Exploiting Private Profile Matching for Efficient Packet Forwarding in Mobile Social Networks

2014 ◽  
pp. 283-311 ◽  
Author(s):  
Kuan Zhang ◽  
Xiaohui Liang ◽  
Rongxing Lu ◽  
Xuemin Shen
Keyword(s):  
Social Networks ◽  
Packet Forwarding ◽  
Mobile Social Networks ◽  
Profile Matching

scholarly journals Fully Anonymous Profile Matching in Mobile Social Networks

2013 ◽  
Vol 31 (9) ◽  
pp. 641-655 ◽  
Author(s):  
Xiaohui Liang ◽  
Xu Li ◽  
Kuan Zhang ◽  
Rongxing Lu ◽  
Xiaodong Lin ◽  
...  
Keyword(s):  
Social Networks ◽  
Mobile Social Networks ◽  
Profile Matching

scholarly journals Private Profile Matching for Mobile Social Networks Based on Fuzzy Extractors

10.29007/st23 ◽  
2018 ◽  
Author(s):  
Jaweher Zouari ◽  
Mohamed Hamdi ◽  
Tai-Hoon Kim
Keyword(s):  
Social Networks ◽  
Privacy Preservation ◽  
Homomorphic Encryption ◽  
Mobile Social Networks ◽  
Fuzzy Extractor ◽  
Mobile Social Networking ◽  
Profile Matching ◽  
Novel Approach ◽  
Privacy Breaches ◽  
Fuzzy Extractors

Interacting with geographically proximate users who present similar interests and preferences is a key service offered by mobile social networks which leads to the creation of new connections that combine physical and social closeness. Usually these interactions are based on social profile matching where users publish their preferences and attributes to enable the search for a similar profile. Such public search would result in the leakage of sensitive or identifiable information to strangers who are not always potential friends. As a consequence this promising feature of mobile social networking may cause serious privacy breaches if not addressed properly. Most existent work relies on homomorphic encryption for privacy preservation during profile matching, while we propose in this paper a novel approach based on the fuzzy extractor which performs private matching of two sets and reveals them only if they overlap considerably. Our scheme achieves a desirable trade off between security and complexity.

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