From Bi-Level to One-Level: A Framework for Structural Attacks to Graph Anomaly Detection-Reference-Cited by-同舟云学术

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From Bi-Level to One-Level: A Framework for Structural Attacks to Graph Anomaly Detection

Published:2024 Issue: Volume: Page:1-14
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Zhu Yulin¹^ORCID,Lai Yuni¹^ORCID,Zhao Kaifa¹^ORCID,Luo Xiapu¹^ORCID,Yuan Mingquan²,Wu Jun³^ORCID,Ren Jian⁴^ORCID,Zhou Kai¹^ORCID

Affiliation:

1. Department of Computing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong

2. Sam’s Club Innovation Center, Dallas, TX, USA

3. Institute of Cyber Science and Technology, Shanghai Jiaotong University, Shanghai, China

4. Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10535517.pdf?arnumber=10535517

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