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A methodology for honeypot attack-defense strategy selection based on four-party evolutionary game

adaptive-and-self-organizing-systems
agents-and-multi-agent-systems
computer-networks-and-communications
optimization-theory-and-computation
security-and-privacy

Abstract

The traditional network attack-defense confrontation only considers the two parties of attack and defense, ignoring the intervention of users themselves and regulators. Aiming at the problem of defense strategy selection in network attack-defense confrontation, combined with the evolutionary game model, a four-party game model of attackers, defenders, users, and regulators is constructed. The replication dynamic equation is used to carry out the evolutionary stability analysis of the behavior strategy selection of each subject, the Lyapunov first law is used to analyze the stability of each equilibrium point of the game model, and the MATLAB is used to carry out the simulation experiment on the analysis results, to discuss the influence of each variable on the behavior strategy selection of the four-party subjects and verify the accuracy and applicability of the model. The results show that the model can reach the evolutionary stable state and obtain the optimal defense strategy in different situations, which can provide theoretical support for solving the problem of network information security.
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