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Title: | Secure Particle Filtering With Paillier Encryption-Decryption Scheme: Application to Multi-machine Power Grids |
Authors: | Qu, B Wang, Z Shen, B Dong, H |
Keywords: | particle filter;encryption-decryption scheme;nonlinear/non-Gaussian systems;secure state estimation;power grids |
Issue Date: | 1-May-2023 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Citation: | Qu, B. et al. (2023) 'Secure Particle Filtering With Paillier Encryption-Decryption Scheme: Application to Multi-machine Power Grids', IEEE Transactions on Smart Grid, 15 (1), pp. 863 - 873. doi: 10.1109/TSG.2023.3271949. |
Abstract: | This paper is concerned with the encryption-decryption-based state estimation problem for a class of multi-machine power grids with non-Gaussian noises. For the purposes of security enhancement and data privacy protection, the Paillier encryption-decryption scheme is adopted to map the measurement data into the ciphertext space before being transmitted through the communication network. The aim of this paper is to develop a novel secure particle filter algorithm to cope with the nonlinearity/non-Gaussianity from the system plant and the decrypted signals after the measurement transmission. In particular, a modified likelihood function is proposed to obtain the importance weights where the encryption-decryption process of the measurement data is taken into full consideration. The developed algorithm is applied to multi-machine power grids, and it is demonstrated via simulation studies (on three test scenarios of the IEEE 39-bus power system) that our proposed secure state estimation scheme possesses the desired performance index in terms of security and accuracy. |
Description: | This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI10.1109/TSG.2023.3271949, IEEE Transactions on Smart Grid. |
URI: | https://bura.brunel.ac.uk/handle/2438/26989 |
DOI: | https://doi.org/10.1109/TSG.2023.3271949 |
ISSN: | 1949-3053 |
Other Identifiers: | ORCiD: Bogang Qu https://orcid.org/0000-0001-8237-7191 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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