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Defense strategy selection based on incomplete information game for the false data injection attack.

Defense strategy selection based on incomplete information game for the false data injection attack.

Authors :
Yi, Na
Xu, Jianjun
Source :
International Journal of Systems Science; Oct2024, Vol. 55 Issue 14, p2897-2913, 17p
Publication Year :
2024

Abstract

With the rapid development and wide application of sensing devices and communication networks, the traditional power system has transformed into a cyber physical power system (CPPS) gradually. The constant interaction of information flow and power flow exposes the grid to potential cyber-attack risks. In this paper, the defense strategy selection approaches are proposed based on incomplete information game against false data injection attack (FDIA) in different scenarios. Firstly, the attack-defense tree model containing economic indicators and a measure of attack is established, and the expected revenues of both attacker and defender are calculated in detail. Secondly, the static Bayesian attack-defense game model in which the defender grasps incomplete information is constructed, considering two cases of low-tech attacker and high-tech attacker. Then, the zero-sum attack-defense game model in which the attacker masters incomplete information is structured, considering the changing attack space. Finally, the simulations are carried out on the IEEE 30-bus system, and the optimal defense strategies in the case of two incomplete information are obtained by solving the equilibrium point. The simulation results demonstrate that the proposed method is effective in cyber security defense system, and can provide guiding ideology and theoretical basis for operators to deploy defense measures. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00207721
Volume :
55
Issue :
14
Database :
Complementary Index
Journal :
International Journal of Systems Science
Publication Type :
Academic Journal
Accession number :
179483174
Full Text :
https://doi.org/10.1080/00207721.2024.2363546