Review of Machine Learning Approach on Credit Card Fraud Detection

Autor:	Rejwan Bin Sulaiman, Vitaly Schetinin, Paul Sant
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Artificial neural network (ANN) Credit card fraud Federated learning Random forest (RF) method Support vector machine (SVM) Privacy-preserving Information technology T58.5-58.64 Electronic computers. Computer science QA75.5-76.95
Zdroj:	Human-Centric Intelligent Systems, Vol 2, Iss 1-2, Pp 55-68 (2022)
Druh dokumentu:	article
ISSN:	2667-1336
DOI:	10.1007/s44230-022-00004-0
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/15597d044e6e4b21b500647e172a6ff6 Zobrazit plný text záznamu Full text from SpringerLink View record in DOAJ