Secure and Private Proofs for Location-Based Activity Summaries in Urban Areas
Activity-based social networks, where people upload and share information about their location-based activities (e.g., the routes of their activities), are increasingly popular. Such systems, however, raise privacy and security issues: the service providers know the exact locations of their users; the users can report fake location information to, for example, unduly brag about their performance. In this paper, we propose a secure privacy-preserving system for reporting location-based activity summaries (e.g., the total distance covered and the elevation gain). Our solution is based on a combination of cryptographic techniques and geometric algorithms, and it relies on existing Wi-Fi access point networks deployed in urban areas. We evaluate our solution by using real data-sets from the FON community networks and from the Garmin Connect activity-based social network, and show that it can achieve tight (up to a median accuracy of 79%) verifiable lower-bounds of the distance covered and of the elevation gain, while protecting the location privacy of the users with respect to both the social network operator and the access point network operator(s).