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文章基本信息

  • 标题:Game-Theoretic Strategy for Personalized Privacy Protection
  • 本地全文:下载
  • 作者:Chao Yu ; Yuliang Shi
  • 期刊名称:International Journal of Grid and Distributed Computing
  • 印刷版ISSN:2005-4262
  • 出版年度:2014
  • 卷号:7
  • 期号:4
  • 页码:123-138
  • DOI:10.14257/ijgdc.2014.7.4.12
  • 出版社:SERSC
  • 摘要: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.
  • 关键词:multi-tenant; Software as a Service (SaaS); Nash equilibrium; privacy ; protection
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