A method for analyzing Stackelberg attack–defense game model in 5G by tCPSO

Abstract

The development of 5G brings convenience to people, but it also brings threats. It is particularly important to analyze attack–defense confrontation from a macro perspective. Network security of graph is an important research problem in current network environment. A Stackelberg game model based on 5G network graph is established to analyze the attack–defense confrontation in this paper. In order to solve the Nash equilibrium, a compact particle swarm optimization based on t-Location-Scale distribution (tCPSO) is proposed. The tCPSO uses less memory space and has better optimization performance. The experiments prove that tCPSO has better optimization performance than other heuristic algorithms on CEC2013. The clustering experiments further show that tCPSO has better optimization ability than other heuristic algorithms. The optimal defense strategies under different attack–defense resources are analyzed in this paper. It is concluded that increasing the successful defense rate is more effective for the defender to obtain greater profit than reducing the successful attack rate. Using intelligent computing to solve Nash equilibrium is a new idea for researchers to analyze attack–defense confrontation.