Review of machine learning approach on credit card fraud detection
- Rejwan Bin Sulaiman,
- ,
- Paul Sant
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
EnglishPages 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
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