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Prive: Anonymous Location-Based Queries in Distributed Mobile Systems

机译:Prive:分布式移动系统中基于匿名位置的查询

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Nowadays, mobile users with global positioning devices can access Location Based Services (LBS) and query about points of interest in their proximity. For such applications to succeed, privacy and confidentiality are essential. Encryption alone is not adequate; although it safeguards the system against eavesdroppers, the queries themselves may disclose the location and identity of the user. Recently, there have been proposed centralized architectures based on K-anonymi-ty, which utilize an intermediate anonymizer between the mobile users and the LBS. However, the anonymizer must be updated continuously with the current locations of all users. Moreover, the complete knowledge of the entire system poses a security threat., if the anonymizer is compromised.rnIn this paper we address two issues: (i) We show that existing approaches may fail to provide spatial anonymity for some distributions of user locations and describe a novel technique which solves this problem, (ii) We propose Prive, a decentralized architecture for preserving the anonymity of users issuing spatial queries to LBS. Mobile users self-organize into an overlay network with good fault tolerance and load balancing properties. Prive avoids the bottleneck caused by centralized techniques both in terms of anonymi-zation and location updates. Moreover, the system state is distributed in numerous users, rendering Prive resilient, to attacks. Extensive experimental studies suggest that Prive is applicable to real-life scenarios with large populations of mobile users.
机译:如今,具有全球定位设备的移动用户可以访问基于位置的服务(LBS)并查询附近的兴趣点。为了使此类应用程序成功,隐私和机密至关重要。仅加密是不够的。尽管它可以保护系统免受窃听,但查询本身可能会泄露用户的位置和身份。最近,已经提出了一种基于K-匿名的集中式架构,该架构利用了移动用户和LBS之间的中间匿名器。但是,匿名程序必须使用所有用户的当前位置连续更新。此外,如果匿名器受到威胁,则整个系统的完整知识也会构成安全威胁。在本文中,我们解决了两个问题:(i)我们表明现有方法可能无法为用户位置的某些分布提供空间匿名性,并且(ii)我们提出了Prive,一种分散式架构,用于保留向LBS发出空间查询的用户的匿名性。移动用户可以自组织成具有良好容错能力和负载平衡属性的覆盖网络。 Prive避免了匿名化和位置更新方面的集中化技术所造成的瓶颈。此外,系统状态分布在众多用户中,使Prive具有抵御攻击的能力。大量的实验研究表明Prive适用于大量移动用户的现实生活场景。

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