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Structural analyses of a parsimonious watermarking policy for data deception attack detection in networked control systems
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Signals and Systems.ORCID iD: 0000-0002-7112-8269
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.ORCID iD: 0000-0001-5491-4068
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Signals and Systems.ORCID iD: 0000-0001-9066-5468
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Signals and Systems.ORCID iD: 0000-0003-0762-5743
2022 (English)In: 2022 IEEE 61st Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 7648-7655Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we perform structural analyses of a parsimonious watermarking policy, which minimizes the average detection delay (ADD) to detect data deception attacks on networked control systems (NCS) for a fixed upper bound on the false alarm rate (FAR). The addition of physical watermarking to the control input of a NCS increases the probability of attack detections with an increase in the control cost. Therefore, we formulate the problem of data deception attack detection for NCS with the facility to add physical watermarking as a stochastic optimal control problem. Then we solve the problem by applying dynamic programming value iterations and find a parsimonious watermarking policy that decides to add watermarking and detects attacks based on the estimated posterior probability of attack. We analyze the optimal policy structure and find that it can be a one, two or three threshold policy depending on a few parameter values. Simulation studies show that the optimal policy for a practical range of parameter values is a two-threshold policy on the posterior probability of attack. Derivation of a threshold-based policy from the structural analysis of the value iteration method reduces the computational complexity during the runtime implementation and offers better structural insights. Furthermore, such an analysis provides a guideline for selecting the parameter values to meet the design requirements.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022. p. 7648-7655
Series
IEEE Conference on Decision and Control, ISSN 0743-1546, E-ISSN 2576-2370
National Category
Control Engineering Telecommunications
Identifiers
URN: urn:nbn:se:uu:diva-501127DOI: 10.1109/CDC51059.2022.9993201ISI: 000948128106060ISBN: 978-1-6654-6761-2 (electronic)ISBN: 978-1-6654-6760-5 (electronic)ISBN: 978-1-6654-6762-9 (print)OAI: oai:DiVA.org:uu-501127DiVA, id: diva2:1754143
Conference
IEEE 61st Conference on Decision and Control (CDC), December 6-9, 2022, Cancun, MEXICO
Funder
Swedish Research Council, 2017-04053Swedish Research Council, 2018-04396Swedish Foundation for Strategic ResearchAvailable from: 2023-05-02 Created: 2023-05-02 Last updated: 2023-05-02Bibliographically approved

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Naha, ArunavaTeixeira, AndréAhlén, AndersDey, Subhrakanti

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