Sarker, I.H.; Khan, A.I.; Abushark, Y.B.; Alsolami, F. Internet of Things (IoT) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions and Research Directions. Mobile Networks and Applications 2022, doi:10.1007/s11036-022-01937-3.
Sarker, I.H.; Khan, A.I.; Abushark, Y.B.; Alsolami, F. Internet of Things (IoT) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions and Research Directions. Mobile Networks and Applications 2022, doi:10.1007/s11036-022-01937-3.
Sarker, I.H.; Khan, A.I.; Abushark, Y.B.; Alsolami, F. Internet of Things (IoT) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions and Research Directions. Mobile Networks and Applications 2022, doi:10.1007/s11036-022-01937-3.
Sarker, I.H.; Khan, A.I.; Abushark, Y.B.; Alsolami, F. Internet of Things (IoT) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions and Research Directions. Mobile Networks and Applications 2022, doi:10.1007/s11036-022-01937-3.
Abstract
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.
Keywords
Internet of Things; cyber-attacks; anomalies; machine learning; deep learning; IoT data analytics; intelligent decision-making; security intelligence
Subject
Computer Science and Mathematics, Security Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
