Sybil node identification algorithm using connectivity threshold for secured community mining in social network

Sybil attack is one of the most common attacks in the social networking systems. A user can create multiple duplicate accounts in social networking sites. This is known as Sybil attack. These Sybil accounts are created to illegitimately increase the control or resources of an unknown malicious user over the certain community. Most of the social networking sites are not having a powerful mechanism to prevent Sybil attacks because most of the sites are open to all users. Identifying Sybil nodes in a network is a huge problem. Several researches are carried out to analyze this problem in online social network communities. In this paper we analyzed various Sybil identification strategies which are used in online social network. We proposed a new strategy for Sybil identification in social networks. That is, Sybil identification using connectivity threshold algorithm (SICT). We established the connection between the nodes. Connection threshold values are calculated and compared with the other nodes in a network. The value exceeds the threshold a value is represented as Sybil node. The proposed method evaluated by using two real world networks data sets and results show that our proposed algorithm performs well to find the Sybil nodes compared to the other existing methods.