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Neural Network-Based Deep Learning for Online Payment Fraud Detection
Yu Xie, Yue Tian, Jiamin Yao, Guanjun Liu
Livre relié | Anglais
128,45 €
+ 256 points
Description
This book explores deep learning as a next-generation approach to online payment fraud detection in the face of increasingly complex and adaptive threats. Traditional rule-based or shallow learning methods are no longer sufficient. Through ten focused chapters, this book tackles challenges such as behavioral modeling, spatiotemporal anomaly detection, class imbalance, behavior drift, and graph-based inference. It applies advanced neural architectures including LSTM, GRU, GANs, GNNs, and spatiotemporal transformers. With a problem-driven structure, each chapter links real-world fraud problems to tailored neural solutions, validated on large-scale transaction data. This book blends theory, practical design, and empirical rigor, offering researchers and practitioners a foundation for scalable, adaptive, and reliable fraud detection systems.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Langue:
- Anglais
Caractéristiques
- EAN:
- 9789819585120
- Date de parution :
- 11-08-26
- Format:
- Livre relié
- Dimensions :
- 155 mm x 235 mm
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