Detection of fraud card and data breaches in credit card transactions

Sanskrati Agarwal * and Usha J

Department of Computer Applications, RV College of Engineering, Bengaluru, India.
 
Review
International Journal of Science and Research Archive, 2023, 09(02), 576–582.
Article DOI: 10.30574/ijsra.2023.9.2.0603
Publication history: 
Received on 19 June 2023; revised on 01 August 2023; accepted on 04 August 2023
 
Abstract: 
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.
 
Keywords: 
Data breaches; Machine learning; Decision trees; Logistic regression; Real-time monitoring
 
Full text article in PDF: 
 
Copyright information: 

Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0