Privacy of a user’s location or location preferences, with respect to other users and the third-party service provider, is a critical concern in such location-sharing-based applications. Equipped with state-of-the-art smart phones and mobile devices, today’s highly interconnected urban population is increasingly dependent on these gadgets to organize and plan their daily lives. These applications often rely on current (or preferred) locations of individual users or a group of users to provide the desired service, which jeopardizes their privacy; users do not necessarily want to reveal their current (or preferred) locations to the service provider or to other, possibly untrusted, users. In this abstract, we propose privacy-preserving algorithms for determining an optimal meeting location for a group of users. We perform a thorough privacy evaluation by formally quantifying privacy-loss of the proposed approaches. In order to study the performance of our algorithms in a real deployment, we implement and test their execution efficiency on Nokia smart phones. By means of a targeted user-study, we attempt to get an insight into the privacy-awareness of users in location-based services and the usability of the proposed solutions.
You are here: / / PRIVACY-PRESERVING ALGORITHMS FOR DETERMINING AN OPTIMAL MEETING LOCATION FOR MOBILE DEVICES