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Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.071207
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 12, 2016.
Abstract: Wireless sensor network (WSN) has been broadly implemented in real world applications, such as monitoring of forest fire, military targets detection, medical and/or science areas and above all in our daily home life as well. Nevertheless, WSNs are effortlessly compromised by adversaries due to their broadcast transmission medium as a means of communication which are lacking in tamper resistance. Consequently, an intruder can over hear all traffic, replay previous messages, inject malicious data packets, or can compromise a node. Commonly, sensor nodes are very much vulnerable of two main issues in security aspect that are node authentication and compromising a node. In this paper, a heterogeneous framework of node capture and intrusion detection for WSNs is proposed. This framework efficiently detects the captured nodes by using a novel technique, embedded with an Intrusion Detection mechanism which aggregates Signature and Anomaly based approach with Neural Network Multi-Layer Perceptron (MLP) classification in a clustering environment. Moreover, the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a security shield to real WSN applications.
Mustafa Al-Fayoumi, Yasir Ahmad and Usman Tariq, “A Heterogeneous Framework to Detect Intruder Attacks in Wireless Sensor Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071207