A Survey on Recent Approaches in Intrusion Detection System in IoTs

Abstract

Internet of Things (IoTs) are Internet-connected devices that integrate physical objects and internet in diverse areas of life like industries, home automation, hospitals and environment monitoring. Although IoTs ease daily activities benefiting human operations, they bring serious security challenges worth concerning. IoTs have become potentially vulnerable targets for cybercriminals, so companies are investing billions of dollars to find an appropriate mechanism to detect these kinds of malicious activities in IoT networks. Nowadays intelligent techniques using Machine Learning (ML) and Artificial Intelligence (AI) are being adopted to prevent or detect novel attacks with best accuracy. This survey classifies and categorizes the recent Intrusion Detection approaches for IoT networks, with more focus on hybrid and intelligent techniques. Moreover, it provides a comprehensive review on IoT layers, communication protocols and their security issues which confirm that IDS is required in both layered and protocol approaches. Finally, this survey discusses the limitations and advantages of each approach to identify future directions of potential IDS implementation.