Advancements in Intrusion Detection Systems for Internet of Things Using Machine Learning
Shahid Ul Haq, Ash Mohammad Abbas · 2022
Advancement in technology leads to connecting different types of devices or things to the Internet and enables the formation of a special kind of network called the Internet of Things (IoT). Intrusion detection in an IoT is a challenging task due to its unique characteristics. Machine learning schemes possess the potential to improve intrusion detection systems in case of an IoT. In this paper, we present a survey of advancements in research on the use of machine learning approaches for intrusion detection in an IoT. Our focus is on architectures, schemes, and the types of machine learning approaches used for intrusion detection. We compare different schemes based on their basis and features.