The impact of trace and adversary models on location privacy provided by K-anonymity

Privacy preserving mechanisms help users of location-based services to balance their location privacy while still getting useful results from the service. The provided location privacy depends on the users' behavior and an adversary's knowledge used to locate the users. The aim of this paper is to investigate how users' mobility patterns and adversaries' knowledge affect the location privacy of users querying a location-based service. We consider three mobility trace models in order to generate user traces that cross each other, are parallel to each other and form a circular shape. Furthermore, we consider four adversary models, which are distinguished according to their level of knowledge of users. We simulate the trace and the adversary models by using Distortion-based Metric and K-anonymity. The results show that the location privacy provided by K-anonymity decreases, as users are located closer to each other in the trace models. The impact of the adversary on location privacy is reduced as more users are cloaked together.