Brigham Young University, USA.
World Journal of Advanced Research and Reviews, 2025, 26(01), 1309-1314
Article DOI: 10.30574/wjarr.2025.26.1.1153
Received on 24 February 2025; revised on 07 April 2025; accepted on 09 April 2025
E-commerce websites face increasing threats from credit card skimming attacks that have evolved from simple code injections to sophisticated operations targeting vulnerabilities in payment systems. These attacks, characterized by malicious code that captures sensitive payment information while allowing websites to function normally, pose significant risks to both businesses and consumers. This article examines the growing landscape of digital skimming threats and advanced detection methodologies, including machine learning-based anomaly detection, integrity-checking systems, automated vulnerability scanning, and real-time transaction monitoring. It further explores preventative technologies such as tokenization, secure payment gateways, web application firewalls, and SSL/TLS encryption. The discussion extends to regulatory compliance frameworks and implementation strategies for comprehensive security, highlighting the multi-layered approach necessary to protect e-commerce platforms in today's digital marketplace.
Credit Card Skimming; E-commerce Security; Tokenization; Machine Learning Detection; Payment Fraud Prevention
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Smita Verma. Combating credit card skimming on E-Commerce websites: Advanced detection methods and preventative technologies. World Journal of Advanced Research and Reviews, 2025, 26(01), 1309-1314. Article DOI: https://doi.org/10.30574/wjarr.2025.26.1.1153.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0