Participatory sensing is emerging as an innovative computing paradigm that targets the ubiquity of always-connected mobile phones and their sensing capabilities. In this context, a multitude of pioneering applications increasingly carry out pervasive collection and dissemination of information and environmental data, such as, traffic conditions, pollution, temperature, etc. Participants collect and report measurements from their mobile devices and entrust them to the cloud to be made available to applications and users. Naturally, due to the personal information associated to the reports (e.g., location, movements, etc.), a number of privacy concerns need to be taken into account prior to a large-scale deployment of these applications. Motivated by the need for privacy protection in Participatory Sensing, this work presents PEPSI: a Privacy-Enhanced Participatory Sensing Infrastructure. We explore realistic architectural assumptions and a minimal set of formal requirements aiming at protecting privacy of both data producers and consumers. We propose two instantiations that attain privacy guarantees with provable security at very low additional computational cost and almost no extra communication overhead.
People increasingly generate content on their mobile devices and upload it to third-party services such as Facebook and Google Latitude for sharing and backup purposes. Although these services are convenient and useful, their use has important privacy implications due to their centralized nature and their acquisitions of rights to user-contributed content. This paper argues that people's interests would be be better served by uploading their data to a machine that they themselves own and control. We term these machines Virtual Individual Servers (VISs) because our preferred instantiation is a virtual machine running in a highly-available utility computing infrastructure. By using VISs, people can better protect their privacy because they retain ownership of their data and remain in control over the software and policies that determine what data is shared with whom. This paper also describes a range of applications of VIS proxies. It then presents our initial implementation and evaluation of one of these applications, a decentralized framework for mobile social services based on VISs. Our experience so far suggests that building such applications on top of the VIS concept is feasible and desirable.