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Review of machine learning approach on credit card fraud detection

Research Output: Contribution to journal Review article Peer-review

Open access

Abstract

Massive usage of credit cards has caused an escalation of fraud. Usage of credit cards has resulted in the growth of online business advancement and ease of the e-payment system. The use of machine learning (methods) are adapted on a larger scale to detect and prevent fraud. ML algorithms play an essential role in analysing customer data. In this research article, we have conducted a comparative analysis of the literature review considering the ML techniques for credit card fraud detection (CCFD) and data confidentiality. In the end, we have proposed a hybrid solution, using the neural network (ANN) in a federated learning framework. It has been observed as an effective solution for achieving higher accuracy in CCFD while ensuring privacy.

Publication Information

Output type

Research Output: Contribution to journal Review article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 55-68 (14 pages)

Journal (Volume, Issue Number)

Human-Centric Intelligent Systems (Volume 2, Issue 1)

Publication milestones

  • Accepted/In press - 28/03/2022
  • Published - 05/05/2022

Publication status

Published - 05/05/2022

External Publication IDs

  • Scopus: 105018873418