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Article: Centralized approximate optimal estimation for cyber-physical systems under joint cyber-attacks

TitleCentralized approximate optimal estimation for cyber-physical systems under joint cyber-attacks
Authors
Keywordsapproximate optimal estimator
cyber-physical systems
deception attacks
denial-of-service attacks
optimal estimator
stability
Issue Date25-Mar-2024
PublisherWiley
Citation
International Journal of Robust and Nonlinear Control, 2024, v. 34, n. 5, p. 3297-3317 How to Cite?
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.


Persistent Identifierhttp://hdl.handle.net/10722/344317
ISSN
2023 Impact Factor: 3.2
2023 SCImago Journal Rankings: 1.459

 

DC FieldValueLanguage
dc.contributor.authorLi, Yuman-
dc.contributor.authorLin, Hong-
dc.contributor.authorZhao, Chang-
dc.contributor.authorLam, James-
dc.date.accessioned2024-07-24T13:50:42Z-
dc.date.available2024-07-24T13:50:42Z-
dc.date.issued2024-03-25-
dc.identifier.citationInternational Journal of Robust and Nonlinear Control, 2024, v. 34, n. 5, p. 3297-3317-
dc.identifier.issn1049-8923-
dc.identifier.urihttp://hdl.handle.net/10722/344317-
dc.description.abstract<p>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.<br></p>-
dc.languageeng-
dc.publisherWiley-
dc.relation.ispartofInternational Journal of Robust and Nonlinear Control-
dc.subjectapproximate optimal estimator-
dc.subjectcyber-physical systems-
dc.subjectdeception attacks-
dc.subjectdenial-of-service attacks-
dc.subjectoptimal estimator-
dc.subjectstability-
dc.titleCentralized approximate optimal estimation for cyber-physical systems under joint cyber-attacks-
dc.typeArticle-
dc.identifier.doi10.1002/rnc.7137-
dc.identifier.scopuseid_2-s2.0-85179669007-
dc.identifier.volume34-
dc.identifier.issue5-
dc.identifier.spage3297-
dc.identifier.epage3317-
dc.identifier.eissn1099-1239-
dc.identifier.issnl1049-8923-

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