基于演化博弈的社交网络隐私保护研究

Research on Privacy Protection for Social Network Based on Evolution Game Theory

[目的/意义]针对当前社交网络隐私保护机制的局限性,研究用户与社交平台双方的隐私行为策略选择问题对于维护网络安全具有重要的现实意义。[方法/过程]基于有限理性的假设,构建了用户与社交平台的隐私博弈模型。利用微分方程稳定性原理求解演化稳定策略,并定量描述了保持系统稳定发展的条件。在此基础上,运用M atlab对不同参数下的演化稳定策略进行数值仿真。[结果 /结论]仿真分析结果表明,用户信任度、社交平台影响力和奖励、第三方监管力度是影响用户和社交平台隐私策略演化的关键因素,并提出隐私保护过度和保护不足的判定标准以及两种情况下相应的社交网络隐私保护对策和建议。

[ Purpose/Significance ] Aiming to solve the limitation of privacy protection of social network, the research on privacy behav- ior strategies of social network platforms and individuals has important practice significance to protect network security. [Method/Process] According to the limited reasonable assumption of game agents, an evolutionary game model of privacy behavior is constructed. The evo- lutionary stable strategies were found by utilizing the stability theory of differential equations. Based on the quantitative analysis of stable e- volution, the strategies were simulated by Matlab with different values of system parameters. [ Resnit/Conelusion] The results show that trust of individuals, influence and incentive of social platforms and government supervision are the critical factors which can affect the evo- lutionary stable strategies of privacy behavior. Then a judgment method is proposed of over protection and limited protection, and several and suggestions are illustrated respectively in these two Cases .