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Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings

机译:使用固定传感器读数的草图来保护隐私的移动性

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Two fundamental tasks of mobility modeling are (1) to track the number of distinct persons that are present at a location of interest and (2) to reconstruct flows of persons between two or more different locations. Stationary sensors, such as Bluetooth scanners, have been applied to both tasks with remarkable success. However, this approach has privacy problems. For instance, Bluetooth scanners store the MAC address of a device that can in principle be linked to a single person. Unique hashing of the address only partially solves the problem because such a pseudonym is still vulnerable to various linking attacks. In this paper we propose a solution to both tasks using an extension of linear counting sketches. The idea is to map several individuals to the same position in a sketch, while at the same time the inaccuracies introduced by this overloading are compensated by using several independent sketches. This idea provides, for the first time, a general set of primitives for privacy preserving mobility modeling from Bluetooth and similar address-based devices.
机译:移动性建模的两个基本任务是(1)跟踪感兴趣的位置上存在的不同人员的数量,以及(2)重构两个或多个不同位置之间的人员流。固定传感器(例如蓝牙扫描仪)已成功应用于这两项任务。但是,这种方法存在隐私问题。例如,蓝牙扫描仪存储设备的MAC地址,该MAC地址原则上可以链接到一个人。地址的唯一哈希处理只能部分解决该问题,因为这样的笔名仍然容易受到各种链接攻击的攻击。在本文中,我们提出了使用线性计数草图扩展的两种任务的解决方案。这个想法是将几个人映射到一个草图中的相同位置,而与此同时,通过使用几个独立的草图可以弥补由重载引起的不准确性。这个想法首次提供了一组通用原语,用于保护来自蓝牙和类似基于地址的设备的隐私保护移动性模型。

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