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Switching Control for Identification Deception in Cyber-Physical Systems
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-9612-8903
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-5983-0875
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0003-1835-2963
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-9940-5929
2024 (English)In: 2024 IEEE 63rd Conference on Decision and Control, CDC 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024, p. 809-814Conference paper, Published paper (Refereed)
Abstract [en]

We investigate the problem of deceiving a malicious agent employing an identification method to estimate the closed-loop dynamics of a cyber-physical system. In particular, we propose a moving target defense mechanism that utilizes stochastic switching between linear closed-loop dynamics to drive a linear system identification process of a potential adversary to sub-optimal solutions with non-vanishing error. We provide a statistical analysis of the induced identification error and show that it is not possible for any linear system identification method to reconstruct the average dynamics of a stochastic switched linear system. Finally, we utilize the theory of Markov jump linear systems to guarantee asymptotic stability of the switching system, and formulate the switching control problem as an optimization problem that guarantees stability while taking into account the trade-off between security and switching effort. Simulation results showcase the efficacy of the proposed approach in inducing identification error for the adversary using minimal switching.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. p. 809-814
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-361741DOI: 10.1109/CDC56724.2024.10886412Scopus ID: 2-s2.0-86000543445OAI: oai:DiVA.org:kth-361741DiVA, id: diva2:1948008
Conference
63rd IEEE Conference on Decision and Control, CDC 2024, Milan, Italy, Dec 16 2024 - Dec 19 2024
Note

Part of ISBN 9798350316339

QC 20250331

Available from: 2025-03-27 Created: 2025-03-27 Last updated: 2025-03-31Bibliographically approved

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Mavridis, Christos N.Kanellopoulos, ArisSandberg, HenrikJohansson, Karl H.

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