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A privacy-preserving fuzzy interest matching protocol for friends finding in social networks
Wang, Xu An; Xhafa Xhafa, Fatos; Luo, Xiaoshuang; Zhang, Shuaiwei; Ding, Yong
Universitat Politècnica de Catalunya. Departament de Ciències de la Computació
Nowadays, it is very popular to make friends, share photographs, and exchange news throughout social networks. Social networks widely expand the area of people’s social connections and make communication much smoother than ever before. In a social network, there are many social groups established based on common interests among persons, such as learning group, family group, and reading group. People often describe their profiles when registering as a user in a social network. Then social networks can organize these users into groups of friends according to their profiles. However, an important issue must be considered, namely many users’ sensitive profiles could have been leaked out during this process. Therefore, it is reasonable to design a privacy-preserving friends-finding protocol in social network. Toward this goal, we design a fuzzy interest matching protocol based on private set intersection. Concretely, two candidate users can first organize their profiles into sets, then use Bloom filters to generate new data structures, and finally find the intersection sets to decide whether being friends or not in the social network. The protocol is shown to be secure in the malicious model and can be useful for practical purposes.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica
Online social networks
Data protection
Internet--Security measures
Xarxes socials en línia
Protecció de dades
Internet--Mesures de seguretat
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