QFNN-FFD: Quantum Federated Neural Network for Financial Fraud Detection
Nouhaila Innan Alberto Marchisio Muhammad Shafique Mohamed Bennai
This study introduces the Quantum Federated Neural Network for Financial
Fraud Detection (QFNN-FFD), a cutting-edge framework merging Quantum Machine
Learning (QML) and quantum computing with Federated Learning (FL) to innovate
financial fraud detection. Using quantum technologies' computational power and
FL's data privacy, QFNN-FFD presents a secure, efficient method for identifying
fraudulent transactions. Implementing a dual-phase training model across
distributed clients surpasses existing methods in performance. QFNN-FFD
significantly improves fraud detection and ensures data confidentiality,
marking a significant advancement in fintech solutions and establishing a new
standard for privacy-focused fraud detection.