Message in a Sealed Bottle: Privacy Preserving Friending in Social Networks
This addresses privacy concerns for users in proximity-based social networks, offering a practical solution with incremental improvements in efficiency and security.
The paper tackles the problem of privacy-preserving friend matching in decentralized mobile social networks, achieving secure and efficient profile matching without exposing personal data. Evaluations on real data and smartphone implementations show significant efficiency improvements over existing solutions.
Many proximity-based mobile social networks are developed to facilitate connections between any two people, or to help a user to find people with matched profile within a certain distance. A challenging task in these applications is to protect the privacy the participants' profiles and personal interests. In this paper, we design novel mechanisms, when given a preference-profile submitted by a user, that search a person with matching-profile in decentralized multi-hop mobile social networks. Our mechanisms are privacy-preserving: no participants' profile and the submitted preference-profile are exposed. Our mechanisms establish a secure communication channel between the initiator and matching users at the time when the matching user is found. Our rigorous analysis shows that our mechanism is secure, privacy-preserving, verifiable, and efficient both in communication and computation. Extensive evaluations using real social network data, and actual system implementation on smart phones show that our mechanisms are significantly more efficient then existing solutions.