Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation

20 January 2022

Papers citing "Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation"

26 / 26 papers shown

Title
Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense Kirill Lukyanov Mikhail Drobyshevskiy Georgii Sazonov Mikhail Soloviov Ilya Makarov GNN 41 0 0 06 May 2025
Robustness questions the interpretability of graph neural networks: what to do? Kirill Lukyanov Georgii Sazonov Serafim Boyarsky Ilya Makarov AAML 105 0 0 05 May 2025
Exploiting Meta-Learning-based Poisoning Attacks for Graph Link Prediction Mingchen Li Di Zhuang Keyu Chen Dumindu Samaraweera Morris Chang AAML 40 0 0 08 Apr 2025
Sub-graph Based Diffusion Model for Link Prediction Hang Li Wei Jin Geri Skenderi Harry Shomer Wenzhuo Tang Wenqi Fan Jiliang Tang DiffM 26 0 0 13 Sep 2024
Debiased Graph Poisoning Attack via Contrastive Surrogate Objective Kanghoon Yoon Yeonjun In Namkyeong Lee Kibum Kim Chanyoung Park AAML 23 2 0 27 Jul 2024
Towards Graph Contrastive Learning: A Survey and Beyond Wei Ju Yifan Wang Yifang Qin Zhengyan Mao Zhiping Xiao ... Dongjie Wang Qingqing Long Siyu Yi Xiao Luo Ming Zhang 47 12 0 20 May 2024
CORE: Data Augmentation for Link Prediction via Information Bottleneck Kaiwen Dong Zhichun Guo Nitesh V. Chawla 17 0 0 17 Apr 2024
Fast Inference of Removal-Based Node Influence Weikai Li Zhiping Xiao Xiao Luo Yizhou Sun AAML 28 1 0 13 Mar 2024
All in One: Multi-Task Prompting for Graph Neural Networks (Extended Abstract) Xiangguo Sun Hong Cheng Jia Li Bo Liu Jihong Guan LLMAG 27 2 0 11 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
Active Learning for Graphs with Noisy Structures Hongliang Chi Cong Qi Suhang Wang Yao Ma 30 3 0 04 Feb 2024
Towards Inductive Robustness: Distilling and Fostering Wave-induced Resonance in Transductive GCNs Against Graph Adversarial Attacks Ao Liu Wenshan Li Tao Li Beibei Li Hanyuan Huang Pan Zhou AAML 21 4 0 14 Dec 2023
GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks Bang Wu He Zhang Xiangwen Yang Shuo Wang Minhui Xue Shirui Pan Xingliang Yuan 54 6 0 13 Dec 2023
EdgePruner: Poisoned Edge Pruning in Graph Contrastive Learning Hiroya Kato Kento Hasegawa Seira Hidano Kazuhide Fukushima AAML 27 0 0 12 Dec 2023
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent Lorenz Kummer Samir Moustafa Nils N. Kriege Wilfried N. Gansterer GNN AAML 25 0 0 02 Nov 2023
GraphCloak: Safeguarding Task-specific Knowledge within Graph-structured Data from Unauthorized Exploitation Yixin Liu Chenrui Fan Xun Chen Pan Zhou Lichao Sun 48 4 0 11 Oct 2023
Certifiably Robust Graph Contrastive Learning Min Lin Teng Xiao Enyan Dai Xiang Zhang Suhang Wang AAML 19 5 0 05 Oct 2023
Black-Box Attacks against Signed Graph Analysis via Balance Poisoning Jialong Zhou Y. Lai Jian Ren Kai Zhou AAML 23 4 0 05 Sep 2023
Coupled-Space Attacks against Random-Walk-based Anomaly Detection Y. Lai Marcin Waniek Liying Li Jing-Zheng Wu Yulin Zhu Tomasz P. Michalak Talal Rahwan Kai Zhou AAML 25 0 0 26 Jul 2023
Homophily-Driven Sanitation View for Robust Graph Contrastive Learning Yulin Zhu Xing Ai Yevgeniy Vorobeychik Kai Zhou AAML 16 0 0 24 Jul 2023
Similarity Preserving Adversarial Graph Contrastive Learning Yeonjun In Kanghoon Yoon Chanyoung Park AAML 10 9 0 24 Jun 2023
HAT-GAE: Self-Supervised Graph Auto-encoders with Hierarchical Adaptive Masking and Trainable Corruption Chengyu Sun SSL 24 1 0 28 Jan 2023
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning Haoran Yang Xiangyu Zhao Muyang Li Hongxu Chen Guandong Xu FedML 15 2 0 24 Jul 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 25 25 0 20 May 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
Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective Jihong Wang Minnan Luo Jundong Li Ziqi Liu Jun Zhou Qinghua Zheng AAML 15 5 0 21 Jan 2022