Privacy-Preserving Data Collection in Context-Aware Applications

Wei Li, Chun-qiang Hu, Tianyi Song, Jiguo Yu, Xiaoshuang Xing, Zhipeng Cai
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引用次数: 3

Abstract

Thanks to the development and popularity of context-aware applications, the quality of users' life has been improved through a wide variety of customized services. Meanwhile, users are suffering severe risk of privacy leakage and their privacy concerns are growing over time. To tackle the contradiction between the serious privacy issues and the growing privacy concerns in context-aware applications, in this paper, we propose a privacy-preserving data collection scheme by incorporating the complicated interactions among user, attacker, and service provider into a three-antithetic-party game. Under such a novel game model, we identify and rigorously prove the best strategies of the three parties and the equilibriums of the games. Furthermore, we evaluate the performance of our proposed data collection game by performing extensive numerical experiments, confirming that the user's data privacy can be effective preserved.
上下文感知应用中保护隐私的数据收集
由于上下文感知应用程序的开发和普及,用户的生活质量通过各种定制服务得到了改善。与此同时,用户面临着严重的隐私泄露风险,他们对隐私的担忧也在与日俱增。为了解决上下文感知应用中严重的隐私问题与日益增长的隐私关注之间的矛盾,本文提出了一种将用户、攻击者和服务提供商之间复杂的交互纳入三方博弈的隐私保护数据收集方案。在这种新颖的博弈模型下,我们识别并严格证明了三方的最佳策略和博弈的均衡。此外,我们通过进行广泛的数值实验来评估我们提出的数据收集游戏的性能,确认可以有效地保护用户的数据隐私。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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