E. Saraswathi, Prateek P. Kulkarni, Momin Nawaf Khalil, Shishir Chandra Nigam
{"title":"基于人工神经网络和自组织映射的信用卡欺诈预测与检测","authors":"E. Saraswathi, Prateek P. Kulkarni, Momin Nawaf Khalil, Shishir Chandra Nigam","doi":"10.1109/ICCMC.2019.8819758","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Credit Card Fraud Prediction And Detection using Artificial Neural Network And Self-Organizing Maps\",\"authors\":\"E. Saraswathi, Prateek P. Kulkarni, Momin Nawaf Khalil, Shishir Chandra Nigam\",\"doi\":\"10.1109/ICCMC.2019.8819758\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":232624,\"journal\":{\"name\":\"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCMC.2019.8819758\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMC.2019.8819758","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Credit Card Fraud Prediction And Detection using Artificial Neural Network And Self-Organizing Maps
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.