Geosocial networks are online social networks centered on the locations of subscribers and businesses. Providing input to targeted advertising, profiling social network users becomes an important source of revenue. Its natural reliance on personal information introduces a trade-off between user privacy and incentives of participation for businesses and geosocial network providers. In this paper we introduce location centric profiles (LCPs), aggregates built over the profiles of users present at a given location. We introduce PROFILR, a suite of mechanisms that construct LCPs in a private and correct manner. We introduce iSafe, a novel, context aware public safety application built on PROFILR . Our Android and browser plugin implementations show that PROFILR is efficient: the end-to-end overhead is small even under strong correctness assurances.
@cite_15 proposed SMILE, a privacy-preserving missed-connections'' service similar to Craigslist, where the service provider is untrusted and users do not have existing relationships. The solution is distributed, allowing users to anonymously prove to each other the existence of a past encounter. While we have a similar setup, our work addresses a different problem, of privately collecting location centric user profile aggregates.
@cite_15
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Conventional mobile social services such as Loopt and Google Latitude rely on two classes of trusted relationships: participants trust a centralized server to manage their location information and trust between users is based on existing social relationships. Unfortunately, these assumptions are not secure or general enough for many mobile social scenarios: centralized servers cannot always be relied upon to preserve data confidentiality, and users may want to use mobile social services to establish new relationships. To address these shortcomings, this paper describes SMILE, a privacy-preserving "missed-connections" service in which the service provider is untrusted and users are not assumed to have pre-established social relationships with each other. At a high-level, SMILE uses short-range wireless communication and standard cryptographic primitives to mimic the behavior of users in existing missed-connections services such as Craigslist: trust is founded solely on anonymous users' ability to prove to each other that they shared an encounter in the past. We have evaluated SMILE using protocol analysis, an informal study of Craigslist usage, and experiments with a prototype implementation and found it to be both privacy-preserving and feasible.