Protecting privacy for distance and rank based group nearest neighbor queries

Abstract

This paper proposes a novel approach to safeguarding location privacy for GNN (group nearest neighbor) queries. Given the locations of a group of dispersed users, the GNN query returns the location that minimizes the total or the maximal distance for all group users. The returned location is typically a meeting place such as a cinema or coffee shop where the group would like to meet. In our work, we highlight the challenges for private GNN queries and propose a general framework that have two key features: (i) it ensures privacy in a decentralized manner and (ii) can compute an optimal location for GNN query that maximizes the group’s overall preference for the meeting place. To mask their p..