基于差分隐私的位置隐私保护和基于位置的服务质量权衡框架

Tianyi Feng, L. Wong, Sumei Sun, Yonghao Zhao, Zhixiang Zhang
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引用次数: 3

摘要

随着基于位置的服务的广泛使用和定位系统的发展,用户的位置甚至敏感信息很容易被一些不可信的实体获取,这意味着隐私问题需要引起重视。在本文中,我们提出了一个差分隐私框架来保护用户的位置隐私并提供基于位置的服务。我们提出了位置隐私、服务质量和差分隐私的度量,引入位置隐私保护机制,帮助用户找到位置隐私和服务质量之间的权衡或最优策略。此外,我们设计了一个对手模型来推断用户的真实位置,应用服务提供商可以使用该模型来提高服务质量。最后给出了仿真结果,并对系统的性能进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Location Privacy Preservation and Location-based Service Quality Tradeoff Framework Based on Differential Privacy
With the widespread use of location-based services and the development of localization systems, user’s locations and even sensitive information can be easily accessed by some untrusted entities, which means privacy concerns should be taken seriously. In this paper, we propose a differential privacy framework to preserve users’ location privacy and provide location-based services. We propose the metrics of location privacy, service quality and differential privacy to introduce a location privacy preserving mechanism, which can help users find the tradeoff or optimal strategy between location privacy and service quality. In addition, we design an adversary model to infer users’ true locations, which can be used by application service providers to improve service quality. Finally, we present simulation results and analyze the performance of our proposed system.
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