Detection and Elimination of Black Hole Attack in WSN
S.Ilavarasan1, P.Latha2
1Mr.S.Ilavarasan*, Assistant Professor(SG) in the Department of IT, Saveetha Engineering College, Chennai
2Dr.P.Latha, Professor in the Department of IT, Saveetha Engineering College, Chennai
Manuscript received on October 16, 2019. | Revised Manuscript received on 27 October, 2019. | Manuscript published on November 10, 2019. | PP: 1377-1382 | Volume-9 Issue-1, November 2019. | Retrieval Number: L39081081219/2019©BEIESP | DOI: 10.35940/ijitee.L3908.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Wireless Sensor Network has become one of the most emerging areas of research in recent days. WSNs have been applied in a variety of application areas such as military, traffic surveillance, environment monitoring and so on. Since WSN is not a secure network and each sensor node can be compromised by the intruder. There are plenty of security threats in sensor networks like Black hole Attack, Wormhole attack, Sinkhole attack. Recently, there are so many algorithms are proposed to detect or to prevent attack by the researchers. Still, the research is continuing to evaluate sensor nodes’ trust and reputation. At present to monitor nodes’ behavior direct and indirect trust values are used and most of the detection method uses additional nodes to detect an attack. These method increases the cost and also overhead. This paper proposed a method which detects the Black hole attack without using any additional node to monitor the network. The proposed work uses Attacker Detection metric (AD metric) to detect malicious node based on the average sequence number, time delay and reliability. OLSR protocol is used for routing which improves the network lifetime by minimizing the packet flooding. Besides, to ensure reliable data transmission Elliptical Curve Digital Signature Algorithm is used. Simulation results are obtained and show malicious nodes are eliminated using AD metrics
Keywords: AD metrics, OLSR, Black hole attack, ECDSA Algorithm
Scope of the Article: Algorithm Engineering