隐藏敏感模式以保护LBS应用程序的位置隐私

Feng-Yuan Tai, Jian-Kai Song, Yi-Chen Tsai, Hsiao-Ping Tsai
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引用次数: 2

摘要

为了在使用LBS时保护隐私,我们提出了一种基于模式的隐身系统,该系统包含一个可信的隐私保护服务器来计算每个敏感模式的隐身区域。为了防止对手用一些简单的线索剔除一些模式,我们将模式安全斗篷(PSC)区域定义为一个矩形区域,该区域至少包含其他l-1个合理和不相似的模式。为了方便在最小PSC区域搜索敏感模式,我们使用r树来存储空间分布的不敏感模式。我们的初步研究结果表明,虽然发现的最优PSC区域的平均面积小于首次发现的PSC区域,但寻找最优PSC区域的成本要高得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloaking sensitive patterns Td preserve location privacy for LBS applications
To protect privacy while using LBS, we propose a pattern-based cloaking system that incorporate a trusted privacy preserving server to compute the cloak region for each sensitive patterns. To prevent adversaries culling out some patterns with some simple clues, we define a pattern-safe-cloak (PSC) region as a rectangle area that contains at least other l-1 reasonable and dissimilar patterns. To facilitate the search of a minimal PSC region for sensitive patterns, we use an R-tree to store the spatially distributed insensitive patterns. Our initial study results show that although the average area of the optimal PSC regions discovered is smaller than that of the first discovered PSC regions, the cost of finding optimal PSC region is much higher.
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