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Class-Specific GAN-Based Minority Data Augmentation for Cyberattack Detection Using the UWF-ZeekData22 Dataset

Intrusion detection systems (IDS) often struggle to detect rare but high-impact attack behaviors due to severe class imbalance in real-world network traffic. This work proposes a class-specific GAN-based augmentation framework that explicitly targets sparsity in the minority-class in structured cybe...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Asfaw Debelie, Sikha S. Bagui, Dustin Mink, Subhash C. Bagui
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2026-02-01
Schriftenreihe:Technologies
Schlagworte:
cybersecurity
intrusion detection
class imbalance
generative adversarial networks
data augmentation
minority-class leaning
Online-Zugang:https://www.mdpi.com/2227-7080/14/2/117
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