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Causality Countermeasures for Anomaly Detection in Cyber-Physical Systems
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
2018 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 2, p. 386-401Article in journal (Refereed) Published
Abstract [en]

The problem of attack detection in cyber-physical systems is considered in this paper. Transferentropy-based causality countermeasures are introduced for both sensor measurements and innovation sequences, which can be evaluated in a data-driven fashion without relying on a model of the underlying dynamic system. The relationships between the countermeasures and the system parameters as well as the noise statistics are investigated, based on which conditions that guarantee the time convergence of the countermeasures are obtained. The effectiveness of the transfer entropy countermeasures in attack detection is evaluated via theoretical analysis, numerical demonstrations, as well as comparative simulations with classical chi(2) detectors. Four types of attacks are considered: denial-of-service, replay, innovation-based deception, and data injection attacks. Abnormal behavior of the transfer entropy can be observed after the occurrence of each of these attacks.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. Vol. 63, no 2, p. 386-401
Keywords [en]
Anomaly detection, causality countermeasures, cyber-physical systems, transfer entropy
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-223519DOI: 10.1109/TAC.2017.2714646ISI: 000423553000006Scopus ID: 2-s2.0-85021740831OAI: oai:DiVA.org:kth-223519DiVA, id: diva2:1184749
Funder
Swedish Research CouncilSwedish Foundation for Strategic Research Knut and Alice Wallenberg Foundation
Note

QC 20180222

Available from: 2018-02-22 Created: 2018-02-22 Last updated: 2018-02-22Bibliographically approved

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