Research on the Optimization Management of Cloud Privacy Strategy Based on Evolution Game. (11th August 2020)

• Record Type: Journal Article
• Authors: Sun, Pan Jun
• Other Names: Maglaras Leandros Academic Editor.
• Is Part Of: Security and communication networks. Volume 2020(2020)
• Publication Date: 2020-08-11
• Subjects: Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1155/2020/6515328
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract : 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.