Preserving Location Privacy in Geosocial Applications
Preserving Location Privacy in Geosocial Applications
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DOI：
10.1109/tmc.2012.247
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发表时间：
2014-01-01
影响因子：
7.9
通讯作者：
Zhao, Ben Y.
中科院分区：
文献类型：
--
作者：
Puttaswamy, Krishna P. N.;Wang, Shiyuan;Zhao, Ben Y.
使用 FourSquare 等地理社交应用程序，数百万人通过朋友和推荐与周围环境进行互动。然而，如果没有足够的隐私保护，这些系统很容易被滥用，例如跟踪用户或以他们为目标进行入室盗窃。在本文中，我们介绍了 LocX，这是一种新颖的替代方案，它可以显着改善位置隐私，而不会增加查询结果的不确定性或依赖于对服务器安全性的强烈假设。我们的主要见解是将安全的用户特定的、保持距离的坐标转换应用于与服务器共享的所有位置数据。用户的朋友共享该用户的秘密，以便他们可以应用相同的转换。这允许服务器正确评估所有位置查询，但我们的隐私机制保证服务器无法从转换后的数据或数据访问中查看或推断实际位置数据。我们证明，即使面对强大的对手模型，LocX 也能提供隐私，并且我们使用原型测量来表明，它以很少的性能开销提供隐私，使其适合当今的移动设备。
Using geosocial applications, such as FourSquare, millions of people interact with their surroundings through their friends and their recommendations. Without adequate privacy protection, however, these systems can be easily misused, for example, to track users or target them for home invasion. In this paper, we introduce LocX, a novel alternative that provides significantly improved location privacy without adding uncertainty into query results or relying on strong assumptions about server security. Our key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. The friends of a user share this user's secrets so they can apply the same transformation. This allows all location queries to be evaluated correctly by the server, but our privacy mechanisms guarantee that servers are unable to see or infer the actual location data from the transformed data or from the data access. We show that LocX provides privacy even against a powerful adversary model, and we use prototype measurements to show that it provides privacy with very little performance overhead, making it suitable for today's mobile devices.