Sybil attack Detection: Improving security of WSNs for smart power grid application

For a large number of sensor network applications security is crucial, especially if the sensor network protects or monitors critical infrastructures such as electric power infrastructure. Smart grid revolutionizes the current electric power infrastructure by the use of wireless sensor networks. Sybil attack is one of the most disrupting attacks in the context of wireless sensor networks. In this attack a malicious node forges multiple identities and therefore disrupts many network protocols such as routing, voting, data aggregation and misbehavior detection. This attack can make several forms of attacks possible. It is also problematic for protocols that rely on voting schemes. Therefore a security mechanism against this attack for wireless sensor networks is mandatory. In this paper we introduced a novel approach called SDTM (Sybil attack Detection using Traffic Monitoring) in a neighbor-based detection manner to detect such attacks. This approach is based on the traffic density around nodes and uses statistical methods to detect the malicious nodes. For simulating our network we used OMNeT++ simulator. After 80 simulations the proposed mechanism (SDTM) achieved a 95.13% detection rate and a 2.29% misdetection rate. we have shown that the occurrence of a Sybil attack using this method is detectable.