连续位置痕迹隐私的聚类地理不可分辨性

Mariana Cunha, Ricardo Mendes, J. Vilela
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引用次数: 9

摘要

我们考虑了可以通过时间/空间关联来估计用户真实位置的模糊位置报告的隐私性。我们提出了一种以用户为中心的位置隐私保护机制(LPPM),它不仅保护用户不受单一报告的影响,而且随着时间的推移,保护用户不受连续报告的影响。我们提出的机制,指定聚类地理不可区分性,创建混淆集群,将附近的位置聚集到一个单一的混淆位置。为了评估该机制的效用,我们采用了一个基于地理围栏的真实用例。我们的评估结果显示了所提出的聚类地理不可区分机制的适当的隐私-效用权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clustering Geo-Indistinguishability for Privacy of Continuous Location Traces
We consider privacy of obfuscated location reports that can be correlated through time/space to estimate the real position of a user. We propose a user-centric Location Privacy-Preserving Mechanism (LPPM) that protects users not only against single reports, but also over time, against continuous reports. Our proposed mechanism, designated clustering geo-indistinguishability, creates obfuscation clusters to aggregate nearby locations into a single obfuscated location. To evaluate the utility of the mechanism, we resorted to a real use-case based on geofencing. Our evaluation results have shown a suitable privacy-utility trade-off for the proposed clustering geo-indistinguishability mechanism.
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