IRIS: A Novel Method of Direct Trust Computation for Generating Trusted Social Networks

Improving trust in social networks appears as the first step toward addressing the existing confidence and privacy concerns related to online social networks. Direct trust is used to develop different trust-based methods such as transitivity and access control, however how to compute direct trust levels is rarely discussed in the literature. To address some of the current limitations, we introduce a novel approach for generating trusted social networks and we compute trust levels between users having direct relationships. Experimental results with data extracted from FOAF files show that our work presents high accuracy.