Grey Hole Attack Detection and Prevention Methods in Wireless Sensor Networks

Gowdham Chinnaraju,S Nithyanandam

doi: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.

Highlights

Wireless Sensor Networks are decentralized in nature and are appropriate for different kinds of applications since the centralized nodes cannot be trusted
Grey Hole Attack (GHA) is the most crucial attack types since it creates a heavy impact upon the components of Wireless Sensor Networks (WSNs) and eventually degrades the performance of network
The total number of Grey Hole Attack hosts was provided for various scenarios that cause constant flooding to consume high power and resources

Summary

Introduction

Wireless Sensor Networks are decentralized in nature and are appropriate for different kinds of applications since the centralized nodes cannot be trusted. WSNs exhibit network scalability feature i.e., it can be connected with networks of huge size, whereas the whole networks should be recognized [1]. With the availability of dynamic and adaptive routing facilities, one can create the network quickly. WSN frequently encounters packet drop-based attacks in which the host may broadcast the packets in case of encountering a short path [4]. The traffic which is directed at the host, is compromised. Hosts are susceptible to collaborative attacks and may be compromised due to which it may pass wrong information to the network.

Methods

Results

Conclusion