Credit Card Fraud Detection Based on DeepInsight and Deep Learning

Jehn Ruey Jiang, Chien Kai Liao

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

7 Scopus citations

Abstract

In this paper, we propose a credit card fraud detection method that leverages DeepInsight and deep learning. The proposed method employs the DeepInsight mechanism to convert non-image credit card transaction data into structured images. These images are then processed by a parallel convolutional neural network (CNN) deep learning model to extract crucial hidden features for credit card fraud detection. To evaluate the performance of our method, we utilize European credit card transaction data. The evaluation results are compared with those of related methods, demonstrating the superiority of our proposed method in terms of the accuracy, true positive rate, true negative rate, and Matthews correlation coefficient.

Original languageEnglish
Title of host publication2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages559-560
Number of pages2
ISBN (Electronic)9798350324174
DOIs
StatePublished - 2023
Event2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Pingtung, Taiwan
Duration: 17 Jul 202319 Jul 2023

Publication series

Name2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023 - Proceedings

Conference

Conference2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023
Country/TerritoryTaiwan
CityPingtung
Period17/07/2319/07/23

Keywords

  • DeepInsight
  • adaptive synthetic sampling
  • convolutional neural network
  • credit card
  • deep learning
  • fraud detection

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