Secure State Estimation for Artificial Neural Networks With Unknown-But-Bounded Noises: A Homomorphic Encryption Scheme

This article is concerned with the secure state estimation problem for artificial neural networks (ANNs) subject to unknown-but-bounded noises, where sensors and the remote estimator are connected via open and bandwidth-limited communication networks. Using the encoding-decoding mechanism (EDM) and...

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Vydané v:IEEE transaction on neural networks and learning systems Ročník 36; číslo 4; s. 6780 - 6791
Hlavní autori: Zhu, Kaiqun, Wang, Zidong, Ding, Derui, Dong, Hongli, Xu, Cheng-Zhong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.04.2025
Predmet:
Artificial neural networks
Artificial neural networks (ANNs)
Bandwidth
bandwidth constraints
Cryptography
Encryption
homomorphic encryption scheme (HES)
Noise
secure state estimation
Security
set-membership state estimation
State estimation
ISSN:2162-237X, 2162-2388, 2162-2388
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Shrnutí:This article is concerned with the secure state estimation problem for artificial neural networks (ANNs) subject to unknown-but-bounded noises, where sensors and the remote estimator are connected via open and bandwidth-limited communication networks. Using the encoding-decoding mechanism (EDM) and the Paillier encryption technique, a novel homomorphic encryption scheme (HES) is introduced, which aims to ensure the secure transmission of measurement information within communication networks that are constrained by bandwidth. Under this encoding-decoding-based HES, the data being transmitted can be encrypted into ciphertexts comprising finite bits. The emphasis of this research is placed on the development of a secure set-membership state estimation algorithm, which allows for the computation of estimates using encrypted data without the need for decryption, thereby ensuring data security throughout the entire estimation process. Taking into account the unknown-but-bounded noises, the underlying ANN, and the adopted HES, sufficient conditions are determined for the existence of the desired ellipsoidal set. The related secure state estimator gains are then derived by addressing optimization problems using the Lagrange multiplier method. Lastly, an example is presented to verify the effectiveness of the proposed secure state estimation approach.
Bibliografia:ObjectType-Article-1
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content type line 23
ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2024.3389873