Attack Detection Based on Encoding–Decoding Approach for Cyber–Physical Systems
Gaofeng Ren, Hao Liu, Yewei Zhang, Yuzhe Li
Abstract
This article is concerned with the attack detection issue for a class of nonlinear cyber–physical systems (CPSs) with unknown-but-bounded (UBB) noises. The nonlinear system is linearized by utilizing first-order Taylor expansion with Lagrangian remainder, and an observer based on zonotopic sets is proposed to estimate the system states. Then, a novel encoding–decoding strategy (EDS) is provided to improve the attack detection rate by selecting appropriate parameters. In order to alleviate the impact introduced by malicious attacks, a countermeasure is taken into account when an attack is detected by the abnormal detector. Finally, the hardware-in-the-loop (HIL) simulation is provided to illustrate the effectiveness of the proposed results.