Multiview-Ensemble-Learning-Based Robust Graph Convolutional Networks Against Adversarial Attacks-Reference-Cited by-同舟云学术

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Multiview-Ensemble-Learning-Based Robust Graph Convolutional Networks Against Adversarial Attacks

Published:2024-08-15 Issue:16 Volume:11 Page:27700-27714
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Wu Tao¹^ORCID,Luo Junhui¹,Qiao Shaojie²^ORCID,Wang Chao³^ORCID,Yuan Lin¹^ORCID,Pu Xiao¹^ORCID,Xian Xingping¹^ORCID

Affiliation:

1. School of Cybersecurity and Information Law, Chongqing University of Posts and Telecommunications, Chongqing, China

2. School of Software Engineering, Chengdu University of Information Technology, Chengdu, China

3. School of Computer and Information Science, Chongqing Normal University, Chongqing, China

Funder

National Natural Science Foundation of China

Key Project of Chongqing Natural Science Foundation Innovation and Development Joint Fund

Chongqing Education Commission Science and Technology Research Program Key Project

Chongqing Technology Innovation and Application Development Project

Open Foundation of Yunnan Key Laboratory of Software Engineering

Science and Technology Research Program of Chongqing Municipal Education Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10623554/10529210.pdf?arnumber=10529210

Reference38 articles.

1. Effective Backdoor Attack on Graph Neural Networks in Spectral Domain

2. Inductive representation learning on large graphs;Hamilton

3. Graph attention networks;Veličković;arXiv:1710.10903,2017

4. Variational graph auto-encoders;Kipf;arXiv:1611.07308,2016

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