A privacy-aware framework for participatory sensing

With the abundance and ubiquity of mobile devices, a new class of applications is emerging, called participatory sensing (PS), where people can contribute data (e.g., images, video) collected by their mobile devices to central data servers. However, privacy concerns are becoming a major impediment in the success of many participatory sensing systems. While several privacy preserving techniques exist in the context of conventional location-based services, they are not directly applicable to the PS systems because of the extra information that the PS systems can collect from their participants. In this paper, we formally define the problem of privacy in PS systems and identify its unique challenges assuming an un-trusted central data server model. We propose PiRi, a privacy-aware framework for PS systems, which enables participation of the users without compromising their privacy. Our extensive experiments verify the efficiency of our approach.