A Novel Two-Stage Algorithm Protecting Internal Attack from WSNs

Abstract

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

A Survey on Security Requirements for WSNs: Focusing on the Characteristics Related to Security

“…Many researchers know that it is important to identify malicious intentions. To this end, many researches are undertaken based on abnormal behavior identification mechanism (ABIM) and dempster-shafer theory (DST) [69].…”