DOI: https://doi.org/10.14710/ijred.8.1.57-64

Detection of Attacks on Wireless Sensor Network Using Genetic Algorithms Based on Fuzzy

1Altinbas University, Istanbul, Turkey

2Turkish Aeronautical Association University, Ankara, Turkey

Published: 2 Feb 2019.
Editor(s): H Hadiyanto

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Abstract

In this paper an individual - suitable function calculating design for WSNs is conferred. A multi-agent- located construction for WSNs is planned and an analytical type of the active combination is built for the function appropriation difficulty. The purpose of this study is to identify the threats identified by clustering genetic algorithms in clustering networks, which will prolong network lifetime. In addition, optimal routing is done using the fuzzy function. Simulation results show that the simulated genetic algorithm improves diagnostic speed and improves energy consumption.

©2019. CBIORE-IJRED. All rights reserved

Article History: Received May 16th 2018; Received in revised form October 6th 2018; Accepted January 6th 2019; Available online

How to Cite This Article: Al-Hayali, S., Ucan, O., Rahebi, J. and Bayat, O. (2019) Detection of Attacks on Wireless Sensor Network Using Genetic Algorithms Based on Fuzzy. International Journal of Renewable Energy Development, 8(1), 57-64.

https://doi.org/10.14710/ijred.8.1.57-64

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Keywords: wireless sensor network; fuzzy, genetic algorithm; detection of attack; malicious node

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Section: Original Research Article
Language : EN
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Last update: 2024-11-21 10:28:31

  1. Improved Performance Using Fuzzy Possibilistic C-Means Clustering Algorithm in Wireless Sensor Network

    Shweta Kushwaha, Kuldeep Singh Jadon. 2020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT), 2020. doi: 10.1109/CSNT48778.2020.9115740