A Novel Two-Stage Algorithm Protecting Internal Attack from WSNs

Wireless sensor networks (WSNs) consists of small nodes with constrain capabilities. It enables numerousapplications with distributed network infrastructure. With its nature and application scenario, security ofWSN had drawn a great attention. In malicious environments for a functional WSN, security mechanismsare essential. Malicious or internal attacker has gained attention as the most challenging attacks toWSNs. Many works have been done to secure WSN from internal attacks but most of them relay on eithertraining data set or predefined thresholds. It is a great challenge to find or gain knowledge about theMalicious. In this paper, we develop the algorithm in two stages. Initially, Abnormal BehaviourIdentification Mechanism (ABIM) which uses cosine similarity. Finally, Dempster-Shafer theory (DST)isused. Which combine multiple evidences to identify the malicious or internal attacks in a WSN. In thismethod we do not need any predefined threshold or tanning data set of the nodes.