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Privacy-Preserving User Profile Matching in Social Networks.

Authors :
Yi, Xun
Bertino, Elisa
Rao, Fang-Yu
Lam, Kwok-Yan
Nepal, Surya
Bouguettaya, Athman
Source :
IEEE Transactions on Knowledge & Data Engineering. Aug2020, Vol. 32 Issue 8, p1572-1585. 14p.
Publication Year :
2020

Abstract

In this paper, we consider a scenario where a user queries a user profile database, maintained by a social networking service provider, to identify users whose profiles match the profile specified by the querying user. A typical example of this application is online dating. Most recently, an online dating website, Ashley Madison, was hacked, which resulted in a disclosure of a large number of dating user profiles. This data breach has urged researchers to explore practical privacy protection for user profiles in a social network. In this paper, we propose a privacy-preserving solution for profile matching in social networks by using multiple servers. Our solution is built on homomorphic encryption and allows a user to find out matching users with the help of multiple servers without revealing to anyone the query and the queried user profiles in clear. Our solution achieves user profile privacy and user query privacy as long as at least one of the multiple servers is honest. Our experiments demonstrate that our solution is practical. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10414347
Volume :
32
Issue :
8
Database :
Academic Search Index
Journal :
IEEE Transactions on Knowledge & Data Engineering
Publication Type :
Academic Journal
Accession number :
144568210
Full Text :
https://doi.org/10.1109/TKDE.2019.2912748