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논문검색

Game-Theoretic Strategy for Personalized Privacy Protection

초록

영어

With the development of cloud computing, more and more service providers deploy multi-tenant 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.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Personalized Privacy Protection Customized Framework
 4. Formulation of the Privacy Protection Strategy
  4.1. Redundancy Checking and Conflict Checking
  4.2. Privacy Protection Level
  4.3. The Privacy Protection Strategy Model
  4.4. The Existence Proof
  4.4. Solution of the Equilibrium Point
 5. Experiments
  5.1. Test on the Impact that the Amount of Tenants’ Data has on Storage Servers
  5.2. Analysis of Privacy Protection Strategy
 6. Summarize
 Acknowledgements
 References

저자정보

  • Chao Yu School of Computer Science and Technology, Shandong University, Jinan, China
  • Yuliang Shi School of Computer Science and Technology, Shandong University, Jinan, China

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