Hybrid Intrusion Detection System for Edge-Based IIoT Relying on Machine-Learning-Aided Detection

The design of an intrusion detection system (IDS) plays a critical role in guaranteeing the security of the Industrial Internet of Things (IIoT). Recently, the rapid development of edge-based IIoT has posed new challenges in the design of a beneficial IDS considering its billions of IIoT devices and substantially decentralized data interaction. Both the detection method and the system architecture become the key components in constructing an efficient IDS for edge-based IIoT. In this article, we survey the typical state-of-theart studies about detection methods and system structure of IDS. Moreover, we propose a hybrid IDS architecture and introduce a machine learning aided detection method, which outperforms the literature in terms of a range of benchmarks.