Improved Energy Intrusion Detection System using Fuzzy System in Wireless Sensor Network
J. Santhosh1, G. Arulkumaran2, P. Balamurugan3
1J. Santhosh, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Avadi, Chennai (Tamil Nadu), India.
2G. Arulkumaran, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Avadi, Chennai (Tamil Nadu), India.
3P. Balamurugan, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Avadi, Chennai (Tamil Nadu), India.
Manuscript received on 15 December 2018 | Revised Manuscript received on 27 December 2018 | Manuscript Published on 24 January 2019 | PP: 333-338 | Volume-7 Issue-4S2 December 2018 | Retrieval Number: Es2076017519/19©BEIESP
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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 (WSN) are predominantly used in collecting information from remote regions. As the data is transmitted in unsecured wireless medium, it is more susceptible for attacks. The distribution of the nodes in WSN eases the task for the attackers to alter the node characteristics and behaviour. This malicious node is a severe threat in terms of data security and resource management to the entire WSN, in which it is deployed. The proposed Co-Active Adaptive Neuro Fuzzy Inference System (CANFIS) is an energy efficient malicious node detection method that detects the presence of malicious nodes in WSNs by considering the space metrics and heuristic features of nodes. The proposed method performance is investigated in provisos of its packet delivery ratio, detection rate and energy consumption, which shows a remarkable progress over the other state of art methods.
Keywords: Wireless Sensor Networks, Malicious Nodes, Energy Efficient, Cluster Head.
Scope of the Article: Fuzzy Logics