Internet Banking Fraud Detection Using Deep Learning Based on Decision Tree and Multilayer Perceptron

被引：0
|
作者：
Kataria, Sonal [1 ]
Nafis, Md Tabrez [1 ]
机构：
[1] Jamia Hamdard, Dept Comp Sci & Engn, New Delhi, India
来源：
PROCEEDINGS OF THE 2019 6TH INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM) | 2019年
关键词：
fraud detection; online banking fraud detection; neural network; online banking fraud; deep learning; artificial neural network; decision tree; multilayer perceptron algorithm; three layer perceptron;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Fraud transactions have become a growing problem in the online banking sphere. As technology progresses, fraudsters also change their methods of committing fraud. There are also emerging technologies that allow fraudsters to mimic the transaction behavior of genuine customers and they also keep changing their methods so that it is difficult to detect fraud. This paper discusses the importance of fraud detection methods and compares Hidden Markov Model, Deep Learning, and Neural Network that are used to detect fraud in online banking transactions.
引用
收藏
页码：1298 / 1302
页数：5
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