An enhanced BiGAN architecture for network intrusion detection

Intrusion detection systems face significant challenges in handling high-dimensional, large-scale, and imbalanced network traffic data. This paper proposes a new architecture combining a denoising autoencoder (AE) and a Wasserstein Generative Adversarial Network (WGAN) to address these challenges. T...

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Bibliographic Details

Main Authors:	Mohammad Arafah, Iain Phillips, Asma Adnane, Mohammad Alauthman, Nauman Aslam
Format:	Default Article
Published:	2025
Subjects:	Commerce, management, tourism and services Information and computing sciences Artificial intelligence Data management and data science Machine learning Psychology Artificial Intelligence & Image Processing AIDS WGAN NSL-KDD CIC-IDS2017 Imbalanced Dataset Synthetic Attacks
Online Access:	https://hdl.handle.net/2134/28524851.v1
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