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

Author(s)	Ms. Sireesha B, Ms. Meghana Palakolanu, Mr. Jagadish Mala, Ms. Tejashwini Putta, Mr. Sasikanth Mandakala
Country	India
Abstract	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.
Keywords	credit card fraud, e-business, logistic regression, support vector machine, XGBoost, Random Forest, K-Nearest Neighbors, Deep Neural Network, generative adversarial networks (GANs), explainable AI (XAI).
Field	Engineering
Published In	Volume 7, Issue 3, March 2026
Published On	2026-03-22
DOI	https://doi.org/10.70528/IJLRP.v7.i3.2013
Short DOI	https://doi.org/hbvwc8

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