Privacy preserving group nearest neighbor queries

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Privacy preserving group nearest neighbor queries
User privacy in location-based services has attracted great interest in the research community. We introduce a novel framework based on a decentralized architecture for privacy preserving group nearest neighbor queries. A group nearest neighbor (GNN) query returns the location of a meeting place that minimizes the aggregate distance from a spread out group of users; for example, a group of users can ask for a restaurant that minimizes the total travel distance from them. We identify the challenges in preserving user privacy for GNN queries and provide a comprehensive solution to this problem. In our approach, users provide their locations as regions instead of exact points to a location service provider (LSP) to preserve their privacy. The LSP returns a set of candidate answers that includes the actual group nearest neighbor. We develop a private filter that determines the actual group nearest neighbor from the retrieved candidate answers without revealing user locations to any invol...
Tanzima Hashem, Lars Kulik, Rui Zhang
Added 09 Jul 2010
Updated 09 Jul 2010
Type Conference
Year 2010
Where EDBT
Authors Tanzima Hashem, Lars Kulik, Rui Zhang
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