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

*Shaymaa Al Hayali  -  Altinbas University, Istanbul, Turkey
Osman Ucan  -  Altinbas University, Istanbul, Turkey
Javad Rahebi  -  Turkish Aeronautical Association University, Ankara, Turkey
Oguz Bayat  -  Altinbas University, Istanbul, Turkey
Published: 2 Feb 2019.
Open Access Copyright (c) 2019 International Journal of Renewable Energy Development

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Section: Original Research Article
Language: EN
Statistics: 832 449

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.

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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.

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

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