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Volume 12
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10.3390/electronics12183927
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Article

Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security

by
Sarah Bin Hulayyil
1,2,
Shancang Li
1,* and
Lida Xu
3
1
School of Computer Science and Informatics, Cardiff University, Cardiff CF10 3AT, UK
2
College of Applied Studies and Community Service, King Saud University, Riyadh 11451, Saudi Arabia
3
Department of Information Technology & Decision Sciences, Old Dominion University, Norfolk, VA 23529, USA
*
Author to whom correspondence should be addressed.
Electronics 2023, 12(18), 3927; https://doi.org/10.3390/electronics12183927
Submission received: 30 July 2023 / Revised: 6 September 2023 / Accepted: 8 September 2023 / Published: 18 September 2023
(This article belongs to the Special Issue Cyber-Physical Systems in Industrial IoT)
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Abstract

Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are exploited is increasingly challenging and is one of the key technologies to protect IoT devices from cyber attacks. This work conducts a comprehensive survey to investigate the methods and tools used in vulnerability detection in IoT environments utilizing machine learning techniques on various datasets, i.e., IoT23. During this study, the common potential vulnerabilities of IoT architectures are analyzed on each layer and the machine learning workflow is described for detecting IoT vulnerabilities. A vulnerability detection and mitigation framework was proposed for machine learning-based vulnerability detection in IoT environments, and a review of recent research trends is presented.
Keywords: IoT security; vulnerability detection; cyber attacks; device security IoT security; vulnerability detection; cyber attacks; device security

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MDPI and ACS Style

Hulayyil, S.B.; Li, S.; Xu, L. Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security. Electronics 2023, 12, 3927. https://doi.org/10.3390/electronics12183927

AMA Style

Hulayyil SB, Li S, Xu L. Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security. Electronics. 2023; 12(18):3927. https://doi.org/10.3390/electronics12183927

Chicago/Turabian Style

Hulayyil, Sarah Bin, Shancang Li, and Lida Xu. 2023. "Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security" Electronics 12, no. 18: 3927. https://doi.org/10.3390/electronics12183927

APA Style

Hulayyil, S. B., Li, S., & Xu, L. (2023). Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security. Electronics, 12(18), 3927. https://doi.org/10.3390/electronics12183927

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