Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/32451
Title: Anti-eavesdropping set-membership state estimation for networked systems: An encryption–decryption scheme
Authors: Zou, L
Wang, Z
Shen, B
Dong, H
Keywords: eavesdropping;encryption–decryption scheme;set-membership state estimation;artificial-noise-assisted technique;ultimate boundedness analysis
Issue Date: 14-Oct-2025
Publisher: Elsevier
Citation: Zou, L. et al. (2026) 'Anti-eavesdropping set-membership state estimation for networked systems: An encryption–decryption scheme', Automatica, 183, 112652, pp. 1 - 12. doi: 10.1016/j.automatica.2025.112652.
Abstract: In this paper, the secure set-membership state estimation problem is investigated for a class of networked linear systems, where the measurement data might be intercepted by potential eavesdroppers. To protect the privacy of system state from information leakage, an artificial-noise-assisted encryptor is dedicatedly designed to transform the measurement data into the ciphertext (i.e., the encrypted data) before being transmitted, and a decryptor is then employed at the state estimator side to decrypt the received ciphertext. Under the proposed encryption–decryption mechanism, the concept of secrecy capacity is introduced to quantify the information security of the signal transmission process. A parameter-dependent state estimator is constructed to confine the estimation error into a time-varying ellipsoidal set. The desired parameters for the state estimator and the encryptor are co-designed by resorting to a set of recursions. Furthermore, sufficient conditions are derived to guarantee the ultimate boundedness of the time-varying ellipsoidal set. Finally, two simulation examples are provided to demonstrate the effectiveness of our developed secure set-membership state estimation scheme.
Description: The material in this paper was not presented at any conference.
URI: https://bura.brunel.ac.uk/handle/2438/32451
DOI: https://doi.org/10.1016/j.automatica.2025.112652
ISSN: 0005-1098
Other Identifiers: ORCiD: Lei Zou https://orcid.org/0000-0002-0409-7941
ORCiD: Zidong Wang https://orcid.org/0000-0002-9576-7401
ORCiD: Hongli Dong https://orcid.org/0000-0001-8531-6757
Article number: 112652
Appears in Collections:Dept of Computer Science Embargoed Research Papers

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