Review of Machine Learning Approach on Credit Card Fraud Detection

被引：46
作者：
Rejwan Bin Sulaiman
Vitaly Schetinin
Paul Sant
机构：
[1] University of Bedfordshire,
来源：
Human-Centric Intelligent Systems | 2022年 / 2卷 / 1-2期
关键词：
Artificial neural network (ANN); Credit card fraud; Federated learning; Random forest (RF) method; Support vector machine (SVM); Privacy-preserving; Blockchain;
D O I：
10.1007/s44230-022-00004-0
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：55 / 68
页数：13
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