Preserving privacy in gps traces via uncertainty-aware path cloaking

Motivated by a probe-vehicle based automotive traffic monitoring system, this paper considers the problem of guaranteed anonymity in a dataset of location traces while maintaining high data accuracy. We find through analysis of a set of GPS traces from 233 vehicles that known privacy algorithms cannot meet accuracy requirements or fail to provide privacy guarantees for drivers in low-density areas. To overcome these challenges, we develop a novel time-toconfusion criterion to characterize privacy in a location dataset and propose an uncertainty-aware path cloaking algorithm that hides location samples in a dataset to provide a time-to-confusion guarantee for all vehicles. We show that this approach effectively guarantees worst case tracking bounds, while achieving significant data accuracy improvements. Categories and Subject Descriptors K.4.1 [Computers and Society]: Public Policy IssuesPrivacy; K.6 [Management of Computing and Information Systems]: Security and Protection General...

• Type: Conference
• Year: 2007
• Where: CCS
• Authors: Baik Hoh, Marco Gruteser, Hui Xiong, Ansaf Alrabady
• Keywords: CCS 2007, Data Accuracy, Dataset, Privacy, Security Privacy