Advancement of Payment Systems in eCommerce : Machine Learning, Security, and Fraud Detection

Authors

  • Samuel Johnson   Software Automation Engineer, Lululemon, Seattle, WA, USA

Keywords:

eCommerce, Payment Systems, Machine Learning, Fraud Detection, Security Technologies, Tokenization, Encryption, Multi-Factor Authentication (MFA), Digital Wallets, Cryptocurrencies, Artificial Intelligence (AI), Fraud Prevention, User Experience.

Abstract

As the eCommerce market expands, the payment system has become more extensive due to integration and development in payment technologies, security, and user interface. New advancements in technology, such as machine learning (ML), have become essential tools for secure and effective payment systems through real-time identification of fraudulent activities and increasing financial transactions' safety levels to improve people's confidence. This paper aims to review the literature on payment systems in the context of eCommerce, focusing on machine learning for fraud detection. It also explains how contemporary security technologies such as encryption and tokenization are making payment security better and appraises these innovations' obstacles and tendencies.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-02-19

Issue

Volume 9, Issue 1, January-February-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Samuel Johnson , " Advancement of Payment Systems in eCommerce : Machine Learning, Security, and Fraud Detection" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 1, pp.303-323, January-February-2023.