An Adaptive Heterogeneous Credit Card Fraud Detection Model Based on Deep Reinforcement Training Subset Selection-Reference-Cited by-同舟云学术

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An Adaptive Heterogeneous Credit Card Fraud Detection Model Based on Deep Reinforcement Training Subset Selection

Published:2024-08 Issue:8 Volume:5 Page:4026-4041
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Zhu Kun¹^ORCID,Zhang Nana²^ORCID,Ding Weiping³^ORCID,Jiang Changjun¹^ORCID

Affiliation:

1. Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai, China

2. School of Computer Science and Technology, Donghua University, Shanghai, China

3. School of Information Science and Technology, Nantong University, Nantong, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Shanghai Super Doctoral Incentive Program

Shanghai Science and Technology Innovation Action Plan Project

Natural Science Foundation of Jiangsu Province

Natural Science Key Foundation of Jiangsu Education Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9078688/10635096/10417044.pdf?arnumber=10417044

Reference47 articles.

1. Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019

2. Credit Card Fraud Detection: A Realistic Modeling and a Novel Learning Strategy

3. A Transformer-based Model Integrated with Feature Selection for Credit Card Fraud Detection

4. Credit Card Fraud Detection: A Novel Approach Using Aggregation Strategy and Feedback Mechanism

5. Feature construction for fraudulent credit card cash-out detection

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