Papers by Letizia Bertolaja
Location Privacy Management and Protection in Geo-social Networks
2013 IEEE 14th International Conference on Mobile Data Management, 2013
A Practical Location Privacy Attack in Proximity Services
2013 IEEE 14th International Conference on Mobile Data Management, 2013
ABSTRACT The aim of proximity services is to raise alerts based on the distance between moving ob... more ABSTRACT The aim of proximity services is to raise alerts based on the distance between moving objects. While distance can be easily computed from the objects' geographical locations, privacy concerns in revealing these locations exist, especially when proximity among users is being computed. Distance pre- serving transformations have been proposed to solve this problem by enabling the service provider to acquire pairwise distances while not acquiring the actual objects positions. It is known that distance preserving transformations do not provide formal privacy guarantees in presence of certain background knowledge but it is still unclear which are the practical conditions that make distance preserving transformations "vulnerable". We study these conditions by designing and testing an attack based on public density information and on partial knowledge of distances between users. A clustering-based technique first discovers the approximate position of users located in the largest cities. Then a technique based on trilateration reduces this approximation and discovers the approximate position of the other users. Our experimental results show that partial distance information, like the one exchanged in a friend-finder service, can be sufficient to locate up to 60% of the users in an area smaller than a city.
SafeBox: adaptable spatio-temporal generalization for location privacy protection
Gonio, Aequus and Incognitus: three spatial granularities for privacy-aware systems
Location privacy attacks based on distance and density information
Proceedings of the 20th International Conference on Advances in Geographic Information Systems - SIGSPATIAL '12, 2012
ABSTRACT Proximity services alert users about the presence of other users or moving objects based... more ABSTRACT Proximity services alert users about the presence of other users or moving objects based on their distance. Distance preserving transformations are among the techniques that may be used to avoid revealing the actual position of users while still effectively providing these services. Some of the proposed transformations have been shown to actually guarantee location privacy with the assumption that users are uniformly distributed in the considered geographical region, which is unrealistic assumption when the region extends to a county, a state or a country. In this paper we describe a location privacy attack that, only using partial information about the distances between users and public knowledge on the average density of population, can discover the approximate position of users on a map, independently on the fake or hidden position assigned to them by a privacy preserving algorithm. We implement this attack with an algorithm and we experimentally evaluate it showing that it is practically feasible and that partial distance information like the one exchanged in common friend-finder services can be sufficient to violate users' privacy.
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Papers by Letizia Bertolaja