Blockchain-Enhanced Credit Card Fraud Detection Using Machine Learning

Abstract

Abstract— This study integrates blockchain technology and machine learning to enhance credit card fraud detection. ​ Precise fraud prediction is performed using advanced algorithms such as Random Forest, Logistic Regression, XGBoost, and Bayesian models. ​ Tools such as Ganache and MetaMask from Ethereum blockchain facilitate safe and transparent tracking of suspicious transactions. ​ Decentralized and tamper-proof properties of blockchain add reliability, and machine learning adds precision and flexibility. The system is highly accurate and transparent and has the potential to be used to fight financial fraud. ​ Keywords— Credit Card Fraud, Blockchain, Machine Learning, Ethereum, Web3, SMOTE, XGBoost, Streamlit