FlowTrust: Trust Inference With Network Flows
Web-based social networking is increasingly gaining popularity due to the rapid development of computer networking technologies. However, social networking applications still cannot obtain a wider acceptance by many users due to some unresolved issues, such as trust, security, and privacy. Trust, in social networks, mainly studies whether a remote user, called a trustee, behaves as expected by an interested user, called a trustor, through other users, called recommenders. A trusted graph consists of a trustor, a trustee, recommenders, and trust relationships among them. In this paper, the authors propose a novel FlowTrust approach to model a trusted graph with network flows, and evaluate the maximum amount of trust that can flow among a trusted graph using the network flow theory. FlowTrust supports multidimensional trust.