Recent Internet applications, such as online social networks and user-generated content sharing, produce an unprecedented amount of social information, which is further augmented by location or collocation data collected from mobile phones. Unfortunately, this wealth of social information is fragmented across many different proprietary applications. Combined, it could provide a more accurate representation of the social world, and it could enable a whole new set of socially-aware applications. We introduce Prometheus, a peer-to-peer service that collects and manages social information from multiple sources and implements a set of social inference functions while enforcing user-defined access control policies. Prometheus is socially-aware: it allows users to select peers that manage their social information based on social trust and exploits naturally-formed social groups for improved performance. We tested our Prometheus prototype on PlanetLab and built a mobile social application to test the performance of its social inference functions under realtime constraints. We showed that the social-based mapping of users onto peers improves the service response time and high service availability is achieved with low overhead.

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The dramatic rise in mobile applications has greatly increased threats to the security and privacy of users. Security mechanisms on mobile devices are currently limited, so users need more expressive ways to ensure that downloaded mobile applications do not act maliciously. Policy-specification languages were created for this purpose; they allow the enforcement of user-defined policies on third-party applications. We have implemented LoPSiL, a location-based policy-specification language for mobile devices. This article describes LoPSiL's design and implementation, several example policies, and experiments that demonstrate LoPSiL's viability for enforcing policies on mobile devices.