Systematic Literature Review of Machine Learning for IoT Security
Prathibha Kiran Yemmanuru, Jones Yeboah, Khakata Esther N. G · 2023
Internet of Things or simply called IoT are growing exponentially, and they are predicted to double by 2030. Companies are rushing to release their IoT products into the market to gain a competitive edge. This is causing security lapses in IoT devices and luring attackers to hack the data easily. Machine learning (ML) can detect and mitigate attacks. In this systematic literature review, primary studies are conducted on ML algorithms used for IoT security and they are analysed. Primary studies are classified into five categories (to detect attacks, intrusions, DDoS attacks, Malware and ransomware detection). Research conducted is mentioned in detail in this paper and the scope for future work is also discussed.