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Preprint ARTICLE | doi:10.20944/preprints202009.0249.v1

Cybersecurity Issues and Challenges during Covid-19 Pandemic

Alya Hannah Ahmad Kamal, Caryn Chuah Yi Yen, Mah Hui Ping, F Zahra

Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity issues; cybersecurity challenges; Covid-19; security attacks

Online: 11 September 2020 (08:20:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0443.v1

CICIoT2023: A real-time dataset and benchmark for large-scale attacks in IoT environment

Euclides Carlos Pinto Neto, Sajjad Dadkhah, Raphael Ferreira, Alireza Zohourian, Rongxing Lu, Ali A Ghorbani

Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Things (IoT); Dataset; Security; Machine Learning; Deep Learning; DoS; DDoS; Reconnaissance; Web Attacks; Brute Force; Spoofing; Mirai

Online: 8 May 2023 (04:41:28 CEST)

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Preprint REVIEW | doi:10.20944/preprints202101.0457.v1

AI-Driven Cybersecurity: An Overview, Security Intelligence Modeling and Research Directions

Iqbal H. Sarker

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)

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Preprint REVIEW | doi:10.20944/preprints202102.0082.v1

Online Identity Theft, Security Issues, and Reputational Damage

Sopna A/P Sinnathamby Sehgar, Zuriati Ahmad Zukarnain

Subject: Computer Science And Mathematics, Security Systems Keywords: identity theft; cyber-crime; identity fraud; types; techniques

Online: 2 February 2021 (10:31:24 CET)

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Preprint REVIEW | doi:10.20944/preprints201607.0077.v1

Current State of Art in Security of Data Aggregator in Smart Grids

Naina Emmanuel, Adeel Anjum, Sadia Shafiq, Mahamud Hussein Adam

Subject: Computer Science And Mathematics, Security Systems Keywords: Data aggregation, Security and Wireless Sensor Network

Online: 25 July 2016 (14:38:07 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201610.0004.v1

Vehicular Cloud Network and Information Security Mechanisms

Hsin-Te Wu, Gwo-Jiun Horng

Subject: Computer Science And Mathematics, Security Systems Keywords: Vehicular Ad Hoc Network (VANET); Cloud Computing; privacy preservation; security and privacy

Online: 3 October 2016 (20:40:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201807.0207.v1

Smart Home Anti-Theft System: A Novel Approach for Near Real-Time Monitoring, Smart Home Security and Large Video Data Handling for Wellness Protocol

Sharnil Pandya, Hemant Ghayvat, Ketan Kotecha, Moi Hoon Yap, Prosanta Gope

Subject: Computer Science And Mathematics, Security Systems Keywords: smart anti-theft system; intruder detection; unsupervised activity monitoring; smart home; partially/fully covered faces

Online: 11 July 2018 (16:47:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201706.0001.v1

Network Security Issues and Solutions on Vehicular Communication Systems

Oğuz Erçakır, Orkun Kızılırmak, Volkan Erol

Subject: Computer Science And Mathematics, Security Systems Keywords: vehicle to vehicle communications; vehicle to infrastructure communications; network security; mobile ad-hoc networks

Online: 1 June 2017 (04:51:57 CEST)

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Preprint REVIEW | doi:10.20944/preprints202102.0340.v1

Deep Cybersecurity: A Comprehensive Overview from Neural Network and Deep Learning Perspective

Iqbal H. Sarker

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)

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Preprint ARTICLE | doi:10.20944/preprints202108.0047.v1

Artificial Intelligence and Military Applications: Innovations, Cybersecurity Challenges & Open Research Areas

Priyanka Jayakumar, Sarfraz Nawaz Brohi, Noor Zaman Jhanjhi

Subject: Computer Science And Mathematics, Security Systems Keywords: Artificial Intelligence; Military technology; Robotic and Autonomous systems; Autonomous weapons systems

Online: 2 August 2021 (14:33:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0115.v1

The Future of Cybersecurity with Artificial Intelligence (AI) and Machine Learning (ML)

Hrishitva Patel

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)

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Preprint REVIEW | doi:10.20944/preprints202203.0087.v1

Internet of Things (IoT) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions and Research Directions

Iqbal H. Sarker, Asif Irshad Khan, Yoosef B. Abushark, Fawaz Alsolami

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)

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Preprint REVIEW | doi:10.20944/preprints202006.0139.v1

Cybersecurity Data Science: An Overview from Machine Learning Perspective

Iqbal H. Sarker

Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity; machine learning; data science; decision making; cyber-attack; security modeling; intrusion detection; threat intelligence

Online: 11 June 2020 (12:12:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202009.0110.v1

Security and Privacy Issues in Wireless Networks and Mitigation Methods

Alya Hannah Ahmad Kamal, Caryn Chuah Yi Yen, Pang Sze Ling, Fatima -tuz-Zahra

Subject: Computer Science And Mathematics, Security Systems Keywords: wireless networks; security attacks; privacy issues; mitigation methods

Online: 5 September 2020 (03:59:03 CEST)

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Preprint REVIEW | doi:10.20944/preprints202208.0513.v1

The Increase in Security Breaches through Remote Working

Syed Adnan Jawaid

Subject: Computer Science And Mathematics, Security Systems Keywords: Increase in Security Breaches through Remote Working; Security Breaches; Remote Working issues; Remote Working Challenges; Vulnerability issues while Remote working

Online: 30 August 2022 (07:58:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.0317.v1

Blockchain-Based Decentralised Privacy-Preserving Machine Learning Authentication and Verification With Immersive Devices in the Urban Metaverse Ecosystem

Kaya Kuru, Kaan Kuru

Subject: Computer Science And Mathematics, Security Systems Keywords: Metaverse; Smart City (SC); Digital Twins (DTs); cybersecurity; Swarm Artificial Intelligence (SAI); Collaborative Deep Learning (CDL); Federated Learning (FL); Privacy-Preserving Machine Learning (PPML); blockchain; avatar

Online: 6 February 2024 (10:32:40 CET)

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Preprint ARTICLE | doi:10.20944/preprints201912.0079.v1

Survey on Security Issues in Mobile Cloud Computing and Prevention Measures

Rahul Neware

Subject: Computer Science And Mathematics, Security Systems Keywords: mobile computing; cloud computing; security; virtualisation; privacy; authentication; storage

Online: 6 December 2019 (10:49:43 CET)

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Preprint REVIEW | doi:10.20944/preprints202208.0235.v1

Cyber Security; Etiology and Importance

Syed Jawaid

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)

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Preprint ARTICLE | doi:10.20944/preprints202103.0406.v1

Security-Focused Prototyping: A Natural Precursor to Secure Development

Sam Attwood, Nana Onumah, Katie Paxton-Fear, Rupak Kharel

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)

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Preprint ARTICLE | doi:10.20944/preprints201903.0145.v1

Fog Computing Architecture, Applications and Security Issues: A Survey

Rahul Neware

Subject: Computer Science And Mathematics, Security Systems Keywords: Fog Computing, Cloud Computing, Security and Privacy, Edge Computing, Internet of Things

Online: 13 March 2019 (11:07:19 CET)

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The development of the Internet of Things (IoT) has triggered a virtual wave of interconnection and intercommunication among an enormous number of universal things. This has caused an exceptional surge of colossal heterogeneous information, known as an information explosion. Until now, cloud computing has filled in as a proficient method to process and store these data. Still, it came to light that by utilizing just cloud computing, pesky issues like, the expanding requests of actual-time or speed-sensitive applications and the restrictions on system transfer speed could not be solved. Consequently, another computing platform, called fog computing has been advanced as a supplement to the cloud arrangement. Fog computing spreads the cloud administrations and services to the edge of the system, and brings processing, communications and reserving and storage capacity closer to edge gadgets and end-clients and, in the process, aims at enhancing versatility, low latency, transfer speed and safety and protection. This paper takes an extensive and wide-ranging view of fog computing, covering several aspects. At the outset is outlined the many-layered structural design of fog computing and its attributes. After that, chief advances like communication and inter-exchange, computing, reserving and storage, asset administration, naming, safety and safeguarding of privacy are delineated while showing how this backup and facilitate the installations and various applications. Then, numerous applications like augmented reality (AR), healthcare, gaming and brain-machine interface, vehicular computing, smart scenarios etc. are highlighted to explain the fog computing application milieu. Following that, it is shown that how, despite fog computing being a features-rich platform, it is dogged by its susceptibility to several security, privacy and safety concerns, which stem from the nature of its widely distributed and open architecture. Finally, some suggestions are advanced to address some of the safety challenges discussed so as to propel the further growth of fog computing.

Preprint ARTICLE | doi:10.20944/preprints202008.0523.v1

Security and Privacy Issues in Wireless Networks

Nurul Fatini Azhar, Qi Jie Ngoo, Tae Hyun Kim, Kohei Dozono, Fatima tuz Zahra

Subject: Computer Science And Mathematics, Security Systems Keywords: Wireless networks and communication; security issues; HTTP flood attack; SYN flood attack; Internet of Things; blockchain

Online: 24 August 2020 (09:53:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.0898.v1

CICIoMT2024: Attack Vectors in Healthcare devices-A Multi-Protocol Dataset for Assessing IoMT Device Security

Sajjad Dadkhah, Euclides Carlos Pinto Neto, Raphael Ferreira, Reginald Chukwuka Molokwu, Somayeh Sadeghi, Ali Ghorbani

Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Medical Things (IoMT); Internet of Things (IoT); Intrusion Detection System (IDS); ; Security; Dataset; IoT Healthcare

Online: 16 February 2024 (07:45:08 CET)

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The Internet of Things (IoT) has a growing presence in society's daily lives. These lightweight devices can be easily deployed and maintained, enabling extensive adoption in different environments. Furthermore, one of the most promising areas for using IoT devices is healthcare, comprising devices referred to as the Internet of Medical Things (IoMT). Several examples of healthcare services are supported by IoMT devices, e.g., continuous health monitoring. Conversely, there is an increasing concern with the cybersecurity aspects of these devices, and several attacks against IoT infrastructures have been launched in the past few years. These cybersecurity concerns also apply to healthcare applications, where the tradeoff between the benefits and security of IoMT devices must be observed. Given the complexity and amount of data IoMT network traffic generates, advanced methods become especially useful in these environments. Although Machine Learning (ML) brings various techniques and solutions to improve cyberattack detection, prevention, and mitigation, essential features are not addressed in the current state-of-the-art benchmark dataset contributions. Thereupon, the main goal of this research is to propose a realistic benchmark dataset to enable the development and evaluation of IoMT security solutions. In order to accomplish this, 18 attacks were executed against an IoMT testbed composed of 40 IoMT devices (25 real devices and 15 simulated devices), considering the plurality of protocols used in healthcare (e.g., Wi-Fi, MQTT, and Bluetooth). These attacks are categorized into five classes: DDoS, DoS, Recon, MQTT, and spoofing. This effort aims to establish a baseline complementary to the state-of-the-art contributions. The outcome supports researchers in investigating and developing new solutions to make healthcare systems more secure using different mechanisms (e.g., machine learning - ML). This research goes beyond merely conducting attacks on IoMT devices. We also attempt to capture the lifecycle of these devices in different vital phases, from the moment they join the network until they leave, which is called profiling. Profiling allows the different classifiers to identify anomalies of each device individually in the healthcare network. The CICIoMT2024 dataset has been published on CIC's dataset page, making it available for other researchers to use.

Preprint ARTICLE | doi:10.20944/preprints202309.0879.v1

Random Number Generators: Principles and Applications

Anastasios Bikos, Panayiotis E. Nastou, Georgios Petroudis, Yannis Stamatiou

Subject: Computer Science And Mathematics, Security Systems Keywords: Random Number Generation; Cryptography

Online: 14 September 2023 (03:37:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202104.0580.v1

Provisioning Cybersecurity in ICT Complex Supply Chains: An Overview, Key Issues and a Relevant Architecture

Xavi Masip-Bruin, Eva Marín-Tordera, José Ruiz, Admela Jukan, Panagiotis Trakadas, Ales Cernivec, Antonio Lioy, Diego López, Henrique Santos, Antonis Gonos, Ana Silva, Jose Soriano, Grigorios Kalogiannis

Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity; supply chains; IoT systems; systems integration, real scenarios analysis

Online: 21 April 2021 (12:33:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201910.0032.v1

Implementation of Cutting-Edge Internet Technology to the Improvement of Revenue Generation Using Cyber-Security

Joseph Oboyi, Leonard Chinedu Udeze, Paul Tawo Bukie, Emmanuel O. Onoja

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)

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Preprint ARTICLE | doi:10.20944/preprints201809.0524.v1

A Comprehensive Attack Flow Model and Security Analysis for Wi-Fi and WPA3

Christopher P. Kohlios, Thaier Hayajneh

Subject: Computer Science And Mathematics, Security Systems Keywords: WPA3; WiFi; attack flow; security analysis; WLAN

Online: 27 September 2018 (03:19:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201810.0618.v1

Security and Cryptographic Challenges for Authentication Based on Biometrics Data

Stefania Loredana Nita, Marius Iulian Mihailescu, Valentin Corneliu Pau

Subject: Computer Science And Mathematics, Security Systems Keywords: classification; machine learning; chaos-based cryptography; Hadoop; data clustering; biometrics

Online: 26 October 2018 (05:50:53 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0164.v1

Cybonto: Towards Human Cognitive Digital Twins for Cybersecurity

Tam Nguyen

Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity; Artificial General Intelligence; Human Behavior Modeling; Cognitive Systems; Cognitive Twins; Digital Twins

Online: 6 August 2021 (13:42:12 CEST)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints201908.0295.v2

Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk

Sharad Agarwal, Pascal Oser, Stefan Lüders

Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Things; security; vulnerabilities and protective measures; control network security; operation in multi-user environments; risk assessment

Online: 15 September 2019 (02:55:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.1768.v2

Unveiling the Dark Side of ChatGPT: Exploring Cyberattacks and Enhancing User Awareness

Moatsum Alawida, Bayan Abu Shawar, Oludare Isaac Abiodun, Abid Mehmood, Abiodun Esther Omolara, Ahmad k. Al Hwaitat

Subject: Computer Science And Mathematics, Security Systems Keywords: Generative Pre-training Transformer; ChatGPT; cyberattacks; ChatGPT cybersecurity

Online: 8 November 2023 (16:16:14 CET)

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Preprint ARTICLE | doi:10.20944/preprints202004.0481.v1

IntruDTree: A Machine Learning-Based Cyber Security Intrusion Detection Model

Iqbal H. Sarker

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)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints201908.0295.v1

Detecting IoT Devices and How They Put Large Heterogeneous Networks at Security Risk

Sharad Agarwal, Pascal Oser, Stefan Lüders

Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Things; security; vulnerabilities and protective measures; control network security; operation in multi-user environments; risk assessment

Online: 28 August 2019 (14:23:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201807.0227.v1

Design and Implementation of A Security Improvement Framework of Zigbee Network for Intelligent Monitoring in IoT Platform

S M Sohel Rana, Miah Abdul Halim, M Humayun Kabir

Subject: Computer Science And Mathematics, Security Systems Keywords: real-time intelligent monitoring; zigbee protocol; Internet of Things (IoT); office security system; security-threats

Online: 13 July 2018 (05:25:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202202.0099.v1

Functionality-preserving Adversarial Machine Learning For Robust Classification In Cybersecurity And Intrusion Detection Domains: A Survey

Andrew McCarthy, Essam Ghadafi, Panagiotis Andriotis, Phil Legg

Subject: Computer Science And Mathematics, Security Systems Keywords: cybersecurity; adversarial machine learning; machine learning; intrusion detection; functionality-preservation

Online: 7 February 2022 (16:22:14 CET)

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Machine learning has become widely adopted as a strategy for dealing with a variety of cybersecurity issues, ranging from insider threat detection to intrusion and malware detection. However, by their very nature, machine learning systems can introduce vulnerabilities to a security defence whereby a learnt model is unaware of so-called adversarial examples that may intentionally result in mis-classification and therefore bypass a system. Adversarial machine learning has been a research topic for over a decade and is now an accepted but open problem. Much of the early research on adversarial examples has addressed issues related to computer vision, yet as machine learning continues to be adopted in other domains, then likewise it is important to assess the potential vulnerabilities that may occur. A key part of transferring to new domains relates to functionality-preservation, such that any crafted attack can still execute the original intended functionality when inspected by a human and/or a machine. In this literature survey, our main objective is to address the domain of adversarial machine learning attacks and examine the robustness of machine learning models in the cybersecurity and intrusion detection domains. We identify the key trends in current work observed in the literature, and explore how these relate to the research challenges that remain open for future works. Inclusion criteria were: articles related to functionality-preservation in adversarial machine learning for cybersecurity or intrusion detection with insight into robust classification. Generally, we excluded works that are not yet peer-reviewed; however, the authors include some significant papers that make a clear contribution to the domain. There is a risk of subjective bias in the selection of non-peer reviewed articles; however, this is mitigated by co-author review. We selected the following databases with a sizeable computer science element to search and retrieve literature: IEEE Xplore, ACM Digital Library, ScienceDirect, Scopus, SpringerLink,Google Scholar. The literature search was conducted upto January 2022. We have striven to ensure a comprehensive coverage of the domain to the best of our knowledge. We have performed systematic searches of the literature, noting our search terms and results, and following up on all materials that appear relevant and fit within the topic domains of this review. This research was funded by the Partnership PhD scheme at the University of the West of England in collaboration with Techmodal Ltd.

Preprint ARTICLE | doi:10.20944/preprints201906.0144.v1

Applications of Data Mining Algorithms for Network Security

Kai Chain

Subject: Computer Science And Mathematics, Security Systems Keywords: data mining; network security; association rules; DDoS

Online: 16 June 2019 (02:42:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202003.0332.v1

Franklin Tchakounté, Athanase Esdras Yera Pagore, Marcellin Atemkeng, Jean Claude Kamgang

Subject: Computer Science And Mathematics, Security Systems Keywords: reputation; Android; application; sentiment analysis; comments; security service; NLP; Google Play; polarity

Online: 23 March 2020 (04:22:23 CET)

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Preprint ARTICLE | doi:10.20944/preprints202311.0676.v1

Using Large Language Models to Mitigate Ransomware Threats

Fang Wang

Subject: Computer Science And Mathematics, Security Systems Keywords: ransomware; malware; ransomware mitigation

Online: 10 November 2023 (07:44:31 CET)

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Preprint ARTICLE | doi:10.20944/preprints202004.0362.v1

A Novel Methodology for Securing IoT Objects Based on their Security Level Certificates

Akram abdulghani Hezam

Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Things (IoT); security goals; security guidelines; IoT assets; IoT security level certificates; countermeasures; IoT attacks; secure IoT frameworks

Online: 20 April 2020 (12:04:32 CEST)

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Internet of Things (IoT) provides a huge business value for customers, organizations, and governments due to the developments of so many applications in different sectors like energy and healthcare. Nevertheless, as a new emerging technology, IoT faces several security concerns that are more challenging than conventional Internet because of its limited resources as well as its complex ecosystem. Toward this end, we first highlight IoT security challenges and briefly discuss its security goals like confidentiality and integrity. Second, we discuss the most common attacks against IoT, along with their violated security goals. We also review the existing frameworks of security and privacy guidelines for IoT and illustrate their shortcomings. Third, we propose a novel framework for securing IoT objects, the key objective of which is to assign different Security Level Certificates (SLCs) for IoT objects based on their hardware capabilities and protection measures. Objects with SLCs, therefore, will be able to communicate with each other or with the Internet in a secure manner. The proposed framework is composed of five main phases. In phase 1, we classify IoT assets into four components: (i) physical objects, (ii) protocols, (iii) data at rest, and (iv) software, which includes operating systems, middlewares, and applications. We also classify IoT objects into five categories based on their hardware capabilities. In phase 2, we propose security and privacy guidelines for previously mentioned IoT assets, along with their protection measures. In phase 3, we classify protection measures into five SLCs, and then we assign different SLCs for IoT objects. In phase 4: we develop a communication plan between objects based on their SLCs. In phase 5, we propose a four-step method to seamlessly integrate our objects with legacy objects ( objects are not developed according to our framework). Fourth, the feasibility and application of this framework are illustrated using smart homes as a case study. Finally, we investigate how our framework would lessen several attacks and threats against IoT like routing attacks and physical damage. We also provide qualitative arguments to show that this framework could be utilized to solve some of IoT security challenges such as tight resource constrains. Moreover, we discuss the shortcomings of our suggested framework.

Preprint ARTICLE | doi:10.20944/preprints202001.0303.v1

Securing Internet of Things against Physical Layer Attacks Using Hybrid Security Algorithm (HSA)

Meysam Zarei

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)

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Preprint ARTICLE | doi:10.20944/preprints202207.0054.v1

Social Engineering: Concepts, Techniques, and Security Countermeasures

Maria Ul Aziz

Subject: Computer Science And Mathematics, Security Systems Keywords: social engineering; security countermeasures; security awareness; security policies

Online: 5 July 2022 (03:39:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.1768.v1

Unveiling the Dark Side of ChatGPT: Exploring Cyberattacks and Enhancing User Awareness

Moatsum Alawida, Bayan Abu Shawar, Oludare Isaac Abiodun, Abid Mehmood, Abiodun Esther Omolara, Ahmad k. Al Hwaitat

Subject: Computer Science And Mathematics, Security Systems Keywords: Generative Pre-training Transformer; ChatGPT; Cyberattacks; ChatGPT cybersecurity

Online: 26 September 2023 (13:55:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201812.0166.v1

Operational Risk of Insecurity using Control Self Risk Assessment and Linear Programming

Monday Osagie Adenomon, Ezekiel Awhigbo Bulus

Subject: Computer Science And Mathematics, Security Systems Keywords: Risk, Security, Linear programming, Nasarawa Eggon and CSRA

Online: 13 December 2018 (09:45:41 CET)

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Preprint REVIEW | doi:10.20944/preprints202211.0371.v1

Data Protection in Organization by the Implementation of Cyber Security

Syed Adnan Jawaid

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)

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Preprint REVIEW | doi:10.20944/preprints202304.0100.v1

The Metaverse: Economic and Social Values and Risks of New Cryptocurrencies and Blockchain Technologies

Petar Radanliev

Subject: Computer Science And Mathematics, Security Systems Keywords: Blockchain Technologies; Cryptocurrencies; Risk; Value

Online: 6 April 2023 (13:45:45 CEST)

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Preprint REVIEW | doi:10.20944/preprints202207.0298.v1

Holistic Systematic Review on Methodologies of Assessing Effectiveness Cybersecurity Awareness Program

Adamu Garba, Maheyzah Siraj, Siti Othman

Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity; Security Awareness Assessment; Machine Learning

Online: 20 July 2022 (08:22:30 CEST)

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Preprint REVIEW | doi:10.20944/preprints202110.0312.v1

Cybersecurity in the Internet of Things in Industrial Management

Ricardo Raimundo, Albérico Travassos Rosário

Subject: Computer Science And Mathematics, Security Systems Keywords: Cyber Security; Internet of Things

Online: 21 October 2021 (14:01:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202010.0577.v1

Compatibility of a Security Policy for a Cloud-based Healthcare System with the EU General Data Protection Regulation (GDPR)

Dimitra Georgiou, Costas Lambrinoudakis

Subject: Computer Science And Mathematics, Security Systems Keywords: Cloud Computing; Health Systems; Security; Privacy; Data Protection; GDPR

Online: 28 October 2020 (10:00:55 CET)

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Preprint ARTICLE | doi:10.20944/preprints202011.0418.v1

Systematic Literature Review of Security Pattern Research

Hironori Washizaki, Tian Xia, Natsumi Kamata, Yoshiaki Fukazawa, Hideyuki Kanuka, Takehisa Kato, Masayuki Yoshino, Takao Okubo, Shinpei Ogata, Haruhiko Kaiya, Atsuo Hazeyama, Takafumi Tanaka, Nobukazu Yoshioka, G Priyalakshmi

Subject: Computer Science And Mathematics, Security Systems Keywords: Security patterns; Software patterns; Systematic literature review (SLR)

Online: 16 November 2020 (12:13:53 CET)

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Preprint REVIEW | doi:10.20944/preprints202008.0082.v3

Cybersecurity in Intelligent Transportation Systems

Teodora Mecheva, Nikolay Kakanakov

Subject: Computer Science And Mathematics, Security Systems Keywords: ITS; IoT; VANET; cybersecurity

Online: 29 September 2020 (08:47:21 CEST)

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Preprint REVIEW | doi:10.20944/preprints202008.0082.v1

Cybersecurity in Intelligent Transportation Systems

Teodora Mecheva, Nikolay Kakanakov

Subject: Computer Science And Mathematics, Security Systems Keywords: ITS; IoT; VANET; cybersecurity

Online: 4 August 2020 (08:44:36 CEST)

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Working Paper ARTICLE

Mapping of the Security Requirements of GDPR and NIS

Najmudin Saqib, Vasileios Germanos, Wen Zeng, Leandros Maglaras

Subject: Computer Science And Mathematics, Security Systems Keywords: NISD; GDPR; cybersecurity

Online: 15 June 2020 (10:58:30 CEST)

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Preprint REVIEW | doi:10.20944/preprints202312.0205.v2

Integrating AI/ML in Cybersecurity: An Analysis of Open XDR Technology and its Application in Intrusion Detection and System Log Management

Dimitrios Lazaros Pissanidis, Konstantinos Demertzis

Subject: Computer Science And Mathematics, Security Systems Keywords: Artificial Intelligence; Machine Learning; Open Extended Detection and Response; Intrusion Detection Systems; Endpoint Detection and Response; Security Information and Event Management; Threat Detection and Response

Online: 3 January 2024 (02:05:06 CET)

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In today's digital landscape, cybersecurity has become a priority, with attacks becoming increasingly sophisticated. Traditional security approaches are no longer enough, requiring a more dynamic and advanced response. In this context, integrating Artificial Intelligence (AI) and Machine Learning (ML) appears key to addressing this growing threat. However, despite their high effectiveness, there is a developed problem: the integration of various data sources and technologies for comprehensive protection. This article presents an in-depth review of integrating Artificial Intelligence and Machine Learning in cybersecurity, focusing particularly on Open Extended Detection and Response (Open XDR) technology. The literature review in this article was meticulously conducted with specific criteria in mind. It focused on sourcing peer-reviewed journals, authoritative cybersecurity publications, and recent conferences that primarily concentrate on the advancements in AI and ML within the cybersecurity domain, particularly from 2018 to 2023. This timeframe was chosen to ensure the inclusion of the most current and relevant developments in Open XDR technology, Intrusion Detection Systems, Endpoint Detection and Response, and Security Information and Event Management systems. Additionally, the review gave special attention to studies and reports highlighting practical implementations and real-world applications of these technologies, thereby ensuring a comprehensive understanding of their impact and effectiveness in enhancing cybersecurity resilience. The methodology used is a detailed literature review, examining how various cybersecurity components interact and function. These components include Intrusion Detection Systems (IDS), which monitor networks for malicious activities; Endpoint Detection and Response (EDR), which focuses on detecting and investigating security incidents on endpoints; and Security Information and Event Management (SIEM), systems that provide real-time analysis of security alerts. The review also considers the role of Active Directory, a directory service for Windows domain networks, and the process of log forwarding, where log files are transmitted to a central server for analysis, in the context of AI and ML. The paper delves into the development of AI and ML, underscoring their roles in cybersecurity for advanced data processing, pattern recognition, and predicting threats. It explores both supervised (where the model is trained on labeled data) and unsupervised learning (where the model learns from unlabeled data) in ML, and how these techniques bolster cybersecurity measures. The article highlights the significance of Open XDR as a critical innovation that integrates data from multiple sources for comprehensive security analysis. Further, the review discusses how the integration of AI and ML into various cybersecurity tools, such as IDS, EDR, and SIEM, augments capabilities in threat detection and response. It addresses the challenges and opportunities that AI and ML present in the cybersecurity domain, focusing on ethical issues, data privacy concerns, and the necessity for ongoing professional development in this rapidly advancing field. The paper concludes by affirming the effectiveness of merging AI and ML with these cybersecurity tools within the Open XDR framework.

Preprint ARTICLE | doi:10.20944/preprints202011.0644.v1

Towards Security-by-design in Automotive Development Process

Seungyeon Jeong, Sooyoung Kang, Seungjoo Kim

Subject: Computer Science And Mathematics, Security Systems Keywords: Automotive development; Secure SDLC; Evidence-based standard; ISO/SAE 21434; UNECE cybersecurity regulation

Online: 25 November 2020 (14:00:18 CET)

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Preprint CASE REPORT | doi:10.20944/preprints202308.1936.v1

Instrumenting OpenCTI with a Capability for Attack Attribution Support

Sami Ruohonen, Alexey Kirichenko, Dmitriy Komashinskiy, Mariam Pogosova

Subject: Computer Science And Mathematics, Security Systems Keywords: cyberattack; technical cyberattack attribution; digital forensics; machine learning; cyber threat intelligence

Online: 29 August 2023 (09:59:53 CEST)

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Working Paper REVIEW

Cybersecurity in Intelligent Transportation Systems

Teodora Mecheva, Nikolay Kakanakov

Subject: Computer Science And Mathematics, Security Systems Keywords: ITS; IoT; VANET; cybersecurity

Online: 1 September 2020 (04:32:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0429.v1

Botnets: Security Challenges, Taxonomy and Detection

Sumayah Abdullah

Subject: Computer Science And Mathematics, Security Systems Keywords: Botnets; Bots; bot controller; botnet detection; network; botnet architecture; botnet attacks; detection techniques

Online: 30 June 2022 (14:09:31 CEST)

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Preprint REVIEW | doi:10.20944/preprints202401.0159.v1

Leveraging AI/ML for anomaly detection, threat prediction, and automated response.

Olakunle Abayomi Ajala

Subject: Computer Science And Mathematics, Security Systems Keywords: Information and communication technologies; Communication; networking Knowledge exchange; social interaction; Digital landscape; Information security; Cybercrime; Cybersecurity strategies; ; Artific

Online: 3 January 2024 (10:36:17 CET)

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Preprint REVIEW | doi:10.20944/preprints202211.0128.v1

Cyber Security Threats to Educational Institutes: A Growing Concern for the New Era of Cybersecurity

Syed Adnan Jawaid

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)

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Preprint ARTICLE | doi:10.20944/preprints202307.1666.v1

Improvements in Cybersecurity: Coupling Python for Digital Forensics

Abbas Abdulazeez Abdulhameed, Nadia Mahmood Hussien, Yasmin Makki Mohialden, Guillaume Herlem, Isabelle LAJOIE, Réda YAHIAOUI

Subject: Computer Science And Mathematics, Security Systems Keywords: cybersecurity; digital forensics; cyber threats; forensic investigator; python

Online: 25 July 2023 (07:56:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.0901.v1

Enhancing Cyber Security in Organisations by Establishing Attributes Towards Achieving Cyber Resilience

Thavaselvi Munusamy, Touraj Khodadadi, Mazdak Zamani

Subject: Computer Science And Mathematics, Security Systems Keywords: cyber resilience; cyber security; cyber risk; cyberattack; cyber domains

Online: 11 August 2023 (05:30:17 CEST)

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Preprint REVIEW | doi:10.20944/preprints202209.0032.v1

Machine Learning for Intelligent Data Analysis and Automation in Cybersecurity: Current and Future Prospects

Iqbal H. Sarker

Subject: Computer Science And Mathematics, Security Systems Keywords: cybersecurity; machine learning; deep learning; artificial intelligence; data-driven decision making; automation; cyber analytics; intelligent systems;

Online: 2 September 2022 (03:32:48 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202303.0183.v1

Human Activity Recognition-based Cyber-Physical System Security Through IoT-Cloud Computing

Sandesh Achar, Nuruzzaman Faruqui, Md Whaiduzzaman, Albara Awajan, Moutaz Alazab

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)

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Preprint ARTICLE | doi:10.20944/preprints202309.2064.v1

Adversarial Attacks Can Deceive AI Systems, Leading to Misclassification or Incorrect Decisions

Petar Radanliev, Omar Santos

Subject: Computer Science And Mathematics, Security Systems Keywords: adversarial attacks; artificial intelligence; machine learning; defense mechanisms; system integrity; model vulnerabilities; advanced attack techniques; Fast Gradient Sign Method (FGSM); Carlini and Wagner Attack (C&W); targeted attacks; non-targeted attacks; blackbox attacks

Online: 29 September 2023 (08:42:10 CEST)

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Working Paper ARTICLE

A Holistic Cybersecurity Maturity Assessment Framework for Higher Education Institutions

Aliyu Aliyu, Leandros Maglaras, Ying He, Iryna Yevseyeva, Eerke Boiten, Allan Cook, Helge Janicke

Subject: Computer Science And Mathematics, Security Systems Keywords: assessment framework; cyber security; GDPR; PCI-DSS; DSPT; NISD

Online: 23 April 2020 (15:40:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202401.0618.v1

Enhancing Privacy in the Internet of Vehicles via Hyperelliptic Curve Cryptography

George Routis, Panagiotis Dagas, Ioanna Roussaki

Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Things (IoT); Internet of Vehicles (IoV); Vehicular Ad-hoc Networks (VANETs); vehicle privacy; digital certificates; digital signatures; ECC; HECC; energy consumption; message size; Arduino; Zigbee

Online: 8 January 2024 (10:52:59 CET)

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Preprint ARTICLE | doi:10.20944/preprints202404.0238.v1

Sectrabank Model to Mitigate Computer Fraud in Electronic Operations through Banking Applications on Android Devices

Jhon Melendez, Jomark Noriega, Jose Tiznado, Paulo Calderon, Yordy Benites, Luis Rivera, Jose Herrera, Jorge Mayhuasca

Subject: Computer Science And Mathematics, Security Systems Keywords: fake app; SIM swapping; cybercrime; computer fraud; security; authentication

Online: 3 April 2024 (13:13:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.2218.v1

A New Data Balancing Approach based Generative Adversarial Network for Network Intrusion Detection System

Mohammad Jamoos, Antonio García, Mohammad AlKhanafseh, Ola Surakhi

Subject: Computer Science And Mathematics, Security Systems Keywords: Generative Adversarial Network; Intrusion Detection System; Imbalanced Dataset; Machine Learning; Unsupervised Learning

Online: 31 May 2023 (10:22:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.1194.v1

Collaborative Smart Production Supply Chains with Blockchain Based Digital Product Passports

Fatemeh Stodt, Nicolai Maisch, Philipp Ruf, Armin Lechler, Oliver Riedel, Christoph Reich

Subject: Computer Science And Mathematics, Security Systems Keywords: digital product passport; blockchain; GAIA-X; traceability; interoperability; privacy and security; circular economy; smart industries

Online: 21 February 2024 (13:11:13 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0508.v1

ML-Based Detection of Sybil Attack on MANETS

Humaira Ashraf, Mamona Nawaz, NZ Jhanjhi

Subject: Computer Science And Mathematics, Security Systems Keywords: Sybil Attacks; MANETs; Detection Techniques

Online: 5 January 2024 (15:17:49 CET)

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Preprint ARTICLE | doi:10.20944/preprints202308.2137.v1

Hardware Implementations of Elliptic Curve Cryptography Using Shift-Sub Based Modular Multiplication Algorithms

Yamin Li

Subject: Computer Science And Mathematics, Security Systems Keywords: elliptic curve cryptography; affine, projective, and Jacobian coordinates; modular multiplication; hardware security module; Verilog HDL; FPGA; cost/performance evaluation

Online: 31 August 2023 (09:35:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202401.1466.v1

Passwordless Authentication Using a Combination of Cryptography, Steganography, and Biometrics

Tunde Oduguwa, Abdullahi Arabo

Subject: Computer Science And Mathematics, Security Systems Keywords: Passwordless Authentication; RSA; AES; Fingerprint Biometrics; Keystroke Dynamics; LSB Steganography; Android; iOS

Online: 19 January 2024 (09:54:43 CET)

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Preprint ARTICLE | doi:10.20944/preprints202210.0030.v1

Evaluating Software Security in the Era of Quantum Computer by Using Fuzzy TOPSIS

Mohd. Nadeem, Syed Anas Ansar, Masood Ahmad, Prabhash Chandra Pathak, Dr. Rajeev Kumar, Raees Ahmad Khan

Subject: Computer Science And Mathematics, Security Systems Keywords: Quantum Computing; Software Security; Quantum Algorithm; Quantum Security.

Online: 5 October 2022 (09:52:43 CEST)

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Preprint BRIEF REPORT | doi:10.20944/preprints202402.0008.v1

Intrusion Detection Systems: Categories, attack detection and response.

Natalia Lewandowska

Subject: Computer Science And Mathematics, Security Systems Keywords: Intrusion Detection Systems (IDS); Intrusion Prevention System (IPS); Intrusion Response System (IRS); Anomaly (AIDS); Signature (SIDS); Heuristic; Network (NIDS); Host (HIDS); Hybrid; Cloud (CIDS)

Online: 1 February 2024 (08:23:30 CET)

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Working Paper ARTICLE

A Holistic Cybersecurity Maturity Assessment Framework for Higher Education Institutions in the United Kingdom

Aliyu Aliyu, Leandros Maglaras, Ying He, Iryna Yevseyeva, Eerke Boiten, Allan Cook, Helge Janicke

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)

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Preprint ARTICLE | doi:10.20944/preprints202304.0646.v1

Reliable and Delay Aware Routing Protocol for Underwater Wireless Sensor Networks (UWSNs)

Amjid Saleem, Sami Ullah, Najmul Hassan, Jungpil Shin

Subject: Computer Science And Mathematics, Security Systems Keywords: DRAR, Co-DRAR, Relay nodes; Cooperation; Energy efficiency; Routing protocol

Online: 20 April 2023 (10:08:29 CEST)

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Preprint REVIEW | doi:10.20944/preprints202403.0349.v1

A Systematic Literature Review of Zero Trust Architecture for UAV Security Systems in IoBT

Alanoud Abdullah Alquwayzani, Abdullah Abdulrahman Albuali

Subject: Computer Science And Mathematics, Security Systems Keywords: Security; Zero Trust Architecture (ZTA); Drone; UAV, UAV Security; Internet of Battlefield Things (IoBT); Cybersecurity; Suspicious Behavior

Online: 6 March 2024 (11:59:34 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.0770.v1

An Interdisciplinary Approach to Enhancing Cyber Threat Prediction Utilizing Forensic Cyberpsychology and Digital Forensics

Marshall S. Rich, Mary Aiken

Subject: Computer Science And Mathematics, Security Systems Keywords: forensic cyberpsychology; cyberpsychology; predictive analytics; prophet model; behavioral-centric threat intelligence; ISPs; cyber behavioral analysis; cyber forensics; behavioral analysis; time-series analysis; cyber defense

Online: 12 December 2023 (04:13:55 CET)

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A groundbreaking integrated predictive model, termed Cyber Forensics Behavioral Analysis (CFBA), has been developed in an environment characterized by rapidly evolving and increasingly sophisticated cyber threats. This model merges Cyber Behavioral Sciences with Digital Forensics to enhance the prediction accuracy and effectiveness of cyber threats originating from specific Autonomous System Numbers (ASNs). It has been observed that traditional cybersecurity strategies, predominantly focused on technical aspects, must be improved in addressing the complex landscape of cyber threats. Consequently, a novel approach has been proposed in this research, combining technical expertise with insights into the behavior of cybercriminals, thereby addressing a significant gap in existing methodologies. A mixed-methods approach has been employed in the study, integrating quantitative and qualitative research methods. This approach has created a comprehensive framework incorporating digital forensics, cybersecurity, computer science, forensic psychology, and the cyber behavioral sciences which incorporates disciplines scuch as cyberpsychology and forensic cyberpsychology. The study is anchored around four key concepts: (1) Forensic Cyberpsychology, which focuses on understanding psychological aspects of cybercriminal behavior; (2) Digital Forensics, involving the collection and analysis of digital evidence from cyber incidents; (3) Predictive Modeling, which utilizes historical data and patterns to anticipate potential cyber threats; and (4) the Cyber Behavioral Analysis Metric (CBAM) and Cyber Behavioral Score (CBS), tools designed for evaluating and scoring ASNs based on their behavior in terms of cybersecurity threat risks. Challenges encountered in the development of this integration have been significant. Initial setbacks included the misalignment of traditional cyber defense methods with the evolving nature of cyber threats and the absence of a holistic approach in pre-existing models. Through the narrative of these challenges and the subsequent development of the CFBA model, the research highlights the necessity for an interdisciplinary approach to cybersecurity. The outcomes of this study are not merely theoretical but provide practical, actionable tools and frameworks that markedly improve the precision of predicting cyber threats, especially from ASNs. The CFBA model represents a significant shift in cybersecurity strategies, highlighting the importance of integrating behavioral insights with technical knowledge. The study emphasizes the need for ongoing research and collaboration in cybersecurity, advocating for an approach that is as comprehensive and multifaceted as the cyber threats it seeks to mitigate. This research has been conducted to contribute significantly to cybersecurity, offering new perspectives and methodologies in a rapidly changing domain.

Preprint REVIEW | doi:10.20944/preprints202312.1449.v1

A Survey of Intrusion Detection Systems based Machine Learning Approaches Applied to Software-Defined Networks (SDN): Research Issues and Challenges

Ahmed Hasan Kadhim Janabi, Triantafyllos Kanakis, Mark Johnson

Subject: Computer Science And Mathematics, Security Systems Keywords: Software-Defined Network (SDN), Intrusion Detection System (IDS), Machine Learning (ML), Deep Learning (DL), non-Deep Learning, OpenFlow, Control Plane, Data Plane, attack, security, and challenges.

Online: 19 December 2023 (11:18:08 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.0615.v1

Secure Cloud Computing By A dual-Layer Encryption Mechanism

Sanaa Ali Jabber, Soukaena Hashem, Shtha Jafer

Subject: Computer Science And Mathematics, Security Systems Keywords: cloud; storage; secure; SOA; AES; RSA; LSTM

Online: 8 December 2023 (13:15:30 CET)

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Preprint ARTICLE | doi:10.20944/preprints202403.0702.v1

Convergence in Discrete Inverse Dynamical Systems

Eduardo Diedrich

Subject: Computer Science And Mathematics, Security Systems Keywords: Discrete dynamical systems; Inverse modeling; Topological equivalence; Topological transport; Algebraic trees; Combinatorial explosions; Computational complexity; Universal convergence

Online: 17 March 2024 (15:58:52 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0912.v2

Intrusion Detection System for Big Data Environment Using Deep Learning

Pooja Potnurwar, Ayush Ainchwar, Rahul Neware, Vrushali Bongirwar

Subject: Computer Science And Mathematics, Security Systems Keywords: intrusion detection system; big data; deep learning; CNN; LSTM; GAN; cybersecurity; network security

Online: 15 January 2024 (08:11:36 CET)

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Preprint REVIEW | doi:10.20944/preprints202312.0205.v1

Integrating AI/ML in Cybersecurity: An Analysis of Open XDR Technology and its Application in Intrusion Detection and System Log Management

Dimitrios Lazaros Pissanidis, Konstantinos Demertzis

Subject: Computer Science And Mathematics, Security Systems Keywords: Artificial Intelligence; Machine Learning; Open Extended Detection and Response; Intrusion Detection Systems; Endpoint Detection and Response; Security Information and Event Management; Threat Detection and Response

Online: 5 December 2023 (04:25:34 CET)

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In today's digital landscape, cybersecurity has become a priority, with attacks becoming increasingly sophisticated. Traditional security approaches are no longer enough, requiring a more dynamic and advanced response. In this context, integrating Artificial Intelligence (AI) and Machine Learning (ML) appears key to addressing this growing threat. However, despite their high effectiveness, there is a developed problem: the integration of various data sources and technologies for comprehensive protection. This article presents an in-depth review of integrating Artificial Intelligence and Ma-chine Learning in cybersecurity, focusing particularly on Open Extended Detection and Response (Open XDR) technology. The methodology used is a detailed literature review, examining how various cybersecurity components interact and function. These components include Intrusion Detection Systems (IDS), which monitor networks for malicious activities; Endpoint Detection and Response (EDR), which focuses on detecting and investigating security incidents on endpoints; and Security Information and Event Management (SIEM), systems that provide real-time analysis of security alerts. The review also considers the role of Active Directory, a directory service for Windows domain networks, and the process of log forwarding, where log files are transmitted to a central server for analysis, in the context of AI and ML. The paper delves into the development of AI and ML, underscoring their roles in cybersecurity for advanced data processing, pattern recognition, and predicting threats. It explores both supervised (where the model is trained on labeled data) and unsupervised learning (where the model learns from unlabeled data) in ML, and how these techniques bolster cybersecurity measures. The article highlights the significance of Open XDR as a critical innovation that integrates data from multiple sources for comprehensive security analysis. Further, the review discusses how the integration of AI and ML into various cybersecurity tools, such as IDS, EDR, and SIEM, augments capabilities in threat detection and response. It addresses the challenges and opportunities that AI and ML present in the cybersecurity domain, focusing on ethical issues, data privacy concerns, and the necessity for ongoing professional development in this rapidly advancing field. The paper concludes by affirming the effectiveness of merging AI and ML with these cybersecurity tools within the Open XDR framework. This integration significantly enhances threat detection, response efficiency, and overall cybersecurity resilience. The aim is to provide a comprehensive understanding of the current state of cybersecurity technologies, their interaction with AI and ML, and insights into the field's future developments.

Preprint REVIEW | doi:10.20944/preprints202212.0499.v1

Multi-aspects AI-based Modeling and Adversarial Learning for Cybersecurity Intelligence and Robustness: A Comprehensive Overview

Iqbal H. Sarker

Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity; artificial intelligence; machine learning; cyber data analytics; intelligent decision-making; adversarial attacks; robust secured systems; industry 4.0 applications.

Online: 27 December 2022 (01:53:56 CET)

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Preprint ARTICLE | doi:10.20944/preprints202306.0161.v1

Smartphone User Identification Using Accelerometer Data

Eyhab Al-Mahadeen, Mansoor Alghamdi, Ahmad S. Tarawneh, Majed Abdullah Alrowaily, Malek Alrashidi, Ibrahim S. Alkhazi, Almoutaz Mbaidin, Anas Ali Akasasbeh, Mohammad Ali Abbadi, Ahmad B. Hassanat

Subject: Computer Science And Mathematics, Security Systems Keywords: biometrics; deep learning; time series; feature selection; classification; accelerometer; Sustainability

Online: 2 June 2023 (09:00:51 CEST)

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Preprint REVIEW | doi:10.20944/preprints202311.0565.v1

Systematic Literature Review on 5G-IoT Security Aspects

Dalton Valadares, Newton Will, Álvaro Sobrinho, Anna Lima, Igor Morais, Danilo Santos

Subject: Computer Science And Mathematics, Security Systems Keywords: Internet of Things; 5G Networks; threats; vulnerabilities; mitigations

Online: 8 November 2023 (13:56:22 CET)

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Preprint ARTICLE | doi:10.20944/preprints202212.0130.v1

Quantum Logic Locking for Security

Rasit Onur Topaloglu

Subject: Computer Science And Mathematics, Security Systems Keywords: quantum computing; quantum circuit; qubit; quantum security; quantum logic locking; QLL; logic locking; hardware security

Online: 7 December 2022 (10:55:58 CET)

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Preprint REVIEW | doi:10.20944/preprints202403.0225.v1

Port Scanning Techniques Tools and Detection

Sam Coyle

Subject: Computer Science And Mathematics, Security Systems Keywords: Port Scanning; TCP; TCP SYN; UDP; Stealth Scan; ZMap; NMap; MASSCAN; Anomaly based detection; Signature based detection

Online: 5 March 2024 (06:30:01 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.1750.v1

A Cyber Risk Assessment Approach to Federated Identity Management Framework Based Digital Healthcare System

Shamsul Huda, Md. Rezaul Islam, Vinay Naga Vamsi Kottala, Jemal Hussen Abawajy

Subject: Computer Science And Mathematics, Security Systems Keywords: Cybersecurity risk for healthcare; Risk Framework and standards; Risk; threat models; risk mitigations

Online: 26 December 2023 (01:41:20 CET)

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Abstract: Integration of Medical Cyber Physical Systems (MCPS) and Internet-of-Medical Devices (IoMT) with conventional hospital networks have facilitated easy and speedy data collection, vertical and horizontal connectedness and collaborations among healthcare providers. Federated identity management (FIM) provides a solution towards the identity management challenge arising from this integration of millions of MCPSs to get personalized care and frictionless experiences for the patients, doctors, and employees. FIM protocols such as OAuth, Security Assertion Markup Language (SAML) are highly susceptible to cyber attacks like theft of barrier token, replay attack, message insertion, and Man-in-Middle attacks. IoMT devices have vulnerabilities in their firmware, operating systems, data encryption, data at store and data transmission. Combined vulnerabilities of FIM framework and IoMT devices creates major cyber risks for the current digital healthcare system. Therefore, a comprehensive and evidenced based cyber risk assessment is an urgent need for a cyber-safe digital health care system that can avoid frequent life threatening situations. This paper proposes a comprehensive and evidenced based cyber risk assessment approach for FIM and IoMT based collaborative digital healthcare systems. The novelty of the proposed approach is that it considers three dimensional vulnerabilities arising from existing IT communication protocols and infrastructure, IoMT and MCPS medical devices, protocols of FIM and their combined impact on hospitals and provides corresponding recommendations of security controls. The proposed approaches combine two industry standards including Cyber Resilience Review (CRR) asset management, NIST SP 800-30 to take advantage of both approaches. We have used a large number of IoMT and MCPS devices from multiple providers for threat modelling and produced evidence based cyber-risks using attack trees and detailed attack sequence diagrams to validate proposed approaches. The corresponding recommendation of security controls will support healthcare professionals and providers significantly for improving both the patient and medical device safety management within the FIM enabled healthcare ecosystem.

Preprint ARTICLE | doi:10.20944/preprints202402.1265.v1

Optimal Deployment

Peter Lohmander

Subject: Computer Science And Mathematics, Security Systems Keywords: optimization; Lanchester equations; attrition coefficients; differential equation system; numerical iteration

Online: 22 February 2024 (07:11:04 CET)

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This study focuses on the optimal deployment problem, and determines the optimal size of a military force to send to the battle field. The decision is optimized, based on an objective function, that considers the cost of deployment, the cost of the time it takes to win the battle, and the costs of killed and wounded soldiers with equipment. The cost of deployment is modeled as an explicit function of the number of deployed troops and the value of a victory with access to a free territory, is modeled as a function of the length of the time it takes to win the battle. The cost of lost troops and equipment, is a function of the size of the reduction of these lives and resources. An objective function, based on these values and costs, is optimized, under different parameter assumptions. The battle dynamics is modeled via the Lanchester differential equation system based on the principles of directed fire. First, the deterministic problem is solved analytically, via derivations and comparative statics analysis. General mathematical results are reported, including the directions of changes of the optimal deployment decisions, under the influence of alternative types of parameter changes. Then, the first order optimum condition from the analytical model, in combination with numerically specified parameter values, is used to determine optimal values of the levels of deployment in different situations. A concrete numerical case, based on documented facts from the Battle of Iwo Jima, during WW II, is analyzed, and the optimal US deployment decisions are determined under different assumptions. The known attrition coefficients of both armies, from USA and Japan, and the initial size of the Japanese force, are parameters. The analysis is also based on some parameters without empirical documentation, that are necessary to include to make optimization possible. These parameter values are motivated in the text. The optimal solutions are found via Newton- Raphson iteration. Finally, a stochastic version of the optimal deployment problem is defined. The attrition parameters are considered as stochastic, before the deployment decisions have been made. The attrition parameters of the two armies have the same expected values as in the deterministic analysis, are independent of each other, have correlation zero, and have relative standard deviations of 20%. All possible deployment decisions, with 5000 units intervals, from 0 to 150000 troops, are investigated, and the optimal decisions are selected. The analytical, and the two numerical, methods, all show that the optimal deployment level is a decreasing function of the marginal deployment cost, an increasing function of the marginal cost of the time to win the battle, an increasing function of the marginal cost of killed and wounded soldiers and lost equipment, an increasing function of the initial size of the opposing army, an increasing function of the efficiency of the soldiers in the opposing army and a decreasing function of the efficiency of the soldiers in the deployed army. With stochastic attrition parameters, the stochastic model also shows that the probability to win the battle is an increasing function of the size of the deployed army. When the optimal deployment level is selected, the probability of a victory is usually less than 100%, since it would be too expensive to guarantee a victory with 100% probability. Some of many results of relevance to the Battle of Iwo Jima, are the following: In the deterministic Case 0 analysis, the optimal US deployment level is 66200, the time to win the battle is 30 days and 14000 US soldiers are killed or wounded. If the marginal cost of the time it takes to win a victory doubles, the optimal deployment increases to 75400, the time to win a victory is reduced to 26 days, and less than 12000 soldiers are killed or wounded. In the stochastic Case 0 analysis, the optimal US deployment level is 65000, the expected time to win the battle is 46 days and almost 25000 US soldiers are expected to be killed or wounded. If the cost per killed or wounded soldier increases from 0 to 5 M $US, the optimal deployment level increases to 75000. Then, the victory is expected to appear after 35 days and 19900 US soldiers are expected to be killed or wounded.

Preprint REVIEW | doi:10.20944/preprints202310.1280.v1

Information Security Applications in Smart Cities: A Bibliometric Analysis of Emerging Research

Thiago Poleto, Thyago Celso Cavalcante Nepomuceno, Victor Diogho Heuer De Carvalho, Ligiane Cristina Braga de Oliveira Friaes, Rodrigo Cleiton Paiva De Oliveira, Ciro José Jardim Figueiredo

Subject: Computer Science And Mathematics, Security Systems Keywords: information security; smart city; technical collaborations networks; applications; bibliometric analysis

Online: 20 October 2023 (06:30:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.0374.v1

Software Vulnerability Detection Method Based on Abstract Syntax Tree Feature Migration（AST-FMVD）

Zi-Jun Li, Tao Li, Hao-Dong Chen, Qin Yu, Meng-qing Qiao, Lin Li

Subject: Computer Science And Mathematics, Security Systems Keywords: deep learning; transfer learning; zero-shot; vulnerability detection; abstract syntax tree

Online: 6 September 2023 (10:20:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.1005.v1

Continuous Authentication in the Digital Age: An Analysis of Reinforcement Learning and Behavioral Biometrics

Priya Bansal, Abdelkader Ouda

Subject: Computer Science And Mathematics, Security Systems Keywords: Continuous Authentication; Static Authentication; Behavioral Biometrics; Reinforcement Learning (RL); Q-learning; Keystroke Dynamics; Anomaly Detection; Machine Learning; Supervised Learning; User Authentication; Identification

Online: 14 June 2023 (07:42:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202212.0054.v1

Sharding-Based Proof-of-Stake Blockchain Protocols: Key Components & Probabilistic Security Analysis

Abdelatif Hafid, Abdelhakim Senhaji Hafid, Dimitrios Makrakis

Subject: Computer Science And Mathematics, Security Systems Keywords: Security analysis; Blockchain; probabilistic analysis; sharding-based Blockchain protocols; malicious nodes; Proof-of-Stake; practical Byzantine fault tolerance.

Online: 5 December 2022 (01:00:40 CET)

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Preprint REVIEW | doi:10.20944/preprints202305.1874.v1

Privacy-Preserving Blockchain Technologies

Dalton Cézane Gomes Valadares, Angelo Perkusich, Aldenor Martins Falcão, Chris Seline

Subject: Computer Science And Mathematics, Security Systems Keywords: Security; Trusted Execution Environments; Technical Analysis; Privacy Preservation

Online: 26 May 2023 (07:17:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202311.0950.v1

Implementation of an Enhanced Multi-Factor Authentication Scheme with a Track and Trace Capability for Online Banking Platforms

Glen Lehlohonolo Moepi, Topside Ehleketani Mathonsi

Subject: Computer Science And Mathematics, Security Systems Keywords: attacks; biometrics; Multi-Factor Authentication (MFA); online banking services; security; vulnerability

Online: 14 November 2023 (15:46:48 CET)

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Preprint REVIEW | doi:10.20944/preprints202312.0865.v1

Review of Generative Models in Generating Synthetic Attack Data for Cybersecurity

Garima Agrawal, Amardeep Kaur, Sowmya Myneni

Subject: Computer Science And Mathematics, Security Systems Keywords: Cyber Security; GANs; Network Security; Cyber-Attacks; Adversarial Attacks; Generative Models; Generative Nets, Synthetic Attack Data

Online: 12 December 2023 (13:10:48 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0555.v1

Cyber Security on the Edge: Efficient Enabling of Machine Learning on IoT Devices

Swati Kumari, Vatsal Tulshyan, Hitesh Tewari

Subject: Computer Science And Mathematics, Security Systems Keywords: IoT; Cyber Threats; Distributed Computing; AI-enabled Chips; Container Orchestration; DDoS Attacks

Online: 8 January 2024 (09:54:49 CET)

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Preprint ARTICLE | doi:10.20944/preprints202403.0714.v1

Blockchain-Based Zero Trust Supply Chain Security Integrated with Deep Reinforcement Learning

Shereen Ismail, Hajar Moudoud, Diana Dawoud, Hassan Reza

Subject: Computer Science And Mathematics, Security Systems Keywords: Security; Zero Trust; Blockchain; Smart Contract; Supply Chain; Deep Reinforcement Learning; Cyberattacks

Online: 12 March 2024 (14:00:37 CET)

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Preprint ARTICLE | doi:10.20944/preprints202308.0040.v1

Investigating IPTV Malware in the Wild

Adam Lockett, Ioannis Chalkias, Cagatay Yucel, Jane Henriksen-Bulmer, Vasilis Katos

Subject: Computer Science And Mathematics, Security Systems Keywords: Malware Analysis; Cyber Threat Intelligence; IPTV; Digital Investigations

Online: 2 August 2023 (05:29:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.1935.v1

Secure CAPTCHA by Genetic Algorithm (GA) and Multi-Layer Perceptron (MLP)

Saman Shojae Chaeikar, Fatemeh Mirzaei Asl, Saeid Yazdanpanah, Mazdak Zamani, Touraj Khodadadi

Subject: Computer Science And Mathematics, Security Systems Keywords: CAPTCHA; authentication; hand gesture recognition; genetic algorithm; multilayer perceptron; MLP

Online: 27 July 2023 (15:48:04 CEST)

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Computer Science and Mathematics