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Secure State Estimation with Asynchronous Measurements against Malicious Measurement-data and Time-stamp Manipulation
Tsinghua University.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.ORCID iD: 0000-0001-9316-233X
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
Tsinghua University.
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2023 (English)In: 2023 62nd IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 7073-7080Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a secure state estimation scheme with non-periodic asynchronous measurements for linear continuous-time systems under false data attacks on the measurement transmit channel. After sampling the output of the system, a sensor transmits the measurement information in a triple composed of sensor index, time-stamp, and measurement value to the fusion center via vulnerable communication channels. The malicious attacker can corrupt a subset of the sensors through (i) manipulating the time-stamp and measurement value; (ii) blocking transmitted measurement triples; or (iii) injecting fake measurement triples. To deal with such attacks, we propose the design of local estimators based on observability space decomposition, where each local estimator updates the local state and sends it to the fusion center after sampling a measurement. Whenever there is a local update, the fusion center combines all the local states and generates a secure state estimate by adopting the median operator. We prove that local estimators of benign sensors are unbiased with stable covariance. Moreover, the fused central estimation error has bounded expectation and covariance against at most p corrupted sensors as long as the system is 2p-sparse observable. The efficacy of the proposed scheme is demonstrated through an application on a benchmark example of the IEEE 14-bus system.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023. p. 7073-7080
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:uu:diva-518889DOI: 10.1109/CDC49753.2023.10383571ISI: 001166433805126ISBN: 979-8-3503-0124-3 (print)ISBN: 979-8-3503-0125-0 (electronic)OAI: oai:DiVA.org:uu-518889DiVA, id: diva2:1822817
Conference
62nd IEEE Conference on Decision and Control (CDC), DEC 13-15, 2023, Singapore, SINGAPORE
Funder
Swedish Research Council, 2018-04396Swedish Research Council, 2021-06316Swedish Foundation for Strategic ResearchAvailable from: 2023-12-28 Created: 2023-12-28 Last updated: 2024-03-22Bibliographically approved

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Nguyen, Anh TungTeixeira, André

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