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Pervasive social networks extend traditional social networking by enabling users to share information in a peer-to-peer fashion using their wireless mobile devices. Contrary to traditional online social networks, privacy protection in such networks depends heavily on users' context (time, location, activity, etc.) and their sensitivity to the shared data and context. Existing privacy-preserving mechanisms do not adapt well to different data, context and user sensitivities. In this work, we follow a fresh approach for privacy preservation, called privacy-triggered communications; it allows users in such pervasive networks to dynamically regulate their communications based on their context and on the evolution of their privacy in that context. Our initial results show that this is a feasible strategy for privacy management in pervasive social networking scenarios.
Date of Conference: 20-24 June 2011