Detecting Sybil attacks in Wireless Sensor Networks using neighboring information

As the prevalence of Wireless Sensor Networks (WSNs) grows in the military and civil domains, the need for network security has become a critical concern. In a Sybil attack, the WSN is subverted by a malicious node which forges a large number of fake identities in order to disrupt the network's protocols. In attempting to protect WSNs against such an attack, this paper develops a scheme in which the node identities are verified simply by analyzing the neighboring node information of each node. The analytical results confirm the efficacy of the approach given a sufficient node density within the network. The simulation results demonstrate that for a network in which each node has an average of 9 neighbors, the scheme detects 99% of the Sybil nodes with no more than a 4% false detection rate. The experiment result shows that the Sybil nodes can still be identified when the links are not symmetric.