DocumentCode :
1940058
Title :
Secure friend discovery in mobile social networks
Author :
Dong, Wei ; Dave, Vacha ; Qiu, Lili ; Zhang, Yin
Author_Institution :
Univ. of Texas at Austin, Austin, TX, USA
fYear :
2011
fDate :
10-15 April 2011
Firstpage :
1647
Lastpage :
1655
Abstract :
Mobile social networks extend social networks in the cyberspace into the real world by allowing mobile users to discover and interact with existing and potential friends who happen to be in their physical vicinity. Despite their promise to enable many exciting applications, serious security and privacy concerns have hindered wide adoption of these networks. To address these concerns, in this paper we develop novel techniques and protocols to compute social proximity between two users to discover potential friends, which is an essential task for mobile social networks.We make three major contributions. First, we identify a range of potential attacks against friend discovery by analyzing real traces. Second, we develop a novel solution for secure proximity estimation, which allows users to identify potential friends by computing social proximity in a privacy-preserving manner. A distinctive feature of our solution is that it provides both privacy and verifiability, which are frequently at odds in secure multiparty computation. Third, we demonstrate the feasibility and effectiveness of our approaches using real implementation on smartphones and show it is efficient in terms of both computation time and power consumption.
Keywords :
mobile computing; security of data; social networking (online); mobile social networks; physical vicinity; potential attacks; potential friend discovery; privacy concerns; privacy-preserving manner; protocols; secure friend discovery; secure proximity estimation; smartphones; verifiability; Cryptography; Mobile communication; Mobile computing; Privacy; Protocols; Servers; Social network services;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INFOCOM, 2011 Proceedings IEEE
Conference_Location :
Shanghai
ISSN :
0743-166X
Print_ISBN :
978-1-4244-9919-9
Type :
conf
DOI :
10.1109/INFCOM.2011.5934958
Filename :
5934958
Link To Document :
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