A Novel Privacy-Preserving Group Matching Scheme in Social Networks
The group service allowing users with common attributes to make new connections and share information has been a crucial service in social networks. In order to determine which group is more suitable to join, a stranger outside of the groups needs to collect profile information of group members. When a stranger applies to join one group, each group member also wants to learn more about the stranger to decide whether to agree to the application. In addition, users’ profiles may contain private information and they don’t want to disclose them to strangers. In this paper, by utilizing private set intersection (PSI) and a semi-trusted third party, we propose a group matching scheme which helps users to make better decisions without revealing personal information. We provide security proof and performance evaluation on our scheme, and show that our system is efficient and practical to be used in mobile social networks.
KeywordsSocial Networks Group Matching Private Set Intersection
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