Title
Efficient Customized Privacy Preserving Friend Discovery in Mobile Social Networks
Abstract
Mobile social networks have been increasingly popular with the explosive growth of mobile devices. Mobile users are allowed to interact with potential friends within a certain distance. Motivated by this feature, many exciting applications have been developed, yet the challenge of privacy protection is thus aroused. In this paper, we propose an efficient customized privacy preserving friend discovery mechanism, which not only protects the privacy of users' profile, but also establishes a verifiable secure communication channel between matched users. Besides, the initiator has the freedom to set a customized request profile by choosing the interested attributes and giving each attribute a specific value. Moreover, the request profile's privacy protection level is customized by the initiator according to his/her own privacy requirements. We also consider the collusion attacks among unmatched users. To the best of our knowledge, this is the first work to address such a security threat. Our protocol guarantees that only exactly matched users are able to communicate with the initiator securely, while little information can be obtained by other participants. To increase the matching efficiency, our design adopts the Bloom filter to efficiently exclude most unmatched users. As a result, our design effectively protects the profile privacy and efficiently decreases the computational overhead. Security analysis and performance evaluation are conducted to justify the superiority of our protocol.
Year
DOI
Venue
2015
10.1109/ICDCS.2015.31
International Conference on Distributed Computing Systems
Keywords
Field
DocType
Mobile social networks, privacy preservation, Attribute Based Encryption, secure friend discovery
Mobile computing,Bloom filter,Computer security,Computer science,Attribute-based encryption,Computer network,Security analysis,Mobile device,Information privacy,Privacy software,Secure communication,Distributed computing
Conference
ISSN
Citations 
PageRank 
1063-6927
2
0.36
References 
Authors
27
4
Name
Order
Citations
PageRank
Hongjuan Li123511.71
Xiuzhen Cheng23238210.23
Keqiu Li31415162.02
Zhi Tian411514.04