 (13:49:56 CEST)
The COVID-19 pandemic resulted in government restrictions that altered the lifestyle of people worldwide. Studying the impact of these restrictions on exercise behaviors will improve our understanding of environmental factors that influence individuals’ PA. We conducted a retrospective analysis using an index of government pandemic stringency developed by Oxford and a wearable device for runners to compare strictness of lockdowns and exercise habits, using digitally-logged PA data from more than 7,000 runners on a global scale. Additionally, time-of-day of PA globally and levels of PA in 14 countries are compared between the pre-pandemic year of 2019 and the first pandemic year of 2020. We found that during the pandemic the time-of-day that people exercised experienced a major shift, with significantly more activities logged during standard working hours on workdays (p<0.001) and fewer during the same time frame on weekends (p<0.001). Of the countries examined, Italy and Spain had among the most strict lockdowns and suffered the largest decreases in activity counts, whereas France experienced a minimal decrease in activity counts despite enacting a similarly strict lockdown. This study suggests that there are several factors affecting PA, including government policy, workplace policy, and cultural norms.
REVIEW | doi:10.20944/preprints202305.0671.v1
Subject: Public Health And Healthcare, Primary Health Care Keywords: physical activity; counseling; primary health care
Online: 9 May 2023 (14:53:26 CEST)
Background: To identify and appraise the impacts and effectiveness of counseling interventions based on the 5A model on indicators of physical activity in adults. Methods: In May, 2022, a systematic review was carried out. Searches were performed in Embase, Lilacs, Pubmed, Scielo, Scopus, Sportdiscus and Web of Science. To avoid potential losses searches also were made in Google Scholar and in reference lists. Assessment of studies, data extraction and synthesis took place independently by two researchers. Results: Four studies composed the synthesis, which involved people with an average age between 40 and 55 years, being women in the majority of the samples. It was observed that counseling was carried out in conjunction with other strategies, such as drawing up an action plan, sending text messages and offering educational material. Only one study showed a statistically significant difference between the intervention and control groups in the “daily number of steps” indicator. Conclusions: counseling based on the 5A model did not reflect significant findings in relation to physical activity. Considering that behavior change for many people is neither a simple nor a quick process and that the 5A model is promising for other behavioral indicators, we indicate the need to carry out new intervention studies, with an expanded focus in relation to themes related to physical activity (e.g., types, dos-es, risks, benefits, identification of barriers and assessment) and, in parallel, the offer of practices in the Primary Health Care setting.
ARTICLE | doi:10.20944/preprints202111.0174.v1
Subject: Medicine And Pharmacology, Orthopedics And Sports Medicine Keywords: coordination abilities; training; handball; physical activity
Online: 9 November 2021 (13:42:11 CET)
According to the reviewed literature, the selection system in the handball game is quite complex and requires new approaches from specialists, based on the current requirements of this game. It was found that a main selection criterion in the game of handball is the coordination abilities because the handball game is mainly based on coordination. In this paper is related the importance of coordinative abilities development in the handball game for young children (10-12 years old) selection process meet in Romania. The results are obtained from a sociological questionnaire, where 109 specialists in the handball game are interrogated, 38 of them being handball coaches, and 71 being teachers of physical education and sports with abilities in handball game. The answers delivered depend on each specialist experience, the knowledge possessed and the difficulties encountered over the years. As a general overview, in the opinion of the surveyed specialists, the selection process in the handball game for Romania does not live up to their expectations, and the development level of coordination abilities meet in 10-12 years children is medium to weak. A total of 51.9% from the respondents stressed the importance of developing coordination abilities to optimize the selection process of children for handball game, opening a new approach in the modern training methods for performance achievement.
ARTICLE | doi:10.20944/preprints202009.0330.v1
Subject: Medicine And Pharmacology, Pediatrics, Perinatology And Child Health Keywords: bullying; dentofacial features; physical features; schoolchildren
Online: 15 September 2020 (04:48:47 CEST)
Context: bullying among schoolchildren is a serious phenomenon and a leading health concern. Aim: to determine the prevalence of bullying, its forms, and its effect on academic abilities and school attendance, as well as associated sociodemographic, physical, and dentofacial features among Saudi schoolchildren. Methods: this cross-sectional study recruited a sample of 1131 parents of schoolchildren 8-18 years old and requested them to complete internationally accepted questionnaires for their children. Chi-square test and logistic regression analysis were used to analyze the data (p<0.05). Results: a majority (89.2%) of schoolchildren were bully victims. Physical bullying (48.9%) was the most common form of bullying. The youngest schoolchildren (8-11 years), those who disliked school classes or neither liked nor hated them, as well as those who were truant from school were more likely to be victims. In addition, those who had worse grades because of bullying, and those who were very often bullied because of good grades or because they showed an interest in school were more likely to be victims. With regards to targeted physical features, teeth were the number one target, followed by the shape of the lips and strength, while teeth shape and color was the most common dentofacial target, followed by anterior open bite and protruded anterior teeth. Boys and the youngest schoolchildren were more often subjected to bullying because of these features (p<0.05). Conclusions: the prevalence of bullying, mainly in a physical form, was high among Saudi schoolchildren, with a negative influence on students’ academic abilities. Problems related to teeth, in particular, which can be treated, were targets, mainly for boys and the youngest schoolchildren. More studies are required in Saudi Arabia to explore the issue further among schoolchildren, themselves.