Adaptive GAN-Enhanced Hybrid Framework for Real-Time Credit Card Fraud Detection in Streaming Environments.

Credit card fraud is increasing due to the growth of online transactions. This project proposes a system that can detect fraudulent transactions in real time. It uses a GAN-based hybrid model to generate additional fraud data and improve detection accuracy. The system continuously analyzes transaction data and adapts to new fraud patterns, helping banks identify fraud quickly and reduce financial loss.