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...

• Type: Conference
• Year: 2010
• Where: EDBT
• Authors: Tanzima Hashem, Lars Kulik, Rui Zhang
• Keywords: Database, EDBT 2010, Group Nearest Neighbor, Neighbor Queries, User Privacy