Detection of fraud card and data breaches in credit card transactions

Data breaches and credit card fraud are now among the biggest problems affecting financial organizations and customers globally. The purpose of this study is to develop an effective fraud detection system that can detect fraudulent credit card transactions and prevent data breaches. The strategy proposed in this paper makes use of machine learning techniques like decision trees and logistic regression, to analyze large datasets of credit card transactions and identify suspicious patterns. The proposed system also includes a real-time monitoring mechanism that alerts the relevant authorities in case of any suspicious activity. The results of the experiments show that the suggested system achieves great accuracy and efficiency in detecting fraudulent transactions and data breaches. It can provide a powerful tool for financial institutions to prevent financial losses and maintain their customers' trust.