Caching as Privacy Enhancing Mechanism in Location-based Services

A Location-based Service has to protect user's location and query information to alleviate privacy concerns. Several location and query privacy preserving approaches, based on the concept of k-anonymity and 1-diversity, have been proposed in the literature. These approaches assume a trusted anonymizer. Caching has been used as the trusted anonymizer to save communication and computation cost and to enhance the privacy of snapshot and continuous user queries. Such cache designs only provide privacy up to a certain limit and are not designed for multiple points of interest (POI) type queries. We propose a novel cache design and a cache event model that provides significantly higher levels of privacy. We also propose a novel privacy preserving metric which measures the privacy offered by different components (caching, k-anonymity, I-diversity) of the anonymizer which is to the best of our knowledge the first comprehensive privacy measuring metric. We perform several experiments on real world data to evaluate the effectiveness of our cache design in terms of privacy enhancements, computation and communication costs.