Abstract
Credit card fraud has been a significant challenge ever since forgers have been inventing new ways to steal money. Thus, adaptive fraud detection methods are required to counter the forgers. Deep learning methods have been attractive candidates because of their adaptive nature to detect emerging credit card frauds. In this paper, we propose a deep learning method to adaptively detect credit card frauds by using neural networks. We experimentally evaluated our model with Kaggle dataset. The analyses results show that our methods adaptively detect credit card frauds.
Original language | English |
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Title of host publication | WiSec 2019 - Proceedings of the 2019 Conference on Security and Privacy in Wireless and Mobile Networks |
Publisher | Association for Computing Machinery, Inc |
Pages | 298-299 |
Number of pages | 2 |
ISBN (Electronic) | 9781450367264 |
DOIs | |
Publication status | Published - 15 May 2019 |
Event | 12th Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2019 - Miami, United States Duration: 15 May 2019 → 17 May 2019 |
Publication series
Name | WiSec 2019 - Proceedings of the 2019 Conference on Security and Privacy in Wireless and Mobile Networks |
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Conference
Conference | 12th Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2019 |
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Country/Territory | United States |
City | Miami |
Period | 15/05/19 → 17/05/19 |
Bibliographical note
Publisher Copyright:© 2019 Copyright held by the owner/author(s).
Funding
This work is supported by Istanbul Technical University under the BAP project, number MAB-2017-40642.
Funders | Funder number |
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Istanbul Teknik Üniversitesi | MAB-2017-40642 |
Keywords
- Financial system
- Fraud detection
- Neural networks
- Security