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Centralized approximate optimal estimation for cyber‐physical systems under joint cyber‐attacks

Yuman Li, Hong Lin, Chang Zhao, James Lam

2023International Journal of Robust and Nonlinear Control11 citationsDOIOpen Access PDF

Abstract

Abstract This paper studies the state estimation for cyber‐physical systems with multiple channels under joint Denial‐of‐Service and deception attacks. We show that the optimal estimator (OE) cannot be implemented in practice, as its computational complexity exponentially grows with respect to time. Then, we develop a centralized approximate optimal estimator (AOE) by using a generalized pseudo‐Bayesian algorithm. This AOE is not only computationally efficient, but also features theoretically guaranteed performance and stability. Specifically, it is proved when the attack success rate is less than a threshold value, both the OE and the AOE are stable, and the averaged performance deviation between the OE and the proposed AOE remains bounded. Finally, simulation examples are provided to illustrate the obtained results.

Topics & Concepts

EstimatorBounded functionComputer scienceCyber-physical systemDenial-of-service attackJoint (building)Stability (learning theory)DeceptionState (computer science)AlgorithmBayesian probabilityMathematical optimizationMathematicsStatisticsArtificial intelligenceEngineeringMachine learningThe InternetSocial psychologyWorld Wide WebMathematical analysisOperating systemArchitectural engineeringPsychologySmart Grid Security and ResilienceFault Detection and Control SystemsNetwork Security and Intrusion Detection