The optimal privacy strategy of cloud service based on evolutionary game

摘要

Cloud service has great convenience, because of its complex structure and dynamic nature, it is difficult to choose the best cost-effective strategy in the process of security and privacy information. To solve this problem, we construct a quantitative benefit of game strategy, use evolutionary game theory to build a game model of attack protection, propose the optimal protection strategy selection algorithm, and make the stable equilibrium solution based on limited rational constraints. Because of the inter dependency among the strategies in the same game group, we use the incentive coefficient to improve the classical dynamic replication equation, establish an improved attack protection evolutionary game model, further discuss and analyze the stability of the equilibrium point based on Jacobian matrix method, and give the optimal selection strategy under different conditions. Finally, we show the correctness, credibility, and effectiveness of the model through experiments; different strategies of the same group have the dual effects of promotion and inhibition, and show the characteristics and advantages of this paper by comparing with other literatures.