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Unsupervised Graph Poisoning Attack via Contrastive Loss
  Back-propagation

Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation

20 January 2022
Sixiao Zhang
Hongxu Chen
Xiangguo Sun
Yicong Li
Guandong Xu
    AAML
    SSL
ArXivPDFHTML

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
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?
Robustness questions the interpretability of graph neural networks: what to do?
Kirill Lukyanov
Georgii Sazonov
Serafim Boyarsky
Ilya Makarov
AAML
87
0
0
05 May 2025
Exploiting Meta-Learning-based Poisoning Attacks for Graph Link Prediction
Exploiting Meta-Learning-based Poisoning Attacks for Graph Link Prediction
Mingchen Li
Di Zhuang
Keyu Chen
Dumindu Samaraweera
Morris Chang
AAML
35
0
0
08 Apr 2025
Sub-graph Based Diffusion Model for Link Prediction
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
Debiased Graph Poisoning Attack via Contrastive Surrogate Objective
Kanghoon Yoon
Yeonjun In
Namkyeong Lee
Kibum Kim
Chanyoung Park
AAML
18
2
0
27 Jul 2024
Towards Graph Contrastive Learning: A Survey and Beyond
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
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
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)
All in One: Multi-Task Prompting for Graph Neural Networks (Extended Abstract)
Xiangguo Sun
Hong Cheng
Jia Li
Bo Liu
Jihong Guan
LLMAG
24
2
0
11 Mar 2024
Minimum Topology Attacks for Graph Neural Networks
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
Active Learning for Graphs with Noisy Structures
Hongliang Chi
Cong Qi
Suhang Wang
Yao Ma
25
3
0
04 Feb 2024
Towards Inductive Robustness: Distilling and Fostering Wave-induced
  Resonance in Transductive GCNs Against Graph Adversarial Attacks
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
19
4
0
14 Dec 2023
GraphGuard: Detecting and Counteracting Training Data Misuse in Graph
  Neural Networks
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
EdgePruner: Poisoned Edge Pruning in Graph Contrastive Learning
Hiroya Kato
Kento Hasegawa
Seira Hidano
Kazuhide Fukushima
AAML
22
0
0
12 Dec 2023
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go
  Indifferent
Attacking Graph Neural Networks with Bit Flips: Weisfeiler and Lehman Go Indifferent
Lorenz Kummer
Samir Moustafa
Nils N. Kriege
Wilfried N. Gansterer
GNN
AAML
14
0
0
02 Nov 2023
GraphCloak: Safeguarding Task-specific Knowledge within Graph-structured
  Data from Unauthorized Exploitation
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
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
Black-Box Attacks against Signed Graph Analysis via Balance Poisoning
Jialong Zhou
Y. Lai
Jian Ren
Kai Zhou
AAML
21
4
0
05 Sep 2023
Coupled-Space Attacks against Random-Walk-based Anomaly Detection
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
Homophily-Driven Sanitation View for Robust Graph Contrastive Learning
Yulin Zhu
Xing Ai
Yevgeniy Vorobeychik
Kai Zhou
AAML
8
0
0
24 Jul 2023
Similarity Preserving Adversarial Graph Contrastive Learning
Similarity Preserving Adversarial Graph Contrastive Learning
Yeonjun In
Kanghoon Yoon
Chanyoung Park
AAML
8
9
0
24 Jun 2023
HAT-GAE: Self-Supervised Graph Auto-encoders with Hierarchical Adaptive
  Masking and Trainable Corruption
HAT-GAE: Self-Supervised Graph Auto-encoders with Hierarchical Adaptive Masking and Trainable Corruption
Chengyu Sun
SSL
19
1
0
28 Jan 2023
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings
  through Graph Contrastive Learning
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning
Haoran Yang
Xiangyu Zhao
Muyang Li
Hongxu Chen
Guandong Xu
FedML
13
2
0
24 Jul 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and
  Privacy Protection
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
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
19
6
0
15 Feb 2022
Toward Enhanced Robustness in Unsupervised Graph Representation
  Learning: A Graph Information Bottleneck Perspective
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
12
5
0
21 Jan 2022
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