An open design privacy-enhancing platform supporting location-based applications
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Predictive spatio-temporal queries: a comprehensive survey and future directions
Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems
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The ubiquity of smartphones and other location-aware hand-held devices has resulted in a dramatic increase in popularity of location-based services (LBS) tailored to user locations. The comfort of LBS comes with a privacy cost. Various distressing privacy violations caused by sharing sensitive location information with potentially malicious services have highlighted the importance of location privacy research aiming to protect user privacy while interacting with LBS.The anonymity and cloaking-based approaches proposed to address this problem cannot provide stringent privacy guarantees without incurring costly computation and communication overhead. Furthermore, they mostly require a trusted intermediate anonymizer to protect a user's location information during query processing. In this chapter, we review a set of fundamental approaches based on private information retrieval to process range and k-nearest neighbor queries, the elemental queries used in many Location Based Services, with significantly stronger privacy guarantees as opposed to cloaking or anonymity approaches.