Detecting Cybersecurity Attacks in Internet of Things Using Artificial Intelligence Methods: A Systematic Literature Review

Abdullahi, Mujaheed; Baashar, Yahia; Alhussian, Hitham; Alwadain, Ayed; Aziz, Norshakirah; Capretz, Luiz Fernando; Abdulkadir, Said Jadid

doi:10.3390/electronics11020198

articleElectronicsJan 10, 2022GOLD OA

Detecting Cybersecurity Attacks in Internet of Things Using Artificial Intelligence Methods: A Systematic Literature Review

MAMujaheed Abdullahi YBYahia Baashar HAHitham Alhussian AAAyed Alwadain NANorshakirah Aziz

Universiti Teknologi Petronas · Universiti Tenaga Nasional · +3 more institutions

Indexed incrossrefdoaj

Abstract

In recent years, technology has advanced to the fourth industrial revolution (Industry 4.0), where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have evolved exponentially on a large scale. The rapid development of IoT devices and networks in various forms generate enormous amounts of data which in turn demand careful authentication and security. Artificial intelligence (AI) is considered one of the most promising methods for addressing cybersecurity threats and providing security. In this study, we present a systematic literature review (SLR) that categorize, map and survey the existing literature on AI methods used to detect cybersecurity attacks in the IoT environment.…

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345

total citations

FWCI: 46.02
Percentile: 100%
References: 101

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Authors

7

Topics & keywords

Topics

Keywords

Computer science
Computer security
Intrusion detection system
Artificial intelligence
Machine learning
Support vector machine
The Internet
Random forest

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