Game-Theoretic Strategy for Personalized Privacy Protection

With the development of cloud computing, more and more service providers deploy multitenant applications to the cloud. Multi-tenant data is stored by non-fully trusted SaaS service providers, and the protection of data privacy attracts more attention. This paper proposes a privacy protection strategy customization framework. This framework considers the privacy protection needs, SaaS application performance, the interests of both tenants and SaaS service providers, and analyzes the whole privacy protection strategy formulation process based on the Nash equilibrium, then establishes the game model of privacy protection, finally obtains the privacy protection strategy by analyzing of the game model. The experiments show that the privacy protection game model has better feasibility and effectiveness.