Privacy protection among three antithetic-parties for context-aware services
Privacy protection among three antithetic-parties for context-aware services
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DOI：
10.1016/j.jnca.2021.103115
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发表时间：
2021-10
期刊：
影响因子：
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通讯作者：
Yan Huang;Wei Li;Jinbao Wang;Zhipeng Cai;A. Bourgeois
中科院分区：
文献类型：
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作者：
Yan Huang;Wei Li;Jinbao Wang;Zhipeng Cai;A. Bourgeois
情境感知服务的普及提高了人们的生活质量，同时也带来了严重的隐私问题。为了使用户接收到高质量的服务，他们面临着可能正在窃听数据的对手和/或不受信任的服务平台将其数据出售给对手而泄露私人信息的风险。博弈论已被用作一个强大的工具，以实现隐私保护的战略平衡之间的权衡利润（服务）和成本（数据泄漏）的用户。然而，大多数现有的方案不能充分利用博弈论的力量，因为它们无法描述任何两个（三个）参与方之间的相互关系：用户，平台和对手。现有的方案也不总是能够为用户提供具体的指导，以减少来自平台和对手的联合威胁的影响。在本文中，我们设计了一个隐私保护游戏来量化三方的关注点，并捕捉其中任何两个之间的互动。我们还在细粒度级别为每一方确定最佳策略，即特定设置，而不仅仅是二元选择。我们通过理论分析和实验验证了我们提出的游戏模型的性能。
The popularity of context-aware services is improving the quality of life, while raising serious privacy issues. In order for users to receive quality service, they are at risk of leaking private information by adversaries that are possibly eavesdropping on the data and/or by the untrusted service platform selling off its data to adversaries. Game theory has been utilized as a powerful tool to achieve privacy preservation by strategically balancing the trade-off between profit (service) and cost (data leakage) for the user. However, most of the existing schemes cannot fully exploit the power of game theory, as they fail to depict the mutual relationship between any two (of the three) parties involved: user, platform, and adversary. Existing schemes are also not always able to provide specific guidance for a user to reduce the impact of the joint threats from the platform and adversary. In this paper, we design a privacy-preserving game to quantify the three parties’ concerns and capture interactions between any two of them. We also identify the best strategy for each party at a fine-grained level, i.e. specific settings, not simply binary choices. We validate the performance of our proposed game model through both a theoretical analysis and experiments.