Cited By
View all- Abu Khalil DAbuzir Y(2024)Detecting and Analyzing Network Attacks: A Time-Series Analysis Using the Kitsune DatasetJournal of Emerging Computer Technologies10.57020/ject.15631465:1(9-23)Online publication date: 2-Nov-2024
Deep Learning-Based Anomaly Detection in Network Traffic for Cyber Threat Identification
Authors: 
Luay Ibrahim Khalaf, Baydaa Alhamadani, Omar Ayad Ismael, Ahmed A. Radhi, Saadaldeen Rashid Ahmed, Sameer AlgburiAuthors Info & Claims
Pages 303 - 309
Abstract
An essential aspect of cybersecurity is the continuously growing threat landscape, which necessitates the use of advanced anomaly detection techniques in network data. The traditional approach might often be inadequate when it comes to addressing intricate cyber-security issues. Therefore, it is possible that deep learning approaches might be superior in terms of accuracy and performance. The primary objective of our study is to provide a novel algorithm that combines Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), autoencoders, and GANs to create a comprehensive strategy for detecting anomalies. This technique aims to solve research gaps that have not been previously explored. By using the MTA-KDD'19 dataset, our research enhances precision by achieving a remarkable accuracy rate of 95% in detecting various types of network traffic abnormalities. This discovery not only demonstrated the harmfulness of our deep learning-based approach but also highlighted the effectiveness of these measures in reducing the issue, particularly when faced with diverse threats. This enhances the development of network security procedures.
CCS CONCEPTS • Computing methodologies∼ Artificial intelligence • Security and privacy∼Network security
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https://paperswithcode.com/dataset/mta-kdd-19
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Published In
May 2024
367 pages
ISBN:9798400716928
DOI:10.1145/3660853
Copyright © 2024 ACM.
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Published: 23 June 2024
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AICCONF '24
AICCONF '24: Cognitive Models and Artificial Intelligence Conference
May 25 - 26, 2024
İstanbul, Turkiye
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View all- Abu Khalil DAbuzir Y(2024)Detecting and Analyzing Network Attacks: A Time-Series Analysis Using the Kitsune DatasetJournal of Emerging Computer Technologies10.57020/ject.15631465:1(9-23)Online publication date: 2-Nov-2024
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