Hybrid Generative Adversarial Network Assisted Oversampling for Credit Card Fraud Detection

Credit-card fraud detection is a challenging task due to the highly imbalanced nature of real-world transaction data, where fraudulent cases constitute a tiny fraction of the total. In this study, we address this challenge using the publicly available Credit Card Fraud Detection dataset from Kaggle,...

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Autores principales:	Eman Abdullah Aldakheel, Ahmed M. Osman, Safia Abbas, Yasser Fouad, Ahmed M. Elshewey
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	IEEE 2026-01-01
Colección:	IEEE Access
Materias:	Credit card fraud detection imbalanced data classification generative adversarial network transaction anomaly detection financial cybersecurity GAN
Acceso en línea:	https://ieeexplore.ieee.org/document/11471296/
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