graph-adversarial-learning-literature

graph-adversarial-learning-literature

图数据对抗攻防研究文献综述

该项目整理了图结构数据对抗攻击和防御相关论文,涵盖节点分类、图分类、链接预测等任务。论文按上传日期降序排列,便于了解最新进展。项目还包含一篇综述文章,回顾110多篇相关研究。对图对抗学习研究者提供了系统性的文献资源。

图对抗学习图神经网络攻击方法防御策略节点分类Github开源项目
<div align="center"> <h1>Awesome Graph Adversarial Learning Literature</h1> <a href="https://awesome.re"><img src="https://awesome.re/badge.svg"/></a> <a href="http://makeapullrequest.com"><img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square"/></a> </div>

A curated list of adversarial attacks and defenses papers on graph-structured data.

Papers are sorted by their uploaded dates in descending order.

If you want to add new entries, please make PRs with the same format.

This list serves as a complement to the survey below.

Adversarial Attack and Defense on Graph Data: A Survey (Updated in Oct 2022. More than 110 papers reviewed).

  • Arxiv Version (Latest)
@article{sun2018adversarial, title={Adversarial Attack and Defense on Graph Data: A Survey}, author={Sun, Lichao and Dou, Yingtong and Yang, Carl and Kai Zhang and Wang, Ji and Yixin Liu and Yu, Philip S. and He, Lifang and Li, Bo}, journal={arXiv preprint arXiv:1812.10528}, year={2018} }
  • TKDE Version
@article{sun2022adversarial, title={Adversarial attack and defense on graph data: A survey}, author={Sun, Lichao and Dou, Yingtong and Yang, Carl and Zhang, Kai and Wang, Ji and Philip, S Yu and He, Lifang and Li, Bo}, journal={IEEE Transactions on Knowledge and Data Engineering}, year={2022}, publisher={IEEE} }

If you feel this repo is helpful, please cite the survey above.

How to Search?

Search keywords like conference name (e.g., NeurIPS), task name (e.g., Link Prediction), model name (e.g., DeepWalk), or method name (e.g., Robust) over the webpage to quickly locate related papers.

Quick Links

Attack papers sorted by year: | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 |

Defense papers sorted by year: | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 |

Attack

Attack Papers 2023 [Back to Top]

YearTitleTypeTarget TaskTarget ModelVenuePaperCode
2023Revisiting Robustness in Graph Machine LearningAttackNode ClassificationGCN, SGC, APPNP, GAT, GATv2, GraphSAGE, LPICLR'23LinkLink
2023Unnoticeable Backdoor Attacks on Graph Neural NetworksAttackNode classification, Graph classificationGCN, GraphSage, and GATArXivLinkLink
2023Attacking Fake News Detectors via Manipulating News Social EngagementAttackFake News DetectionGAT, GCN, and GraphSAGE)WWW'23LinkLink
2023HyperAttack: Multi-Gradient-Guided White-box Adversarial Structure Attack of Hypergraph Neural NetworksAttackNode ClassificationHGNNsArXivLink
2023Turning Strengths into Weaknesses: A Certified Robustness Inspired Attack Framework against Graph Neural NetworksAttackNode ClassificationGCNCVPR'23Link
2023Adversary for Social Good: Leveraging Attribute-Obfuscating Attack to Protect User Privacy on Social NetworksAttackAttribute Protection On Social NetworksGNNsSecureComm 2022Link
2023Node Injection for Class-specific Network PoisoningAttackNode ClassificationGCNarXivLinkLink
2023GUAP: Graph Universal Attack Through Adversarial PatchingAttackNode ClassificationGCNarXivLinkLink

Attack Papers 2022 [Back to Top]

YearTitleTypeTarget TaskTarget ModelVenuePaperCode
2022GANI: Global Attacks on Graph Neural Networks via Imperceptible Node InjectionsAttackNode ClassificationGCN/SGC/Jaccard/SimPGCNArxivLink
2022Motif-Backdoor: Rethinking the Backdoor Attack on Graph Neural Networks via MotifsAttackGraph ClassificationGCN/SAGPool/GIN/ArxivLink
2022Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient DebiasAttackNode ClassificationGCN/GAT/GraphSAGENeurIPS 2022LinkLink
2022Imperceptible Adversarial Attacks on Discrete-Time Dynamic Graph ModelsAttackDynamic Link Prediction/Node ClassificationGC-LSTM/EVOLVEGCN/DYSATNeurIPS 2022 Workshop TGLLink
2022A2S2-GNN: Rigging GNN-Based Social Status by Adversarial Attacks in Signed Social NetworksAttackClassification in unsigned or undirected graphsGNNsIEEE Transactions on Information Forensics and SecurityLink
2022Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement LearningAttackNode ClassificationGCN/SGC/GAT/APPNPAAAI23LinkLink
2022QuerySnout: Automating the Discovery of Attribute Inference Attacks against Query-Based SystemsAttackQuery-based systems attribute inferenceDiffix/TableBuilder/SimpleQBSCCS 2022LinkLink
2022Are Defenses for Graph Neural Networks Robust?AttackNode ClassificationGNN, GCN, Jaccard GCN, SVD GCN, GNNGuard, RGCN, ProGNN, GRAND, Soft Median GDCNeurIPS 2022LinkLink
2022Poisoning GNN-based Recommender Systems with Generative Surrogate-based AttacksAttackPromotion/Recommendation/Re-producingGNNACM TISLink
2022Dealing with the unevenness: deeper insights in graph-based attack and defenseAttackSet-Cover problemGCN, RGCN, GCN-Jaccard, Pro-GNNMachine LearningLink
2022Membership Inference Attacks Against Robust Graph Neural NetworkAttackMembership InferenceGCNCSS 2022Link
2022Sparse Vicious Attacks on Graph Neural NetworksAttackLink predictionGNNarXivLinkLink
2022Model Inversion Attacks against Graph Neural NetworksAttackNode ClassificationGCN, GAT and GraphSAGETKDELinkLink
2022Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node ClassificationAttackSemi-Supervised Node ClassificationGNNPattern RecognitionLink
2022Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural NetworksAttacknode classificationGNNIEEE ICDM 2022LinkLink
2022Resisting Graph Adversarial Attack via Cooperative Homophilous AugmentationAttacksemi-Supervised Node ClassificationGNNECML PKDD 2022Link
2022What Does the Gradient Tell When Attacking the Graph StructureAttackNode ClassificationGCN, GraphSage and H2GCNarXivLink
2022Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label PropagationAttackNode ClassificationGNNsCIKM 2022LinkLink
2022Revisiting Item Promotion in GNN-based Collaborative Filtering: A Masked Targeted Topological Attack PerspectiveAttackCollaborative filteringLightGCNarXivLink
2022Link-Backdoor: Backdoor Attack on Link Prediction via Node InjectionAttackLink PredictionGAE, VGAE, GIC, ARGA, ARVGAarXivLinkLink
2022Graph Structural Attack by Perturbing Spectral DistanceAttacknode classificationtwo-layer GCNKDD 2022Link
2022Are Gradients on Graph Structure Reliable in Gray-box Attacks?Attacknode classification tasksGraphSageCIKM 2022Link
2022Adversarial Camouflage for Node Injection Attack on GraphsAttacksemi-supervised information retrieval taskGNNsarXivLink
2022CLUSTER ATTACK: Query-based Adversarial Attacks on Graphs with Graph-Dependent PriorsAttacknode classificationGNNsIJCAI 2022Link
2022IoT-based Android Malware Detection Using Graph Neural Network With Adversarial DefenseAttackMalware DetectionGNNIEEE Internet of ThingsLink
2022Private Graph Extraction via Feature ExplanationsAttacknode classification2-layer GCNarXivLink
2022Towards Secrecy-Aware Attacks Against Trust Prediction in Signed GraphsAttacktrust prediction in signed graphsSGCN, SNEAarXivLink
2022Camouflaged Poisoning Attack on Graph Neural NetworksAttacknode classificationGCNICMR 2022Link
2022LOKI: A Practical Data Poisoning Attack Framework against Next Item RecommendationsAttackNext Item RecommendationsBPRMF, FPMC, GRU4REC, TransRecTKDE 2022Link
2022Poisoning GNN-based Recommender Systems with Generative Surrogate-based AttacksAttackPromotion/Recommendation/Re-producingGNNsACM Transactions on Information Systems 2022Link
2022Transferable Graph Backdoor AttackAttackGraph ClassificationGNNsRAID 2022Link
2022Cluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent PriorsAttackNode ClassificationGNNsIJCAI 2022LinkLink
2022Adversarial Robustness of Graph-based Anomaly DetectionAttackAnomaly DetectionGNNsArxivLink
2022Adversarial Attack Framework on Graph Embedding Models with Limited KnowledgeAttackNode ClassificationGNNsPreprint

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