  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.
