Credit Card Fraud Prediction And Detection using Artificial Neural Network And Self-Organizing Maps

被引:1
|
作者
Saraswathi, E. [1 ]
Kulkarni, Prateek [1 ]
Khalil, Momin Nawaf [1 ]
Nigam, Shishir Chandra [1 ]
机构
[1] SRM IST RAMAPARAM, Comp Sci & Engn, Chennai, Tamil Nadu, India
关键词
Artificial Neural Network (ANN); Machine Learning; Self-Organising Maps (SOM);
D O I
10.1109/iccmc.2019.8819758
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The credit card business has increased speedily over the last two decades. Corporations and establishments are moving towards various online services, which aims to permit their customers with high potency and accessibility. The evolution is a huge step towards potency, accessibility and profitableness of view. Nevertheless, it additionally has some downsides. These smart services are recently prone to significant security related vulnerabilities. Developing business through card depends on the fact that neither the card nor the user needs to be present at the point of transaction. Thus, it is impossible for merchandiser to check weather the cardholder is real or not. Companies' loss in recent times are majorly due to the credit card fraud and the fraudsters who ceaselessly obtain new ways to commit the unlawful activities. As we know that Artificial Neural Network has the ability to work as a human brain when trained properly. We have also implemented SOM for accuracy purpose. In this paper, we discuss about the performance of the network and their accuracy.
引用
收藏
页码:1124 / 1128
页数:5
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