Attacking location privacy

Abstract

The proliferation of location-based services in recent years has highlighted the need to consider location privacy. This has led to the development of methods enhancing location privacy, and to the investigation of reasons for sharing location information. While computational attacks on location privacy and their prevention have attracted a lot of research, attacks based on humans strategies and tactics have mostly been considered implicitly. This note addresses this knowledge gap by reporting on a user study, which we conducted in the context of a location-based game. Participants had to identify other players over the course of several weeks. The results show that human strategies for deanonymization and re-identification can be highly successful and thus pose a threat to location privacy comparable to computational attacks. By incorporating real-world knowledge (that is not easily available in automated attacks), human players were able to efficiently identify other people in the game.