1 Department of Computer Science, Science and Technology, Aarhus University2 Missouri University of Science & Technology3 The University of Melbourne4 Renmin University of China5 Department of Computer Science, Science and Technology, Aarhus University
With the growing use of location-based services, location privacy attracts increasing attention from users, industry, and the research community. While considerable effort has been devoted to inventing techniques that prevent service providers from knowing a user’s exact location, relatively little attention has been paid to enabling so-called peer-wise privacy—the protection of a user’s location from unauthorized peer users. This paper identifies an important efficiency problem in existing peer-privacy approaches that simply apply a filtering step to identify users that are located in a query range, but that do not want to disclose their location to the querying peer. To solve this problem, we propose a novel, privacy-policy enabled index called the PEB-tree that seamlessly integrates location proximity and policy compatibility. We propose efficient algorithms that use the PEB-tree for processing privacy-aware range and kNN queries. Extensive experiments suggest that the PEB-tree enables efficient query processing.
Proceedings of the Vldb Endowment, 2011, Vol 5, Issue 1, p. 37-48