Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26612
Title: Encrypted Finite-Horizon Energy-to-Peak State Estimation for Time-Varying Systems Under Eavesdropping Attacks: Tackling Secrecy Capacity
Authors: Zou, L
Wang, Z
Shen, B
Dong, H
Lu, G
Keywords: eavesdropping;encryption-decryption scheme;energy-to-peak state estimation;artificial-noise-assisted technique;finite-horizon state estimation
Issue Date: 28-Mar-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Zou, L. et al. (2023) 'Encrypted Finite-Horizon Energy-to-Peak State Estimation for Time-Varying Systems Under Eavesdropping Attacks: Tackling Secrecy Capacity', IEEE/CAA Journal of Automatica Sinica, 10 (4), pp. 985 - 996. doi: 10.1109/JAS.2023.123393.
Abstract: This paper is concerned with the problem of finite-horizon energy-to-peak state estimation for a class of networked linear time-varying systems. Due to the inherent vulnerability of network-based communication, the measurement signals transmitted over a communication network might be intercepted by potential eavesdroppers. To avoid information leakage, by resorting to an artificial-noise-assisted method, we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term. A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption scheme. The purpose of the addressed problem is to design an encryption-decryption scheme and a state estimator such that: 1) the desired secrecy capacity is ensured; and 2) the required finite-horizon $l_{2}-l_{\infty}$ performance is achieved. Sufficient conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state estimator. Finally, simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme.
URI: https://bura.brunel.ac.uk/handle/2438/26612
DOI: https://doi.org/10.1109/JAS.2023.123393
ISSN: 2329-9266
Other Identifiers: ORCID iDs: Lei Zou 0000-0002-0409-7941; Zidong Wang https://orcid.org/0000-0002-9576-7401.
Appears in Collections:Dept of Computer Science Research Papers

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