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Detection of Stealthy False Data Injection Attacks Against Cyber-Physical Systems:A Stochastic Coding Scheme 被引量:3

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摘要 This paper,from the view of a defender,addresses the security problem of cyber-physical systems(CPSs)subject to stealthy false data injection(FDI)attacks that cannot be detected by a residual-based anomaly detector without other defensive measures.To detect such a class of FDI attacks,a stochastic coding scheme,which codes the sensor measurement with a Gaussian stochastic signal at the sensor side,is proposed to assist an anomaly detector to expose the FDI attack.In order to ensure the system performance in the normal operational context,a decoder is adopted to decode the coded sensor measurement when received at the controller side.With this detection scheme,the residual under the attack can be significantly different from that in the normal situation,and thus trigger an alarm.The design condition of the coding signal covariance is derived to meet the constraints of false alarm rate and attack detection rate.To minimize the trace of the coding signal covariance,the design problem of the coding signal is converted into a constraint non-convex optimization problem,and an estimation-optimization iteration algorithm is presented to obtain a numerical solution of the coding signal covariance.A numerical example is given to verify the effectiveness of the proposed scheme.
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2022年第5期1668-1684,共17页 系统科学与复杂性学报(英文版)
基金 supported by the National Natural Science Foundation of China under Grant Nos.61925303,62088101,U20B2073,61720106011,and 62173002 the National Key R&D Program of China under Grant No.2018YFB1700100 the Beijing Natural Science Foundation under Grant No.4222045。
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