Private Retrieval of POI Details in Top-K Queries

Location privacy preservation algorithms in the context of location-based services have evolved in the recent years. However, a majority of the proposals assume that points of interests (POI) are ranked only by distance, and demand extensive architectural changes. As a result, a significant gap remains between academic proposals and the industry standard of implementing location based services. Recent advances in mobile device capabilities, more specifically in their computational power and energy efficiency, have opened the possibility of engaging the client hardware more actively in the execution of a privacy algorithm, thereby relaxing strong dependencies on trusted third parties or the service provider. With this motivation, we propose a novel privacy algorithm that determines the most prominent result set through operations restricted to the client device, thereby limiting the communication of precise location information to the service provider. The service provider only acts as a data source, and is required to perform operations that are within existing industry norms. By measuring the privacy offered by the algorithm under a formal threat model, we demonstrate its robustness and practicability, and supplement our conclusions with empirical evidence.