FindU: Privacy-preserving personal profile matching in mobile social networks

Ming Li, Ning Cao, Shucheng Yu, Wenjing Lou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

197 Scopus citations


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.

Original languageEnglish (US)
Title of host publication2011 Proceedings IEEE INFOCOM
Number of pages9
StatePublished - 2011
Externally publishedYes
EventIEEE INFOCOM 2011 - Shanghai, China
Duration: Apr 10 2011Apr 15 2011

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X



ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering

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