Privacy-Preserving Techniques for Proximity Based LBS

As location based services (LBS) become more popular, preserving users\´ privacy is becoming an important task. In this paper we present our findings about the privacy threats related to a particular class of LBS and the techniques we recently developed to protect users from these threats. The class of services we address are the proximity based services, in which a user obtains to know if the distance of other users (or, in general, other entities) from her location is above or below a requested threshold. A popular service belonging to this class is the "friend-finder" service. A user subscribed to this kind of service wants to be alerted when one of her buddies is in the neighborhood, so they can eventually get in contact and meet. Depending on the type of service provided, "buddies" can be either identified by a set of known users (like contact lists in instant messaging services) or by a set of users which meets some criteria requested by the user. More technically, a proximity based service consists of spatial range queries on the database of users\´ locations, using the desired proximity threshold as range.