文章基本信息

标题：Enhanced Anomaly Detector for Nonlinear Cyber-Physical Systems against Stealthy Integrity Attacks
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作者：Kangkang Zhang ; Marios M. Polycarpou ; Thomas Parisini 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：13682-13687
DOI：10.1016/j.ifacol.2020.12.870
语种：English
出版社：Elsevier
摘要：AbstractThe detection of stealthy integrity attacks for nonlinear cyber-physical systems is a great challenge for the research community. This paper proposes a backward-in-time detection methodology to enhance the anomaly detector against stealthy integrity attacks for a class of nonlinear cyber-physical systems. It uses the virtual value of the state at a time instant prior to the occurrence time of the attacks for detecting stealthy attacks. The definition of stealthy integrity attacks is formulated in the context of nonlinear plants such that they are undetectable with respect to traditional anomaly detectors. A H∞fixed-point smoother is developed for estimating the analytical virtual values of the states at a prior time to the attack occurrence time, and then, the backward-in-time detection schemes are proposed based on the smoother. Based on the prior estimates, attack residual generation and threshold generation schemes are designed. Finally, a simulation is presented to illustrate the effectiveness of the enhanced anomaly detector.
关键词：KeywordsStealthy integrity attacksnonlinear cyber-physical systemsbackward-in-time detection methodology