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A Novel Forward-Propagation Workflow Assessment Method for Malicious Packet Detection.

Nagaiah Mohanan Balamurugan¹, Raju Kannadasan², Mohammed H Alsharif³

¹Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Sriperumbudur, Chennai 602117, India.

Sensors (Basel, Switzerland)

|June 10, 2022

Summary

This study introduces a novel Convolutional Neural Network (CNN) forward-propagation method for enhanced malicious network data detection. The CNN approach significantly outperforms K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) algorithms in accuracy and precision.

Keywords:

convolutional neural network deep learning k-nearest neighbor machine learning novel forward propagation support vector machine

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Area of Science:

Computer Science
Cybersecurity
Artificial Intelligence

Background:

Digital network data transmission faces increasing sophisticated malicious attacks.
Existing detection methods require innovative solutions to combat evolving threats.

Purpose of the Study:

To propose and evaluate a novel method using Convolutional Neural Network (CNN) forward-propagation for effective malicious information detection.
To compare the performance of the proposed CNN method against K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) algorithms.

Main Methods:

An experiment was conducted using the CNN forward-propagation workflow on a dataset (N=11) to detect malicious packets.
Performance was evaluated using accuracy, precision, false-positive rate, and false-negative rate.
Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS).

Main Results:

The CNN forward-propagation method achieved a mean accuracy of 98.84% and mean precision of 99.08%.
These results were superior to KNN (accuracy 95.55%, precision 95.97%) and SVM (accuracy 94.43%, precision 94.58%).
The proposed CNN method demonstrated lower false-positive (1.93%) and false-negative (3.49%) rates compared to KNN and SVM.

Conclusions:

The forward-propagation method of the CNN algorithm is a highly effective technique for detecting malicious information in digital networks.
CNN significantly outperforms traditional machine learning algorithms like KNN and SVM in identifying malicious data packets.
The proposed method offers improved accuracy and precision with reduced error rates for network security.