Provisioning Privacy and Accountability in Participatory Sensing

Mobile Crowd Sensing (MCS) is a cost-effective and innovative paradigm that exploits the power of the crowd by facilitating individuals with sensing and computing devices to collectively sense the physical world and share the sensed data. The goal is to extract information from the collected data to measure and map phenomena of common interest. For an MCS campaign to be successful, privacy of the participants should be preserved. At the same time, the platform should be able to fix responsibility when a dishonest participant behaves maliciously (for instance, shares falsified data). Hence, privacy and accountability are important issues which need to be provisioned in the MCS architecture. This work proposes an extension to an existing MCS architecture which takes care of both. Security analysis of the architecture is also presented.