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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. In this paper, the authors 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, they do not need any predefined threshold or tanning data set of the nodes.
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