Biblio

This last decade has witnessed a wide adoption of connected mobile devices able to capture the context of their owners from embedded sensors (GPS, Wi-Fi, Bluetooth, accelerometers). The advent of mobile and pervasive computing has enabled rich social and contextual applications, but the use of such technologies raises severe privacy issues and challenges. The privacy threats come from diverse adversaries, ranging from curious service providers and other users of the same service to eavesdroppers and curious applications running on the device. The information that can be collected from mobile device owners includes their locations, their social relationships, and their current activity. All of this, once analyzed and combined together through inference, can be very telling about the users' private lives. In this talk, we will describe privacy threats in mobile and pervasive networks. We will also show how to quantify the privacy of the users of such networks and explain how information on co-location can be taken into account. We will describe the role that privacy enhancing technologies (PETs) can play and describe some of them. We will also explain how to prevent apps from sifting too many personal data under Android. We will conclude by mentioning the privacy and security challenges raised by the quantified self and digital medicine