⚔🛡 Awesome Graph Adversarial Learning

⚔🛡 Awesome Graph Adversarial Learning
👀Quick Look
⚔Attack
- 2023
- 2022
- 2021
- 2020
- 2019
- 2018
- 2017
🛡Defense
- 2023
- 2022
- 2021
- 2020
- 2019
- 2018
- 2017
🔐Certification
⚖Stability
🚀Others
📃Survey
⚙Toolbox
🔗Resource

This repository contains Attack-related papers, Defense-related papers, Robustness Certification papers, etc., ranging from 2017 to 2021. If you find this repo useful, please cite: A Survey of Adversarial Learning on Graph, arXiv'20, Link

@article{chen2020survey,
  title={A Survey of Adversarial Learning on Graph},
  author={Chen, Liang and Li, Jintang and Peng, Jiaying and Xie, 
        Tao and Cao, Zengxu and Xu, Kun and He, 
        Xiangnan and Zheng, Zibin and Wu, Bingzhe},
  journal={arXiv preprint arXiv:2003.05730},
  year={2020}
}

👀Quick Look

The papers in this repo are categorized or sorted:

If you want to get a quick look at the recently updated papers in the repository (in 30 days), you can refer to 📍this.

⚔Attack

2023

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Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective, 📝ICLR, :octocat:Code
Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning, 📝AAAI, :octocat:Code
GUAP: Graph Universal Attack Through Adversarial Patching, 📝arXiv, :octocat:Code
Node Injection for Class-specific Network Poisoning, 📝arXiv, :octocat:Code
Unnoticeable Backdoor Attacks on Graph Neural Networks, 📝WWW, :octocat:Code
A semantic backdoor attack against Graph Convolutional Networks, 📝arXiv

2022

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Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem, 📝WSDM, :octocat:Code
Inference Attacks Against Graph Neural Networks, 📝USENIX Security, :octocat:Code
Model Stealing Attacks Against Inductive Graph Neural Networks, 📝IEEE Symposium on Security and Privacy, :octocat:Code
Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, 📝WWW, :octocat:Code
Neighboring Backdoor Attacks on Graph Convolutional Network, 📝arXiv, :octocat:Code
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability, 📝ICLR, :octocat:Code
Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs, 📝AAAI, :octocat:Code
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks, 📝arXiv
Black-box Node Injection Attack for Graph Neural Networks, 📝arXiv, :octocat:Code
Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection, 📝arXiv
Projective Ranking-based GNN Evasion Attacks, 📝arXiv
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation, 📝arXiv
Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization, 📝Asia CCS, :octocat:Code
Bandits for Structure Perturbation-based Black-box Attacks to Graph Neural Networks with Theoretical Guarantees, 📝CVPR, :octocat:Code
Transferable Graph Backdoor Attack, 📝RAID, :octocat:Code
Adversarial Robustness of Graph-based Anomaly Detection, 📝arXiv
Label specificity attack: Change your label as I want, 📝IJIS
AdverSparse: An Adversarial Attack Framework for Deep Spatial-Temporal Graph Neural Networks, 📝ICASSP
Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks, 📝WSDM
Cluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent Priors, 📝IJCAI, :octocat:Code
Label-Only Membership Inference Attack against Node-Level Graph Neural NetworksCluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent Priors, 📝arXiv
Adversarial Camouflage for Node Injection Attack on Graphs, 📝arXiv
Are Gradients on Graph Structure Reliable in Gray-box Attacks?, 📝CIKM, :octocat:Code
Adversarial Camouflage for Node Injection Attack on Graphs, 📝arXiv
Graph Structural Attack by Perturbing Spectral Distance, 📝KDD
What Does the Gradient Tell When Attacking the Graph Structure, 📝arXiv
BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection, 📝ICDM, :octocat:Code
Model Inversion Attacks against Graph Neural Networks, 📝TKDE
Sparse Vicious Attacks on Graph Neural Networks, 📝arXiv, :octocat:Code
Poisoning GNN-based Recommender Systems with Generative Surrogate-based Attacks, 📝ACM TIS
Dealing with the unevenness: deeper insights in graph-based attack and defense, 📝Machine Learning
Membership Inference Attacks Against Robust Graph Neural Network, 📝CSS
Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks, 📝ICDM, :octocat:Code
Revisiting Item Promotion in GNN-based Collaborative Filtering: A Masked Targeted Topological Attack Perspective, 📝arXiv
Link-Backdoor: Backdoor Attack on Link Prediction via Node Injection, 📝arXiv, :octocat:Code
Private Graph Extraction via Feature Explanations, 📝arXiv
Towards Secrecy-Aware Attacks Against Trust Prediction in Signed Graphs, 📝arXiv
Camouflaged Poisoning Attack on Graph Neural Networks, 📝ICDM
LOKI: A Practical Data Poisoning Attack Framework against Next Item Recommendations, 📝TKDE
Adversarial for Social Privacy: A Poisoning Strategy to Degrade User Identity Linkage, 📝arXiv
Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node Classification, 📝Pattern Recognition
GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections, 📝arXiv, :octocat:Code
Motif-Backdoor: Rethinking the Backdoor Attack on Graph Neural Networks via Motifs, 📝arXiv
Are Defenses for Graph Neural Networks Robust?, 📝NeurIPS, :octocat:Code
Adversarial Label Poisoning Attack on Graph Neural Networks via Label Propagation, 📝ECCV
Imperceptible Adversarial Attacks on Discrete-Time Dynamic Graph Models, 📝NeurIPS
Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias, 📝NeurIPS, :octocat:Code
Adversary for Social Good: Leveraging Attribute-Obfuscating Attack to Protect User Privacy on Social Networks, 📝SecureComm

2021

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Stealing Links from Graph Neural Networks, 📝USENIX Security
PATHATTACK: Attacking Shortest Paths in Complex Networks, 📝arXiv
Structack: Structure-based Adversarial Attacks on Graph Neural Networks, 📝ACM Hypertext, :octocat:Code
Optimal Edge Weight Perturbations to Attack Shortest Paths, 📝arXiv
GReady for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack, 📝Information Sciences
Graph Adversarial Attack via Rewiring, 📝KDD, :octocat:Code
Membership Inference Attack on Graph Neural Networks, 📝arXiv
Graph Backdoor, 📝USENIX Security
TDGIA: Effective Injection Attacks on Graph Neural Networks,