GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detection-Reference-Cited by-同舟云学术

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GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detection

Published:2024-08 Issue:4 Volume:10 Page:528-542
ISSN:2332-7790
Container-title:IEEE Transactions on Big Data
language:
Short-container-title:IEEE Trans. Big Data

Author:

Hu Xinxin¹^ORCID,Chen Haotian²^ORCID,Zhang Junjie¹^ORCID,Chen Hongchang¹^ORCID,Liu Shuxin¹^ORCID,Li Xing¹^ORCID,Wang Yahui¹^ORCID,Xue Xiangyang³^ORCID

Affiliation:

1. National Digital Switching System Engineering and Technological Research Center, Zhengzhou, China

2. The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada

3. Institute of Big Data, Fudan University, Shanghai, China

Funder

Henan Province Major Science and Technology Project

Central Plains Talent Foundation of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6687317/10595994/10388428.pdf?arnumber=10388428

Reference75 articles.

1. Research report on telecommunication network fraud management under the new situation,2020

2. Truecaller insights 2021 U.S. spam & scam report,2021

3. Research report on telecommunication network fraud governance in 2021,2022

4. FrauDetector

5. Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

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