Understanding Structural Vulnerability in Graph Convolutional Networks

13 August 2021

Yang Liu

Papers citing "Understanding Structural Vulnerability in Graph Convolutional Networks"

32 / 32 papers shown

Title
AuditVotes: A Framework Towards More Deployable Certified Robustness for Graph Neural Networks Y. Lai Yulin Zhu Y. Sun Y. Wu Bin Xiao Gaolei Li Jianhua Li Kai Zhou AAML 41 0 0 29 Mar 2025
Robust Graph Learning Against Adversarial Evasion Attacks via Prior-Free Diffusion-Based Structure Purification Jiayi Luo Qingyun Sun Haonan Yuan Xingcheng Fu Jianxin Li DiffM AAML 79 0 0 07 Feb 2025
Explainable AI Security: Exploring Robustness of Graph Neural Networks to Adversarial Attacks Tao Wu Canyixing Cui Xingping Xian Shaojie Qiao Chao Wang Lin Yuan Shui Yu AAML 39 0 0 20 Jun 2024
Revisiting Edge Perturbation for Graph Neural Network in Graph Data Augmentation and Attack Xin Liu Yuxiang Zhang Meng Wu Mingyu Yan Kun He Wei Yan Shirui Pan Xiaochun Ye Dongrui Fan AAML 25 2 0 10 Mar 2024
Minimum Topology Attacks for Graph Neural Networks Mengmei Zhang Xiao Wang Chuan Shi Lingjuan Lyu Tianchi Yang Junping Du AAML 36 7 0 05 Mar 2024
Spatial-Temporal DAG Convolutional Networks for End-to-End Joint Effective Connectivity Learning and Resting-State fMRI Classification Rui Yang Wenrui Dai H. She Yiping P. Du Dapeng Wu Hongkai Xiong 20 2 0 16 Dec 2023
Simple and Efficient Partial Graph Adversarial Attack: A New Perspective Guanghui Zhu Meng Chen C. Yuan Y. Huang AAML 18 6 0 15 Aug 2023
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy Enyan Dai Limeng Cui Zhengyang Wang Xianfeng Tang Yinghan Wang Mo Cheng Bin Yin Suhang Wang AAML 25 14 0 14 Jun 2023
Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs Jintang Li Sheng Tian Ruofan Wu Liang Zhu Welong Zhao Changhua Meng Liang Chen Zibin Zheng Hongzhi Yin 31 10 0 18 May 2023
AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing Zhaoliang Chen Zhihao Wu Zhe-Hui Lin Shiping Wang Claudia Plant Wenzhong Guo 27 18 0 14 Apr 2023
Attributed Multi-order Graph Convolutional Network for Heterogeneous Graphs Zhaoliang Chen Zhihao Wu Luying Zhong Claudia Plant Shiping Wang Wenzhong Guo 20 9 0 13 Apr 2023
Are Defenses for Graph Neural Networks Robust? Felix Mujkanovic Simon Geisler Stephan Günnemann Aleksandar Bojchevski OOD AAML 19 56 0 31 Jan 2023
Robust Graph Representation Learning via Predictive Coding Billy Byiringiro Tommaso Salvatori Thomas Lukasiewicz OOD 25 6 0 09 Dec 2022
Semantic Graph Neural Network with Multi-measure Learning for Semi-supervised Classification Jun-Liang Lin Yuan Wan Jingwen Xu X. Qi 25 0 0 04 Dec 2022
Spectral Adversarial Training for Robust Graph Neural Network Jintang Li Jiaying Peng Liang Chen Zibin Zheng Tingting Liang Qing Ling AAML OOD 28 17 0 20 Nov 2022
FocusedCleaner: Sanitizing Poisoned Graphs for Robust GNN-based Node Classification Yulin Zhu Liang Tong Gaolei Li Xiapu Luo Kai Zhou 30 4 0 25 Oct 2022
GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections Junyuan Fang Haixian Wen Jiajing Wu Qi Xuan Zibin Zheng Chi K. Tse AAML 36 22 0 23 Oct 2022
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation Jun Zhuang M. Hasan 23 20 0 21 Aug 2022
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks Jintang Li Zhouxin Yu Zulun Zhu Liang Chen Qi Yu Zibin Zheng Sheng Tian Ruofan Wu Changhua Meng GNN 18 30 0 15 Aug 2022
Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN Kuan Li Yang Liu Xiang Ao Jianfeng Chi Jinghua Feng Hao Yang Qing He AAML 41 63 0 30 Jun 2022
What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders Jintang Li Ruofan Wu Wangbin Sun Liang Chen Sheng Tian Liang Zhu Changhua Meng Zibin Zheng Weiqiang Wang SSL 24 79 0 20 May 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection Bingzhe Wu Jintang Li Junchi Yu Yatao Bian Hengtong Zhang ... Guangyu Sun Peng Cui Zibin Zheng Zhe Liu P. Zhao OOD 27 25 0 20 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 45 104 0 16 May 2022
Detecting Topology Attacks against Graph Neural Networks Senrong Xu Yuan Yao Liangyue Li Wei Yang F. Xu Hanghang Tong 34 3 0 21 Apr 2022
GUARD: Graph Universal Adversarial Defense Jintang Li Jie Liao Ruofan Wu Liang Chen Zibin Zheng Jiawang Dan Changhua Meng Weiqiang Wang AAML 14 8 0 20 Apr 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability Enyan Dai Tianxiang Zhao Huaisheng Zhu Jun Xu Zhimeng Guo Hui Liu Jiliang Tang Suhang Wang 29 131 0 18 Apr 2022
Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision Jun Zhuang M. Hasan AAML 21 42 0 07 Mar 2022
Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack Jintang Li Bingzhe Wu Chengbin Hou Guoji Fu Yatao Bian Liang Chen Junzhou Huang Zibin Zheng OOD AAML 24 6 0 15 Feb 2022
Robustness of Graph Neural Networks at Scale Simon Geisler Tobias Schmidt Hakan cSirin Daniel Zügner Aleksandar Bojchevski Stephan Günnemann AAML 22 123 0 26 Oct 2021
Subgraph Federated Learning with Missing Neighbor Generation Ke Zhang Carl Yang Xiaoxiao Li Lichao Sun S. Yiu FedML 19 163 0 25 Jun 2021
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks Chaoyang He Keshav Balasubramanian Emir Ceyani Carl Yang Han Xie ... Yu Rong P. Zhao Junzhou Huang M. Annavaram Salman Avestimehr FedML OOD 21 2 0 14 Apr 2021
Adversarial Attack and Defense on Graph Data: A Survey Lichao Sun Yingtong Dou Carl Yang Ji Wang Yixin Liu Philip S. Yu Lifang He B. Li GNN AAML 16 273 0 26 Dec 2018