Machine Learning Methods for Intrusive Detection of Wormhole Attack in Mobile Ad Hoc Network (MANET)

Masoud Abdan,Seyed Amin Hosseini Seno,Lihua Yin

doi:10.1155/2022/2375702

Masoud Abdan, Seyed Amin Hosseini Seno + Show 1 more

Open Access

https://doi.org/10.1155/2022/2375702

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Abstract

A wormhole attack is a type of attack on the network layer that reflects routing protocols. The classification is performed with several methods of machine learning consisting of K -nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), linear discrimination analysis (LDA), naive Bayes (NB), and convolutional neural network (CNN). Moreover, we used nodes’ properties for feature extraction, especially nodes’ speed, in the MANET. We have collected 3997 distinct (normal 3781 and malicious 216) samples that comprise normal and malicious nodes. The classification results show that the accuracy of the KNN, SVM, DT, LDA, NB, and CNN methods are 97.1%, 98.2%, 98.9%, 95.2%, 94.7%, and 96.4%, respectively. Based on our findings, the DT method’s accuracy is 98.9% and higher than other ways. In the next priority, SVM, KNN, CNN, LDA, and NB indicate high accuracy, respectively.

Highlights

A MANET is a series of wirelessly interconnected, self-arranged nodes
The results of classification with several methods of machine learning consisting of K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), linear discrimination analysis (LDA), naive Bayes (NB), and convolutional neural network (CNN) are Create MANET network nodes Add wormhole nodes Set rules to monitor wormhole activity Capture all data Feature extraction of MANET nodes using KNN, SVM, DT, LDA, NB and CNN Performance analysis
The results show that the accuracy of the KNN, SVM, DT, LDA, NB, and CNN methods are 97.1%, 98.2%, 98.9%, 95.2%, 94.7%, and 96.4%, respectively

Summary

Introduction

A MANET (mobile ad hoc network) is a series of wirelessly interconnected, self-arranged nodes. Each movable node is a node that is self-managed, and there is no central mobile network management node. Based on their need, the mobile nodes have permission to go somewhere. The mobile nodes have permission to go somewhere It makes it possible for the nodes to join or exit the network [1] quickly. Because of shared channel illumination, unconfident operating environment, restricted resource mobility, rapidly evolving device topology, resource-limited [3], ad hoc wireless mobile networks are susceptible to many security threats

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