Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Neural Network-Based Deep Learning for Online Payment Fraud Detection

Neural Network-Based Deep Learning for Online Payment Fraud Detection

Xie, Yu
Tian, Yue
Yao, Jiamin

Hardcover

Business GeneralGeneral Computers

ISBN10: 9819585120
ISBN13: 9789819585120
Publisher: Springer
Published: May 16 2026
Pages: 185
Weight: 1.01
Height: 0.50 Width: 6.14 Depth: 9.21
Language: English
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.

Also from

Xie, Yu

View All

Also in

Business General

View All