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Grey Hole Attack Detection and Prevention Methods in Wireless Sensor Networks

Gowdham Chinnaraju*, S. Nithyanandam

Department of Computer Science and Engineering, PRIST Deemed to be University, 613403, India

* Corresponding Author: Gowdham Chinnaraju. Email: email

Computer Systems Science and Engineering 2022, 42(1), 373-386. https://doi.org/10.32604/csse.2022.020993

Abstract

Wireless Sensor Networks (WSNs) gained wide attention in the past decade, thanks to its attractive features like flexibility, monitoring capability, and scalability. It overcomes the crucial problems experienced in network management and facilitates the development of diverse network architectures. The existence of dynamic and adaptive routing features facilitate the quick formation of such networks. But flexible architecture also makes it highly vulnerable to different sorts of attacks, for instance, Denial of Service (DoS). Grey Hole Attack (GHA) is the most crucial attack types since it creates a heavy impact upon the components of WSN and eventually degrades the performance of network. In current study, a simple attack detection, prevention and reduction approach is proposed. This is to secure the WSN from GHA and other such attacks by warning and blocking the malicious suspensions and by examining the storage table. Instead of blocking the entire host, the presented approach specifically eliminates the malicious nodes. Further, in case of no malicious traffic detection, the host gets unblocked. In current study, the researchers simulated the model under MATLAB environment and the outcomes showed an enhanced performance and increased utilization of Central Processing Unit (CPU) and packet delivery ratio.

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Cite This Article

G. Chinnaraju and S. Nithyanandam, "Grey hole attack detection and prevention methods in wireless sensor networks," Computer Systems Science and Engineering, vol. 42, no.1, pp. 373–386, 2022. https://doi.org/10.32604/csse.2022.020993



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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