A Targeted Universal Attack on Graph Convolutional Network by Using Fake Nodes

Author:

Dai JiazhuORCID,Zhu Weifeng,Luo Xiangfeng

Funder

State Scholarship Fund of the China Scholarship Council

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Reference33 articles.

1. Maji D, Ghorai G (2020) Computing f-index, coindex and zagreb polynomials of the kth generalized transformation graphs. Heliyon 6(12):e05781

2. Xu K, Chen H, Liu S, Chen P, Weng T, Hong M, Lin X (2019) Topology attack and defense for graph neural networks: an optimization perspective. In: Kraus S (Ed.) Proceedings of the twenty-eighth international joint conference on artificial intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, ijcai.org, pp 3961–3967, https://doi.org/10.24963/ijcai.2019/550

3. Ma Y, Wang S, Derr T, Wu L, Tang J (2019) Attacking graph convolutional networks via rewiring. arXiv preprint arXiv:1906.03750

4. Wu H, Wang C, Tyshetskiy Y, Docherty A, Lu K, Zhu L (2019) Adversarial examples on graph data: deep insights into attack and defense. arXiv preprint arXiv:1903.01610

5. Liu X, Si S, Zhu J, Li Y, Hsieh C (2019) A unified framework for data poisoning attack to graph-based semi-supervised learning. In: Wallach HM, Larochelle H, Beygelzimer A, d’Alché-Buc F, Fox EB, Garnett R (Eds.) Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, pp 9777–9787

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