Online Payment Fraud Detection Model Using Machine Learning Techniques
Author:
Affiliation:
1. Department of Information Technology, College of Computing and Information Technology at Khulais, University of Jeddah, Jeddah, Saudi Arabia
2. Department of Creative Technologies, Air University, Islamabad, Pakistan
Funder
Deputyship for Research and Innovation, Ministry of Education, Saudi Arabia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10341223.pdf?arnumber=10341223
Reference44 articles.
1. Enhanced credit card fraud detection based on attention mechanism and LSTM deep model
2. Robust Financial Fraud Alerting System Based in the Cloud Environment
3. A novel combined approach based on deep Autoencoder and deep classifiers for credit card fraud detection
4. Artificial neural network technique for improving prediction of credit card default: A stacked sparse autoencoder approach;ebiaredoh-mienye;Int J Electr Comput Eng (IJECE),2021
5. Cost-sensitive payment card fraud detection based on dynamic random forest and k -nearest neighbors
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Unraveling Financial Fraud With AI and Machine Learning;Advances in Web Technologies and Engineering;2024-08-30
2. Unscrambling Financial Fraud With AI and Machine Learning in E-Commerce Transactions;Advances in Finance, Accounting, and Economics;2024-08-30
3. CCFD: Efficient Credit Card Fraud Detection Using Meta-Heuristic Techniques and Machine Learning Algorithms;Mathematics;2024-07-19
4. Fraud Detection in Financial Transactions Using Deep Learning Approach: A Comparative Study;2024 5th International Conference for Emerging Technology (INCET);2024-05-24
5. An Improved Variational Autoencoder Generative Adversarial Network with Convolutional Neural Network for Fraud Financial Transaction Detection;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3