ISCAS OpenIR
A Novel privacy-preserving group matching scheme in social networks
Chi, Jialin (1); Lv, Zhiquan (1); Zhang, Min (1); Li, Hao (1); Hong, Cheng (1); Feng, Dengguo (1)
2014
Conference Name15th International Conference on Web-Age Information Management, WAIM 2014
Pages336-347
Conference DateJune 16, 2014 - June 18, 2014
Conference PlaceMacau, China
Indexed TypeCPCI ; EI
Publish PlaceSpringer Verlag
ISSN3029743
ISBN9783319080093
Department(1) Trusted Computing and Information Assurance Laboratory, Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) University of Chinese Academy of Sciences, Beijing, China
English AbstractThe 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. © 2014 Springer International Publishing Switzerland.; 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. © 2014 Springer International Publishing Switzerland.
KeywordSocial Networks Group Matching Private Set Intersection
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/16515
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Chi, Jialin ,Lv, Zhiquan ,Zhang, Min ,et al. A Novel privacy-preserving group matching scheme in social networks[C]. Springer Verlag,2014:336-347.
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