TY - GEN
T1 - FindU
T2 - IEEE INFOCOM 2011
AU - Li, Ming
AU - Cao, Ning
AU - Yu, Shucheng
AU - Lou, Wenjing
PY - 2011
Y1 - 2011
N2 - Making new connections according to personal preferences is a crucial service in mobile social networking, where the initiating user can find matching users within physical proximity of him/her. In existing systems for such services, usually all the users directly publish their complete profiles for others to search. However, in many applications, the users' personal profiles may contain sensitive information that they do not want to make public. In this paper, we propose FindU, the first privacy-preserving personal profile matching schemes for mobile social networks. In FindU, an initiating user can find from a group of users the one whose profile best matches with his/her; to limit the risk of privacy exposure, only necessary and minimal information about the private attributes of the participating users is exchanged. Several increasing levels of user privacy are defined, with decreasing amounts of exchanged profile information. Leveraging secure multi-party computation (SMC) techniques, we propose novel protocols that realize two of the user privacy levels, which can also be personalized by the users. We provide thorough security analysis and performance evaluation on our schemes, and show their advantages in both security and efficiency over state-of-the-art schemes.
AB - Making new connections according to personal preferences is a crucial service in mobile social networking, where the initiating user can find matching users within physical proximity of him/her. In existing systems for such services, usually all the users directly publish their complete profiles for others to search. However, in many applications, the users' personal profiles may contain sensitive information that they do not want to make public. In this paper, we propose FindU, the first privacy-preserving personal profile matching schemes for mobile social networks. In FindU, an initiating user can find from a group of users the one whose profile best matches with his/her; to limit the risk of privacy exposure, only necessary and minimal information about the private attributes of the participating users is exchanged. Several increasing levels of user privacy are defined, with decreasing amounts of exchanged profile information. Leveraging secure multi-party computation (SMC) techniques, we propose novel protocols that realize two of the user privacy levels, which can also be personalized by the users. We provide thorough security analysis and performance evaluation on our schemes, and show their advantages in both security and efficiency over state-of-the-art schemes.
UR - http://www.scopus.com/inward/record.url?scp=79960878565&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960878565&partnerID=8YFLogxK
U2 - 10.1109/INFCOM.2011.5935065
DO - 10.1109/INFCOM.2011.5935065
M3 - Conference contribution
AN - SCOPUS:79960878565
SN - 9781424499212
T3 - Proceedings - IEEE INFOCOM
SP - 2435
EP - 2443
BT - 2011 Proceedings IEEE INFOCOM
Y2 - 10 April 2011 through 15 April 2011
ER -