Secure and private proofs for location-based activity summaries in urban areas

Abstract

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).

SecureRun: Cheat-Proof and Private Summaries for Location-Based Activities

“…SecureRun achieves good accuracy, up to a median accuracy of more than 80%. This constitutes a significant improvement compared to the performance of the initial version of the system reported in [1]: On average, we achieved an absolute improvement of 5-10 points in the median accuracy. In our survey, we also asked the participants about their level of satisfaction regarding activity summaries for different values of the summary accuracy (i.e., "Assuming that you have run 10 miles, what would your level of satisfaction be if SecureRun issues a certificate of 6 mi?…”

“…1 We assume them to be semi-honest or honest-but-curious, meaning that they do not deviate from the protocol specified in our solution, but that they analyze the information they collect while executing the protocol.…”

“…In fact, solutions guaranteeing (1) would benefit the service provider by ensuring that cheating is infeasible, whereas solutions satisfying (2) would protect users' location privacy but would provide locations that are too coarse-grained for computing meaningful summaries.…”

“…Finally, it is able to take advantage of the co-existence of multiple access-point operators to improve the accuracy/privacy trade-off. Unlike the initial version of our system presented in [1], in order to maximize the accuracy of the activity summaries produced, SecureRun computes the optimal set of access points to communicate with. To the best of our knowledge, this is the first work to address privacy and cheating issues in the computation of activity summaries.…”

PrivateRide: A Privacy-Enhanced Ride-Hailing Service

“…These solutions rely on tamper-evident devices installed in the vehicles and random spot-checks to compute the total distance traveled by the vehicles. Later on, Pham et al [51] proposed a solution based on the networks of access points, to provide a verifiable lower-bound of the distance reported by a user.…”