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Linear System Identification-Oriented Optimal Tampering Attack Strategy and Implementation Based on Information Entropy with Multiple Binary Observations

Authors :
Zhongwei Bai
Peng Yu
Yan Liu
Jin Guo
Source :
Algorithms, Vol 17, Iss 6, p 239 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

With the rapid development of computer technology, communication technology, and control technology, cyber-physical systems (CPSs) have been widely used and developed. However, there are massive information interactions in CPSs, which lead to an increase in the amount of data transmitted over the network. The data communication, once attacked by the network, will seriously affect the security and stability of the system. In this paper, for the data tampering attack existing in the linear system with multiple binary observations, in the case where the estimation algorithm of the defender is unknown, the optimization index is constructed based on information entropy from the attacker’s point of view, and the problem is modeled. For the problem of the multi-parameter optimization with energy constraints, this paper uses particle swarm optimization (PSO) to obtain the optimal data tampering attack solution set, and gives the estimation method of unknown parameters in the case of unknown parameters. To implement the real-time improvement of online implementation, the BP neural network is designed. Finally, the validity of the conclusions is verified through numerical simulation. This means that the attacker can construct effective metrics based on information entropy without the knowledge of the defense’s discrimination algorithm. In addition, the optimal attack strategy implementation based on PSO and BP is also effective.

Details

Language :
English
ISSN :
19994893
Volume :
17
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Algorithms
Publication Type :
Academic Journal
Accession number :
edsdoj.32a9dc6455f14f1095dad3622e49b3a1
Document Type :
article
Full Text :
https://doi.org/10.3390/a17060239