Adaptive, Privacy-Enhanced Real-Time Fraud Detection in Banking Networks Through Federated Learning and VAE-QLSTM Fusion

Adaptive, Privacy-Enhanced Real-Time Fraud Detection in Banking Networks Through Federated Learning and VAE-QLSTM Fusion

Increased digital banking operations have brought about a surge in suspicious activities, necessitating heightened real-time fraud detection systems. Conversely, traditional static approaches encounter challenges in maintaining privacy while adapting to new fraudulent trends. In this paper, we provi...

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Bibliographic Details
Main Authors: Hanae Abbassi, Saida El Mendili, Youssef Gahi
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Big Data and Cognitive Computing
Subjects:
real-time fraud detection
VAE-QLSTM
federated learning
TensorFlow Federated
Online Access:https://www.mdpi.com/2504-2289/9/7/185
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