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Article

A Novel Approach for Network Intrusion Detection Using Multistage Deep Learning Image Recognition

1
Department of Computer Science, Kaunas University of Technology, 51386 Kaunas, Lithuania
2
Department of Software Engineering, Kaunas University of Technology, 51386 Kaunas, Lithuania
3
Ignitis, 52374 Kaunas, Lithuania
*
Author to whom correspondence should be addressed.
Academic Editors: Constantinos Kolias, Georgios Kambourakis and Weizhi Meng
Electronics 2021, 10(15), 1854; https://doi.org/10.3390/electronics10151854
Received: 5 July 2021 / Revised: 29 July 2021 / Accepted: 30 July 2021 / Published: 1 August 2021
(This article belongs to the Special Issue Design of Intelligent Intrusion Detection Systems)
The current rise in hacking and computer network attacks throughout the world has heightened the demand for improved intrusion detection and prevention solutions. The intrusion detection system (IDS) is critical in identifying abnormalities and assaults on the network, which have grown in size and pervasiveness. The paper proposes a novel approach for network intrusion detection using multistage deep learning image recognition. The network features are transformed into four-channel (Red, Green, Blue, and Alpha) images. The images then are used for classification to train and test the pre-trained deep learning model ResNet50. The proposed approach is evaluated using two publicly available benchmark datasets, UNSW-NB15 and BOUN Ddos. On the UNSW-NB15 dataset, the proposed approach achieves 99.8% accuracy in the detection of the generic attack. On the BOUN DDos dataset, the suggested approach achieves 99.7% accuracy in the detection of the DDos attack and 99.7% accuracy in the detection of the normal traffic. View Full-Text
Keywords: network intrusion detection; deep learning; image representation network intrusion detection; deep learning; image representation
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MDPI and ACS Style

Toldinas, J.; Venčkauskas, A.; Damaševičius, R.; Grigaliūnas, Š.; Morkevičius, N.; Baranauskas, E. A Novel Approach for Network Intrusion Detection Using Multistage Deep Learning Image Recognition. Electronics 2021, 10, 1854. https://doi.org/10.3390/electronics10151854

AMA Style

Toldinas J, Venčkauskas A, Damaševičius R, Grigaliūnas Š, Morkevičius N, Baranauskas E. A Novel Approach for Network Intrusion Detection Using Multistage Deep Learning Image Recognition. Electronics. 2021; 10(15):1854. https://doi.org/10.3390/electronics10151854

Chicago/Turabian Style

Toldinas, Jevgenijus, Algimantas Venčkauskas, Robertas Damaševičius, Šarūnas Grigaliūnas, Nerijus Morkevičius, and Edgaras Baranauskas. 2021. "A Novel Approach for Network Intrusion Detection Using Multistage Deep Learning Image Recognition" Electronics 10, no. 15: 1854. https://doi.org/10.3390/electronics10151854

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