Conference Proceedings
Protecting Privacy for Group Nearest Neighbor Queries with Crowdsourced Data and Computing
Tanzima Hashem, Mohammed Eunus Ali, Lars Kulik, Egemen Tanin, Anthony Quattrone
Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing | ACM | Published : 2013
Abstract
User privacy in location-based services (LBSs) has become an important research area. We introduce a new direction to protect user privacy that evaluates LBSs with crowdsourced data and computation and eliminates the role of a location based service provider. We focus on the group nearest neighbor (GNN) query that allows a group to meet at their nearest point of interest such as a restaurant that minimizes the total or maximum distance of the group. We develop a crowdsource-based approach, called Private Meet Up, to evaluate GNN queries in a privacy preserving manner and implement a working prototype of Private Meet Up. Copyright © 2013 ACM.
Grants
Awarded by Australian Research Councils Discovery Projects funding scheme
Funding Acknowledgements
This research was supported under Australian Research Councils Discovery Projects funding scheme (project number DP110100757).