Development of an Improved Anonymity in GPS Traces for Analyzing Traffic and Routes

The incorporation of Global Positioning System (GPS) receivers and sensors into mobile devices has enabled collaborative sensing applications, to monitor the dynamics of environments through the collection of data from many users’ devices. The automotive traffic monitoring system and alternative route selection estimates traffic congestion from GPS velocity measurements reported from many devices. This paper considers the problem of improving guaranteed anonymity in a locational data set that includes location traces from many users, while maintaining high data accuracy. A novel time-to-confusion criterion to characterize privacy in a locational data set and propose a disclosure control algorithm that selectively reveals GPS samples to limit the maximum time-to confusion for all vehicles. It also considers heading information reported by users in the tracking model to find alternative route.