基于位置服务的细粒度隐私控制的系统级体系结构

A. Moro, B. Garbinato
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引用次数: 2

摘要

我们引入了一个系统级架构,在通过移动设备访问基于位置的服务的上下文中,提供对用户隐私的细粒度控制。与今天的大多数移动平台相比,用户对自己的隐私只有粗粒度的控制,要么接受无条件地传输他们的位置以使用一项服务,要么完全放弃这项服务。然而,并非所有基于位置的服务都要求相同级别的位置准确性和相同级别的隐私放弃。利用这种结构,用户可以在位置隐私和位置准确性之间进行权衡。为了实现这一点,我们的架构依赖于三个主要元素:扩展底层移动平台的可信模块,该模块与提供基于位置的服务的不可信应用程序之间的安全协议,以及捕获用户感兴趣的区域并以各种精度级别组织它们的树。不受信任的移动应用不再直接接收用户位置:受信任模块拦截它们来计算用户感兴趣的区域并创建树。然后,用户可以决定向何种应用程序公开何种级别的准确性。我们通过比较众所周知的模糊机制和我们的树,从保护隐私的角度来评估这种架构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A System-Level Architecture for Fine-Grained Privacy Control in Location-Based Services
We introduce a system-level architecture providing fine-grained control over user privacy, in the context of location-based services accessed via mobile devices. In contrast with most mobile platforms today, users only have coarse-grained control over their privacy, either accepting to unconditionally stream their locations in order to use a service, or renouncing the service altogether. However, not all location-based services do require the same level of location accuracy and the same level of privacy renouncement. With this architecture, the user can adapt the tradeoff between location privacy and location accuracy. To achieve this, our architecture relies on three main elements: a trusted module extending the underlying mobile platform, a secure protocol between that module and untrusted applications offering location-based services, and a tree capturing user's zones of interest and organizing them in various accuracy levels. Untrusted mobile applications no longer receive user locations directly: the trusted module intercepts them to compute user's zones of interest and create the tree. The user can then decide what level of accuracy will be disclosed to what application. We evaluate this architecture from a privacy preserving point of view by comparing well-known blurring mechanisms and our tree.
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