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In a mobile service scenario, users query a server for nearby points of interest but they may not want to disclose their locations to the service. Intuitively, location privacy may be obtained at the cost of query performance and query accuracy. We develop a solution, called SpaceTwist, for evaluating k nearest neighbor (kNN) queries in this context. This approach is flexible, needs no trusted middleware, and requires only simple processing techniques on the server. Our goal is to obtain the best possible performance, subjected to given requirements for location privacy and query accuracy. Our experimental study shows that SpaceTwist offers very good performance and high privacy, at low communication cost.

Man Lung Yiu received the bachelor's degree in computer engineering and the PhD degree in computer science from the University of Hong Kong in 2002 and 2006, respectively. He is currently an assistant professor in the Department of Computer Science, Aalborg University. His research focuses on the management of complex data, in particular the processing of complex queries on spatio-temporal data.