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Research on the Optimization Management of Cloud Privacy Strategy Based on Evolution Game
Security and Communication Networks Pub Date : 2020-08-11 , DOI: 10.1155/2020/6515328
Pan Jun Sun 1
Affiliation  

Cloud computing services have great convenience, but privacy security is a big obstacle of popularity. In the process result of privacy protection of cloud computing, it is difficult to choose the optimal strategy. In order to solve this problem, we propose a quantitative weight model of privacy information, use evolutionary game theory to establish a game model of attack protection, design the optimal protection strategy selection algorithm, and make the evolutionary stable equilibrium solution method from the limited rational constraint. In order to study the strategic dependence of the same game group, the classical dynamic replication equation is improved by using the incentive coefficient, an improved evolutionary game model of attack protection is constructed, the stability of equilibrium point is further analyzed by Jacobian matrix method, and the optimal selection strategy is obtained under different conditions. Finally, the correctness and validity of the model are verified by experiments, different strategies of the same group have the dual effects of promotion and inhibition, and the advantages of this paper are shown by comparing with other articles.

中文翻译:

基于演化博弈的云隐私策略优化管理研究

云计算服务具有极大的便利性,但是隐私安全性是普及的一大障碍。在云计算隐私保护的过程结果中,难以选择最佳策略。为了解决这个问题,我们提出了一种定量的隐私信息权重模型,运用进化博弈理论建立了攻击防护的博弈模型,设计了最优的保护策略选择算法,并从有限理性出发制定了演化稳定均衡解法。约束。为了研究同一个博弈群体的战略依存关系,利用激励系数对经典动态复制方程进行了改进,构造了改进的攻击防护进化博弈模型,并利用雅可比矩阵法进一步分析了平衡点的稳定性,在不同条件下获得了最优的选择策略。最后,通过实验验证了模型的正确性和有效性,同一组的不同策略具有促进和抑制的双重作用,并与其他文章进行了比较,证明了本文的优势。
更新日期:2020-08-11
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