Class-Specific GAN Augmentation for Imbalanced Intrusion Detection: A Comparative Study Using the UWF-ZeekData22 Dataset

Extreme class imbalance is a persistent obstacle for machine learning-driven intrusion detection, as rare but high-impact cyberattacks occur far less frequently than benign traffic in training data. In many real-world cybersecurity datasets, this imbalance becomes extreme, with certain attack types...

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Principais autores:	Asfaw Debelie, Sikha S. Bagui, Dustin Mink, Subhash C. Bagui
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-04-01
coleção:	Future Internet
Assuntos:	cybersecurity intrusion detection class imbalance generative adversarial networks (GAN) class-specific data augmentation minority-class learning
Acesso em linha:	https://www.mdpi.com/1999-5903/18/4/200
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