The contents of this legacy page are no longer maintained nor supported, and are made available only for historical purposes.

Bibliography Details

B. Hoh, M. Gruteser, H. Xiong, and A. Alrabady, "Preserving privacy in gps traces via uncertainty-aware path cloaking", in ACM Conference on Computer and Communications Security (CCS), 2007.

Preserving privacy in gps traces via uncertainty-aware path cloaking
Authors: B. Hoh
M. Gruteser
H. Xiong
A. Alrabady
Published: ACM Conference on Computer and Communications Security (CCS), 2007
URL: http://portal.acm.org/citation.cfm?id=1315266&jmp=cit&coll=&dl=GUIDE
http://www.winlab.rutgers.edu/~gruteser/papers/ccs308-baik.pdf
ENTRY DATE: 2008-06-16
ABSTRACT: Motivated by a probe-vehicle based automotive traffic monitoring system, this paper considers the problem of guaranteed anonymity in a dataset of location traces while maintaining high data accuracy. We find through analysis of a set of GPS traces from 233 vehicles that known privacy algorithms cannot meet accuracy requirements or fail to provide privacy guarantees for drivers in low-density areas. To overcome these challenges, we develop a novel time-to-confusion criterion to characterize privacy in a location dataset and propose an uncertainty-aware path cloaking algorithm that hides location samples in a dataset to provide a time-to-confusion guarantee for all vehicles. We show that this approach effectively guarantees worst case tracking bounds, while achieving significant data accuracy improvements.