User Centric Privacy in Mobile Communication Scenarios

One common assumption when defining location privacy metrics is that one is dealing with attackers whose objective is to re-identify an individual out of an anonymized data set. However, today´s communication scenarios are more diverse. For instance, there are several entities involved in mobile location sharing between individuals. Hence, in a communication relation with a service provider (e.g. SNS or network infrastructure) or with social contacts, an anonymity approach seems inadequate. Between each user and every single entity involved there is some level of trust and the identities are already known, at least to some extent. Hence, taking an anonymity approach for communication relations to peers or service providers (e.g. SNS or network infrastructure) seems to be inadequate. Therefore, we present an attacker model and propose a user-centric privacy metric to allow a user to uncover the extent of information disclosure and to evaluate autonomously his privacy level in a communication relation with semi-trusted listener groups. The goal of such a metric is to enable an individual to estimate the privacy loss caused by disclosing location information in a specific communication scenario and thus enabling the user to make informed choices, e.g. choose the right protection mechanism.