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User-Defined Privacy Grid System for Continuous Location-Based Services

机译:用户定义的隐私网格系统,用于基于位置的连续服务

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摘要

Location-based services (LBS) require users to continuously report their location to a potentially untrusted server to obtain services based on their location, which can expose them to privacy risks. Unfortunately, existing privacy-preserving techniques for LBS have several limitations, such as requiring a fully-trusted third party, offering limited privacy guarantees and incurring high communication overhead. In this paper, we propose a user-defined privacy grid system called (DGS); the first holistic system that fulfills four essential requirements for privacy-preserving and LBS. (1) The system only requires a semi-trusted third party, responsible for carrying out simple matching operations correctly. This semi-trusted third party does not have any information about a user’s location. (2) Secure snapshot and continuous location privacy is guaranteed under our defined adversary models. (3) The communication cost for the user does not depend on the user’s desired privacy level, it only depends on the number of relevant points of interest in the vicinity of the user. (4) Although we only focus on range and -nearest-neighbor queries in this work, our system can be easily extended to support other spatial queries without changing the algorithms run by the semi-trusted third party and the database server, provided the required search area of a spatial query can be abstracted into spatial regions. Experimental results show that our DGS is more efficient than the state-of-the-art privacy-preserving technique for continuous LBS.
机译:基于位置的服务(LBS)要求用户不断向可能不受信任的服务器报告其位置,以根据其位置获取服务,这可能会使他们面临隐私风险。不幸的是,现有的LBS隐私保护技术有几个局限性,例如要求完全信任的第三方,提供有限的隐私保证并导致高通信开销。在本文中,我们提出了一个用户定义的隐私网格系统,称为(DGS)。满足隐私保护和LBS四个基本要求的第一个整体系统。 (1)系统仅需要半受信任的第三方,负责正确执行简单的匹配操作。此半信任的第三方没有有关用户位置的任何信息。 (2)在我们定义的对手模型下,可以确保安全的快照和连续的位置隐私。 (3)用户的通讯成本不取决于用户所需的隐私级别,而仅取决于用户附近相关兴趣点的数量。 (4)尽管在此工作中我们仅关注范围和-最近邻查询,但是只要需要,我们的系统可以轻松扩展以支持其他空间查询,而无需更改半受信任的第三方和数据库服务器运行的算法。空间查询的搜索区域可以抽象为空间区域。实验结果表明,对于连续的LBS,我们的DGS比最新的隐私保护技术更有效。

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