The success of applications for sharing GPS trajectories raises serious privacy concerns, in particular about users' home addresses. In this paper we show that a Bayesian approach is natural and effective for a rigorous analysis of home-identification attacks and their countermeasures, in terms of privacy. We focus on a family of countermeasures named "privacy-region strategies", consisting in publishing each trajectory from the first exit to the last entrance from/into a privacy region. Their performance is studied through simulations on Brownian motions.
Cite
@article{arxiv.1806.08998,
title = {Bayesian Analysis of Privacy Attacks on GPS Trajectories},
author = {Sirio Legramanti},
journal= {arXiv preprint arXiv:1806.08998},
year = {2019}
}
Comments
6 pages, LaTeX; more concise and partially rewritten with respect to the first version, but same results