Open Access iconOpen Access

ARTICLE

An Optimized and Hybrid Framework for Image Processing Based Network Intrusion Detection System

Murtaza Ahmed Siddiqi, Wooguil Pak*

Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Korea

* Corresponding Author: Wooguil Pak. Email: email

Computers, Materials & Continua 2022, 73(2), 3921-3949. https://doi.org/10.32604/cmc.2022.029541

Abstract

The network infrastructure has evolved rapidly due to the ever-increasing volume of users and data. The massive number of online devices and users has forced the network to transform and facilitate the operational necessities of consumers. Among these necessities, network security is of prime significance. Network intrusion detection systems (NIDS) are among the most suitable approaches to detect anomalies and assaults on a network. However, keeping up with the network security requirements is quite challenging due to the constant mutation in attack patterns by the intruders. This paper presents an effective and prevalent framework for NIDS by merging image processing with convolution neural networks (CNN). The proposed framework first converts non-image data from network traffic into images and then further enhances those images by using the Gabor filter. The images are then classified using a CNN classifier. To assess the efficacy of the recommended method, four benchmark datasets i.e., CSE-CIC-IDS2018, CIC-IDS-2017, ISCX-IDS 2012, and NSL-KDD were used. The proposed approach showed higher precision in contrast with the recent work on the mentioned datasets. Further, the proposed method is compared with the recent well-known image processing methods for NIDS.

Keywords


Cite This Article

APA Style
Siddiqi, M.A., Pak, W. (2022). An optimized and hybrid framework for image processing based network intrusion detection system. Computers, Materials & Continua, 73(2), 3921-3949. https://doi.org/10.32604/cmc.2022.029541
Vancouver Style
Siddiqi MA, Pak W. An optimized and hybrid framework for image processing based network intrusion detection system. Comput Mater Contin. 2022;73(2):3921-3949 https://doi.org/10.32604/cmc.2022.029541
IEEE Style
M.A. Siddiqi and W. Pak, "An Optimized and Hybrid Framework for Image Processing Based Network Intrusion Detection System," Comput. Mater. Contin., vol. 73, no. 2, pp. 3921-3949. 2022. https://doi.org/10.32604/cmc.2022.029541



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
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.
  • 1704

    View

  • 773

    Download

  • 0

    Like

Share Link