{"title":"Energy Balance Based Attack Detection for Cyber Physical Systems","authors":"Zhuyuan Li, Ying Yang, Zhengen Zhao, Ruijie Liu","doi":"10.1109/DDCLS55054.2022.9858499","DOIUrl":null,"url":null,"abstract":"In this article, the deficiency of a widely-used observer-based attack detection scheme for cyber physical systems (CPS) is analyzed and then a novel dissipativity-based attack detector is proposed. Firstly, the definition of kernel attacks is introduced to capture the stealthy attacks which can not be detected through well-established observer-based techniques. Further, a data-driven design of kernel attacks based on subspace identification methods deploying input and output data is presented. To detect kernel attacks, a dissipativity-based attack detector is formulated in light of energy balance equation, providing a complementary strategy to guarantee reliable detection of attacks. Finally, the validity of the presented approach is demonstrated in a numerical example.","PeriodicalId":412672,"journal":{"name":"2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS55054.2022.9858499","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this article, the deficiency of a widely-used observer-based attack detection scheme for cyber physical systems (CPS) is analyzed and then a novel dissipativity-based attack detector is proposed. Firstly, the definition of kernel attacks is introduced to capture the stealthy attacks which can not be detected through well-established observer-based techniques. Further, a data-driven design of kernel attacks based on subspace identification methods deploying input and output data is presented. To detect kernel attacks, a dissipativity-based attack detector is formulated in light of energy balance equation, providing a complementary strategy to guarantee reliable detection of attacks. Finally, the validity of the presented approach is demonstrated in a numerical example.