PAMPAS:使用安全探针的隐私感知移动参与式传感

Dai Hai Ton That, I. S. Popa, K. Zeitouni, C. Borcea
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引用次数: 10

摘要

移动参与式传感可用于许多应用,如车辆交通监测、污染跟踪,甚至健康调查。然而,它的成功取决于找到一种能够查询大量用户的解决方案,既能保护用户的位置隐私,又能实时工作。本文提出了一种用于移动参与式感知中高效数据聚合的隐私感知移动分布式系统PAMPAS。在PAMPAS中,使用安全硬件增强的移动设备(称为安全探针(sp))执行分布式查询处理,同时防止用户访问其他用户的数据。支持的服务器基础设施(SSI)协调sp间的通信和在sp上执行的计算任务。PAMPAS确保SSI不能将sp报告的位置链接到用户身份,即使SSI有额外的背景信息。除了新颖的系统架构外,PAMPAS还提出了两种新的协议,用于敏感隐私的基于位置的聚合和自适应空间划分的sp,以有效地处理资源受限的sp。我们的实验结果和安全性分析表明,这些协议能够实时收集、汇总数据,并共享统计数据或派生模型,而不会泄露任何位置隐私。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PAMPAS: Privacy-Aware Mobile Participatory Sensing Using Secure Probes
Mobile participatory sensing could be used in many applications such as vehicular traffic monitoring, pollution tracking, or even health surveying. However, its success depends on finding a solution for querying large numbers of users which protects user location privacy and works in real-time. This paper presents PAMPAS, a privacy-aware mobile distributed system for efficient data aggregation in mobile participatory sensing. In PAMPAS, mobile devices enhanced with secure hardware, called secure probes (SPs), perform distributed query processing, while preventing users from accessing other users' data. A supporting server infrastructure (SSI) coordinates the inter-SP communication and the computation tasks executed on SPs. PAMPAS ensures that SSI cannot link the location reported by SPs to the user identities even if SSI has additional background information. In addition to its novel system architecture, PAMPAS also proposes two new protocols for privacy-aware location-based aggregation and adaptive spatial partitioning of SPs that work efficiently on resource-constrained SPs. Our experimental results and security analysis demonstrate that these protocols are able to collect the data, aggregate them, and share statistics or derived models in real-time, without any location privacy leakage.
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