A Smart Trust Based Approach for Sybil Node Detection in Online Social Networks

Forged identities (Sybil) have the potential to damage the trust of the platform in the long run by doing malicious works. Owing to the severity of the threats posed by these Sybil nodes, various graph based mechanisms have been proposed to identify them. However, these approaches are more suitable for the classical scenario which considers that it is difficult to establish the linkage between sybil and honest nodes. Contrary to this assumption, the modern scenario assumes that such linkage can be easily established using simple strategies. The work proposed in this paper makes use of a trust based approach to detect sybil nodes in an online social network. The proposed approach is more suitable for the modern scenarios since the strategies to link sybil and honest nodes are based upon the concept of the trustworthiness of the nodes. The proposed approach calculates aggregate trust value of the nodes which is further compared with a benchmark threshold value for deciding whether the node is Sybil or Benign. The proposed model has been theoretically analyzed and the obtained results clearly exhibit the efficiency of the proposed work over the existing approaches.