Private location centric profiles for GeoSocial networks Conference

Carbunar, B, Rahman, M, Rishe, N et al. (2012). Private location centric profiles for GeoSocial networks . 458-461. 10.1145/2424321.2424389

cited authors

  • Carbunar, B; Rahman, M; Rishe, N; Ballesteros, J

abstract

  • Providing input to targeted advertising, profiling social network users is an important source of revenue for geosocial networks. Since profiles contain personal information, their construction 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. Our Android implementation shows that Profil R is efficient: the end-to-end overhead is small even under strong correctness assurances. © 2012 Authors.

publication date

  • December 1, 2012

Digital Object Identifier (DOI)

International Standard Book Number (ISBN) 13

start page

  • 458

end page

  • 461