Artificial immunity based distributed and fast anomaly detection for Industrial Internet of Things

Beibei Li, Yujie Chang, Hanyuan Huang, Wenshan Li, Tao Li, Wen Chen

Abstract: Highlights•Presenting a novel artificial immunity based distributed and fast anomaly detection system for IIoT.•Designing a new negative selection based hyper-dimensional anomaly detector generation model.•Crafting a point-hyperspace tree based self-detector indexing mechanism.•Demonstrating that the proposed AIm-ADS outperforms existing studies in both detection rate and detection time.