A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree Algorithm

Today, many people prefer online payment methods due to the rapid growth in cashless electronic transactions. Credit and debit cards are the most popular electronic payment methods but are prone to fraud due to the nature of their use and the tendency of fraudsters to access their details. This stud...

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Main Author: Abdulaziz Saleh Alraddadi
Format: Article
Language:English
Published: D. G. Pylarinos 2023-08-01
Series:Engineering, Technology & Applied Science Research
Subjects:
Online Access:https://etasr.com/index.php/ETASR/article/view/6128
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author Abdulaziz Saleh Alraddadi
author_facet Abdulaziz Saleh Alraddadi
author_sort Abdulaziz Saleh Alraddadi
collection DOAJ
description Today, many people prefer online payment methods due to the rapid growth in cashless electronic transactions. Credit and debit cards are the most popular electronic payment methods but are prone to fraud due to the nature of their use and the tendency of fraudsters to access their details. This study proposes a theoretical credit fraud detection and prevention model using a Decision Tree Algorithm (DCA). Moreover, a survey questionnaire was used to investigate students' perceptions of credit card fraud incidents. Data were collected from 102 students from different universities and countries around the world. The results showed that 95.9% of the respondents knew how credit/debit card fraud occurs, while 4.1% of them did not. Finally, 81.6% expressed their willingness to use a tool based on the proposed model to prevent or detect credit/debit card fraud incidents.
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spelling doaj.art-3f6db5f312514c6e90a8d94b4deda1192023-08-10T05:33:17ZengD. G. PylarinosEngineering, Technology & Applied Science Research2241-44871792-80362023-08-0113410.48084/etasr.6128A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree AlgorithmAbdulaziz Saleh Alraddadi0College of Computer Science and Engineering, Taibah University, Saudi ArabiaToday, many people prefer online payment methods due to the rapid growth in cashless electronic transactions. Credit and debit cards are the most popular electronic payment methods but are prone to fraud due to the nature of their use and the tendency of fraudsters to access their details. This study proposes a theoretical credit fraud detection and prevention model using a Decision Tree Algorithm (DCA). Moreover, a survey questionnaire was used to investigate students' perceptions of credit card fraud incidents. Data were collected from 102 students from different universities and countries around the world. The results showed that 95.9% of the respondents knew how credit/debit card fraud occurs, while 4.1% of them did not. Finally, 81.6% expressed their willingness to use a tool based on the proposed model to prevent or detect credit/debit card fraud incidents. https://etasr.com/index.php/ETASR/article/view/6128online paymentcredit card fraudDecision Tree Algorithm (DCA)survey
spellingShingle Abdulaziz Saleh Alraddadi
A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree Algorithm
Engineering, Technology & Applied Science Research
online payment
credit card fraud
Decision Tree Algorithm (DCA)
survey
title A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree Algorithm
title_full A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree Algorithm
title_fullStr A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree Algorithm
title_full_unstemmed A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree Algorithm
title_short A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree Algorithm
title_sort survey and a credit card fraud detection and prevention model using the decision tree algorithm
topic online payment
credit card fraud
Decision Tree Algorithm (DCA)
survey
url https://etasr.com/index.php/ETASR/article/view/6128
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