A Privacy-Aware Architecture to Share Device-to-Device Contextual Information

Smartphones have become the perfect companion devices. They have myriad sensors for gathering the context of their owners in order to adapt the behaviour of different applications to the device's situation. This information can also be of great help in enabling the development of social applications that, otherwise, would require a costly and intractable deployment of sensors. Mobile Crowd Sensing systems highly reduce this cost, but realizing this vision using traditional centralized networking primitives requires a constant stream of the sensed data to the cloud in order to store and process it, which in turn leads to the individuals about whom the data is sensed losing control over the privacy of the data. In this paper, we propose an architecture for a device-to-device Mobile Crowd Sensing system and we deepen on a new privacy model that allows users to define access control policies based on their context and the consumer's context.