Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/30950
Title: Secure Recursive State Estimation of Networked Systems Against Eavesdropping: A Partial-Encryption-Decryption Method
Authors: Zou, L
Wang, Z
Shen, B
Dong, H
Keywords: eavesdropping;encryption-decryption scheme;minimum mean squared error;recursive state estimation;ultimate boundedness analysis
Issue Date: 9-Dec-2024
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Zou, L. et al. (2024) 'Secure Recursive State Estimation of Networked Systems Against Eavesdropping: A Partial-Encryption-Decryption Method', IEEE Transactions on Automatic Control, 0 (early access), pp. 1 - 14. doi: 10.1109/TAC.2024.3512413.
Abstract: This paper addresses the problem of secure recursive state estimation for a networked linear system, which may be vulnerable to interception of transmitted measurement data by eavesdroppers. To effectively protect information security, an encryption-decryption-based communication scheme can be used, but encrypting all the measurement data from sensors can result in significant computational costs. To address this issue, a partial-encryption-decryption (PED) mechanism is proposed to enhance information security with relatively low computational costs. In this mechanism, only part of the transmitted measurement signals are encrypted, and the remaining signals are transmitted directly to the estimator. A Jordan-canonical-form-based approach is developed to select the appropriate parameter for the PED mechanism, and recursive formulas for the state estimator are designed based on the principle of minimum mean squared error. Sufficient conditions are derived to guarantee the ultimate boundedness of the estimation error variance matrix. Finally, the proposed PED-based recursive state estimation scheme is evaluated through two simulation examples to demonstrate its effectiveness.
URI: https://bura.brunel.ac.uk/handle/2438/30950
DOI: https://doi.org/10.1109/TAC.2024.3512413
ISSN: 0018-9286
Other Identifiers: ORCiD: Lei Zou https://orcid.org/0000-0002-0409-7941
ORCiD: Zidong Wang https://orcid.org/0000-0002-9576-7401
ORCiD: Bo Shen https://orcid.org/0000-0003-3482-5783
ORCiD: Hongli Dong https://orcid.org/0000-0001-8531-6757
Appears in Collections:Dept of Computer Science Research Papers

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