Protecting privacy for group nearest neighbor queries with crowdsourced data and computing

Authors:
Tanzima Hashem;Mohammed Eunus Ali;Lars Kulik;Egemen Tanin;Anthony Quattrone
Affiliations:
Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh;Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh;University of Melbourne, Victoria, Australia;University of Melbourne, Victoria, Australia;Department of Computing and Information Systems, University of Melbourne, Australia
Venue:
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
Year:
2013

Citing 8
Cited 0

Group Nearest Neighbor Queries

ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking

Proceedings of the 1st international conference on Mobile systems, applications and services
Private queries in location based services: anonymizers are not necessary

Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Private Queries and Trajectory Anonymization: a Dual Perspective on Location Privacy

Transactions on Data Privacy
A survey of computational location privacy

Personal and Ubiquitous Computing
Privacy preserving group nearest neighbor queries

Proceedings of the 13th International Conference on Extending Database Technology
Safeguarding location privacy in wireless ad-hoc networks

UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
GLP: A cryptographic approach for group location privacy

Computer Communications

Quantified Score

Hi-index	0.00

Visualization

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 PrivateMeetUp, to evaluate GNN queries in a privacy preserving manner and implement a working prototype of PrivateMeetUp.