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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.
  Last Modified: Wed Mar-27-2019 22:23:20 PDT
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