ESSDM: an Efficient Mechanism for Handling Sybil Attacks in Social Networks
B. Dhivya, S. Justin Samuel, M. Karthiga · International Review on Computers and Software (IRECOS) · 2014
Social networks are becoming more popular platforms for communication, interaction and collaboration among relatives & friends. Researchers have recently come out with an emerging class of technology that leverage relationships from social networks to improve security in applications such as electronic mail, overlay routing and web browsing. Peer-to-peer systems are mostly vulnerable to Sybil attacks. The Sybil attack is an attack where an adversary creates multiple Duplicate or False identities to compromise the running of the system. By including false information by the Duplicated entities, an adversary can mislead a system into making decisions benefiting. Defending against Sybil attacks is quite challenging. Over the last few years, there are so many approaches suggested to overcome such issues of fake user behavior but there remain some issues unaddressed. This work gives a novel Sybil attack detection and removal mechanism based on behavioral analysis and neighbor similarity calculation named Enhanced Similarity based Sybil Detection Mechanism (ESSDM). In this approach, neighbor nodes acquainting with more familiarity are identified as the duplicated Sybil nodes. By applying our enhanced similarity based Sybil detection mechanism, the results show that the Sybil attack is considerably minimized, thereby improving security and its performance level.