An Imperceptible and Owner-unique Watermarking Method for Graph Neural Networks-Reference-Cited by-同舟云学术

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An Imperceptible and Owner-unique Watermarking Method for Graph Neural Networks

Published:2024-07-05 Issue: Volume:32 Page:108-113
ISSN:
Container-title:ACM Turing Award Celebration Conference 2024
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Author:

Zhang Linji¹^ORCID,Xue Mingfu²^ORCID,Zhang Leo Yu³^ORCID,Zhang Yushu¹^ORCID,Liu Weiqiang⁴^ORCID

Affiliation:

1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, CN

2. School of Communication and Electronic Engineering, East China Normal University, CN

3. School of Information and Communication Technology, Griffith University, AU

4. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, CN

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3674399.3674443

Reference32 articles.

1. Yossi Adi, Carsten Baum, Moustapha Cisse, Benny Pinkas, and Joseph Keshet. 2018. Turning your weakness into a strength: Watermarking deep neural networks by backdooring. In 27th USENIX Security Symposium. 1615–1631.

2. DeepMarks

3. Yongqiang Chen Han Yang Yonggang Zhang Kaili Ma Tongliang Liu Bo Han and James Cheng. 2022. Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. CoRR abs/2202.08057.

4. Unnoticeable Backdoor Attacks on Graph Neural Networks

5. DeepSigns

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