A Trust-Based Privacy-Preserving Friend Recommendation Scheme for Online Social Networks

Online social networks (OSNs), which attract thousands of million people to use everyday, greatly extend OSN users´ social circles by friend recommendations. OSN users´ existing social relationship can be characterized as 1-hop trust relationship, and further establish a multi-hop trust chain during the recommendation process. As the same as what people usually experience in the daily life, the social relationship in cyberspaces are potentially formed by OSN users´ shared attributes, e.g., colleagues, family members, or classmates, which indicates the attribute-based recommendation process would lead to more fine-grained social relationships between strangers. Unfortunately, privacy concerns raised in the recommendation process impede the expansion of OSN users´ friend circle. Some OSN users refuse to disclose their identities and their friends´ information to the public domain. In this paper, we propose a trust-based privacy-preserving friend recommendation scheme for OSNs, where OSN users apply their attributes to find matched friends, and establish social relationships with strangers via a multi-hop trust chain. Based on trace-driven experimental results and security analysis, we have shown the feasibility and privacy preservation of our proposed scheme.