Poster: A deep learning method for fraud detection in financial systems

Mahmut Ögrek, Eyüp Ögrek, Serif Bahtiyar*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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 languageEnglish
Title of host publicationWiSec 2019 - Proceedings of the 2019 Conference on Security and Privacy in Wireless and Mobile Networks
PublisherAssociation for Computing Machinery, Inc
Pages298-299
Number of pages2
ISBN (Electronic)9781450367264
DOIs
Publication statusPublished - 15 May 2019
Event12th Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2019 - Miami, United States
Duration: 15 May 201917 May 2019

Publication series

NameWiSec 2019 - Proceedings of the 2019 Conference on Security and Privacy in Wireless and Mobile Networks

Conference

Conference12th Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2019
Country/TerritoryUnited States
CityMiami
Period15/05/1917/05/19

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.

FundersFunder number
Istanbul Teknik ÜniversitesiMAB-2017-40642

    Keywords

    • Financial system
    • Fraud detection
    • Neural networks
    • Security

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