papers_with_code.md

	Title	Type	Venue	Code	Year
0	Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective	⚔Attack	📝ICLR	Code	2023
1	Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning	⚔Attack	📝AAAI	Code	2023
2	GUAP: Graph Universal Attack Through Adversarial Patching	⚔Attack	📝arXiv	Code	2023
3	Node Injection for Class-specific Network Poisoning	⚔Attack	📝arXiv	Code	2023
4	Unnoticeable Backdoor Attacks on Graph Neural Networks	⚔Attack	📝WWW	Code	2023
5	Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem	⚔Attack	📝WSDM	Code	2022
6	Inference Attacks Against Graph Neural Networks	⚔Attack	📝USENIX Security	Code	2022
7	Model Stealing Attacks Against Inductive Graph Neural Networks	⚔Attack	📝IEEE Symposium on Security and Privacy	Code	2022
8	Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation	⚔Attack	📝WWW	Code	2022
9	Neighboring Backdoor Attacks on Graph Convolutional Network	⚔Attack	📝arXiv	Code	2022
10	Understanding and Improving Graph Injection Attack by Promoting Unnoticeability	⚔Attack	📝ICLR	Code	2022
11	Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs	⚔Attack	📝AAAI	Code	2022
12	Black-box Node Injection Attack for Graph Neural Networks	⚔Attack	📝arXiv	Code	2022
13	Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization	⚔Attack	📝Asia CCS	Code	2022
14	Bandits for Structure Perturbation-based Black-box Attacks to Graph Neural Networks with Theoretical Guarantees	⚔Attack	📝CVPR	Code	2022
15	Transferable Graph Backdoor Attack	⚔Attack	📝RAID	Code	2022
16	Cluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent Priors	⚔Attack	📝IJCAI	Code	2022
17	Are Gradients on Graph Structure Reliable in Gray-box Attacks?	⚔Attack	📝CIKM	Code	2022
18	BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection	⚔Attack	📝ICDM	Code	2022
19	Sparse Vicious Attacks on Graph Neural Networks	⚔Attack	📝arXiv	Code	2022
20	Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks	⚔Attack	📝ICDM	Code	2022
21	Link-Backdoor: Backdoor Attack on Link Prediction via Node Injection	⚔Attack	📝arXiv	Code	2022
22	GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections	⚔Attack	📝arXiv	Code	2022
23	Are Defenses for Graph Neural Networks Robust?	⚔Attack	📝NeurIPS	Code	2022
24	Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias	⚔Attack	📝NeurIPS	Code	2022
25	Structack: Structure-based Adversarial Attacks on Graph Neural Networks	⚔Attack	📝ACM Hypertext	Code	2021
26	Graph Adversarial Attack via Rewiring	⚔Attack	📝KDD	Code	2021
27	TDGIA: Effective Injection Attacks on Graph Neural Networks	⚔Attack	📝KDD	Code	2021
28	Adversarial Attack on Large Scale Graph	⚔Attack	📝TKDE	Code	2021
29	SAGE: Intrusion Alert-driven Attack Graph Extractor	⚔Attack	📝KDD Workshop	Code	2021
30	Adversarial Diffusion Attacks on Graph-based Traffic Prediction Models	⚔Attack	📝arXiv	Code	2021
31	VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning	⚔Attack	📝PAKDD	Code	2021
32	GraphAttacker: A General Multi-Task GraphAttack Framework	⚔Attack	📝arXiv	Code	2021
33	Graph Stochastic Neural Networks for Semi-supervised Learning	⚔Attack	📝arXiv	Code	2021
34	Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings	⚔Attack	📝arXiv	Code	2021
35	Single-Node Attack for Fooling Graph Neural Networks	⚔Attack	📝KDD Workshop	Code	2021
36	Poisoning Knowledge Graph Embeddings via Relation Inference Patterns	⚔Attack	📝ACL	Code	2021
37	Single Node Injection Attack against Graph Neural Networks	⚔Attack	📝CIKM	Code	2021
38	Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications	⚔Attack	📝ICDM	Code	2021
39	Robustness of Graph Neural Networks at Scale	⚔Attack	📝NeurIPS	Code	2021
40	Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models	⚔Attack	📝IJCAI	Code	2021
41	Adversarial Attacks on Graph Classification via Bayesian Optimisation	⚔Attack	📝NeurIPS	Code	2021
42	Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods	⚔Attack	📝EMNLP	Code	2021
43	UNTANGLE: Unlocking Routing and Logic Obfuscation Using Graph Neural Networks-based Link Prediction	⚔Attack	📝ICCAD	Code	2021
44	GraphMI: Extracting Private Graph Data from Graph Neural Networks	⚔Attack	📝IJCAI	Code	2021
45	Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation	⚔Attack	📝ICLR	Code	2020
46	Towards More Practical Adversarial Attacks on Graph Neural Networks	⚔Attack	📝NeurIPS	Code	2020
47	Adversarial Label-Flipping Attack and Defense for Graph Neural Networks	⚔Attack	📝ICDM	Code	2020
48	Exploratory Adversarial Attacks on Graph Neural Networks	⚔Attack	📝ICDM	Code	2020
49	A Targeted Universal Attack on Graph Convolutional Network	⚔Attack	📝arXiv	Code	2020
50	Backdoor Attacks to Graph Neural Networks	⚔Attack	📝SACMAT	Code	2020
51	Adversarial Attack on Community Detection by Hiding Individuals	⚔Attack	📝WWW	Code	2020
52	A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models	⚔Attack	📝AAAI	Code	2020
53	Scalable Attack on Graph Data by Injecting Vicious Nodes	⚔Attack	📝ECML-PKDD	Code	2020
54	Network disruption: maximizing disagreement and polarization in social networks	⚔Attack	📝arXiv	Code	2020
55	Structured Adversarial Attack Towards General Implementation and Better Interpretability	⚔Attack	📝ICLR	Code	2019
56	PeerNets Exploiting Peer Wisdom Against Adversarial Attacks	⚔Attack	📝ICLR	Code	2019
57	Adversarial Attacks on Node Embeddings via Graph Poisoning	⚔Attack	📝ICML	Code	2019
58	Adversarial Attacks on Graph Neural Networks via Meta Learning	⚔Attack	📝ICLR	Code	2019
59	Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective	⚔Attack	📝IJCAI	Code	2019
60	Adversarial Examples on Graph Data: Deep Insights into Attack and Defense	⚔Attack	📝IJCAI	Code	2019
61	A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning	⚔Attack	📝NeurIPS	Code	2019
62	Adversarial Attacks on Neural Networks for Graph Data	⚔Attack	📝KDD	Code	2018
63	Adversarial Attack on Graph Structured Data	⚔Attack	📝ICML	Code	2018
64	Adversarial Sets for Regularising Neural Link Predictors	⚔Attack	📝UAI	Code	2017
65	Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions	🛡Defense	📝NeurIPS	Code	2023
66	Empowering Graph Representation Learning with Test-Time Graph Transformation	🛡Defense	📝ICLR	Code	2023
67	Robust Training of Graph Neural Networks via Noise Governance	🛡Defense	📝WSDM	Code	2023
68	Self-Supervised Graph Structure Refinement for Graph Neural Networks	🛡Defense	📝WSDM	Code	2023
69	Revisiting Robustness in Graph Machine Learning	🛡Defense	📝ICLR	Code	2023
70	Unsupervised Adversarially-Robust Representation Learning on Graphs	🛡Defense	📝AAAI	Code	2022
71	Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels	🛡Defense	📝WSDM	Code	2022
72	Mind Your Solver! On Adversarial Attack and Defense for Combinatorial Optimization	🛡Defense	📝arXiv	Code	2022
73	Graph Neural Network for Local Corruption Recovery	🛡Defense	📝arXiv	Code	2022
74	Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision	🛡Defense	📝AAAI	Code	2022
75	SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation	🛡Defense	📝WWW	Code	2022
76	GUARD: Graph Universal Adversarial Defense	🛡Defense	📝arXiv	Code	2022
77	Bayesian Robust Graph Contrastive Learning	🛡Defense	📝arXiv	Code	2022
78	Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN	🛡Defense	📝KDD	Code	2022
79	Appearance and Structure Aware Robust Deep Visual Graph Matching: Attack, Defense and Beyond	🛡Defense	📝CVPR	Code	2022
80	How does Heterophily Impact Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications	🛡Defense	📝KDD	Code	2022
81	Robust Graph Neural Networks using Weighted Graph Laplacian	🛡Defense	📝SPCOM	Code	2022
82	Robust Tensor Graph Convolutional Networks via T-SVD based Graph Augmentation	🛡Defense	📝KDD	Code	2022
83	Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation	🛡Defense	📝CIKM	Code	2022
84	On the Robustness of Graph Neural Diffusion to Topology Perturbations	🛡Defense	📝NeurIPS	Code	2022
85	Spectral Adversarial Training for Robust Graph Neural Network	🛡Defense	📝TKDE	Code	2022
86	You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets	🛡Defense	📝LoG	Code	2022
87	Learning to Drop: Robust Graph Neural Network via Topological Denoising	🛡Defense	📝WSDM	Code	2021
88	Understanding Structural Vulnerability in Graph Convolutional Networks	🛡Defense	📝IJCAI	Code	2021
89	A Robust and Generalized Framework for Adversarial Graph Embedding	🛡Defense	📝arXiv	Code	2021
90	Information Obfuscation of Graph Neural Network	🛡Defense	📝ICML	Code	2021
91	Elastic Graph Neural Networks	🛡Defense	📝ICML	Code	2021
92	Node Similarity Preserving Graph Convolutional Networks	🛡Defense	📝WSDM	Code	2021
93	NetFense: Adversarial Defenses against Privacy Attacks on Neural Networks for Graph Data	🛡Defense	📝TKDE	Code	2021
94	Power up! Robust Graph Convolutional Network against Evasion Attacks based on Graph Powering	🛡Defense	📝AAAI	Code	2021
95	Unveiling the potential of Graph Neural Networks for robust Intrusion Detection	🛡Defense	📝arXiv	Code	2021
96	A Lightweight Metric Defence Strategy for Graph Neural Networks Against Poisoning Attacks	🛡Defense	📝ICICS	Code	2021
97	Node Feature Kernels Increase Graph Convolutional Network Robustness	🛡Defense	📝arXiv	Code	2021
98	Not All Low-Pass Filters are Robust in Graph Convolutional Networks	🛡Defense	📝NeurIPS	Code	2021
99	Graph Neural Networks with Adaptive Residual	🛡Defense	📝NeurIPS	Code	2021
100	Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification	🛡Defense	📝NeurIPS	Code	2021
101	Topological Relational Learning on Graphs	🛡Defense	📝NeurIPS	Code	2021
102	Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings	🛡Defense	📝NeurIPS	Code	2020
103	Graph Random Neural Networks for Semi-Supervised Learning on Graphs	🛡Defense	📝NeurIPS	Code	2020
104	Reliable Graph Neural Networks via Robust Aggregation	🛡Defense	📝NeurIPS	Code	2020
105	Graph Adversarial Networks: Protecting Information against Adversarial Attacks	🛡Defense	📝ICLR OpenReview	Code	2020
106	A Feature-Importance-Aware and Robust Aggregator for GCN	🛡Defense	📝CIKM	Code	2020
107	Graph Information Bottleneck	🛡Defense	📝NeurIPS	Code	2020
108	Graph Contrastive Learning with Augmentations	🛡Defense	📝NeurIPS	Code	2020
109	Graph Structure Reshaping Against Adversarial Attacks on Graph Neural Networks	🛡Defense	📝None	Code	2020
110	Adversarial Privacy Preserving Graph Embedding against Inference Attack	🛡Defense	📝arXiv	Code	2020
111	GNNGuard: Defending Graph Neural Networks against Adversarial Attacks	🛡Defense	📝NeurIPS	Code	2020
112	Transferring Robustness for Graph Neural Network Against Poisoning Attacks	🛡Defense	📝WSDM	Code	2020
113	All You Need Is Low (Rank): Defending Against Adversarial Attacks on Graphs	🛡Defense	📝WSDM	Code	2020
114	Robust Detection of Adaptive Spammers by Nash Reinforcement Learning	🛡Defense	📝KDD	Code	2020
115	Graph Structure Learning for Robust Graph Neural Networks	🛡Defense	📝KDD	Code	2020
116	On The Stability of Polynomial Spectral Graph Filters	🛡Defense	📝ICASSP	Code	2020
117	On the Robustness of Cascade Diffusion under Node Attacks	🛡Defense	📝WWW	Code	2020
118	Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters	🛡Defense	📝CIKM	Code	2020
119	DefenseVGAE: Defending against Adversarial Attacks on Graph Data via a Variational Graph Autoencoder	🛡Defense	📝arXiv	Code	2020
120	Graph-Revised Convolutional Network	🛡Defense	📝ECML-PKDD	Code	2020
121	Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure	🛡Defense	📝TKDE	Code	2019
122	Bayesian graph convolutional neural networks for semi-supervised classification	🛡Defense	📝AAAI	Code	2019
123	Graph Interpolating Activation Improves Both Natural and Robust Accuracies in Data-Efficient Deep Learning	🛡Defense	📝arXiv	Code	2019
124	Adversarial Training Methods for Network Embedding	🛡Defense	📝WWW	Code	2019
125	Batch Virtual Adversarial Training for Graph Convolutional Networks	🛡Defense	📝ICML	Code	2019
126	Latent Adversarial Training of Graph Convolution Networks	🛡Defense	📝LRGSD@ICML	Code	2019
127	Characterizing Malicious Edges targeting on Graph Neural Networks	🛡Defense	📝ICLR OpenReview	Code	2019
128	Robust Graph Convolutional Networks Against Adversarial Attacks	🛡Defense	📝KDD	Code	2019
129	Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications	🛡Defense	📝NAACL	Code	2019
130	Adversarial Personalized Ranking for Recommendation	🛡Defense	📝SIGIR	Code	2018
131	Hierarchical Randomized Smoothing	🔐Certification	📝NeurIPS'2023	Code	2023
132	(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More	🔐Certification	📝NeurIPS'2023	Code	2023
133	Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks	🔐Certification	📝NeurIPS'2022	Code	2022
134	Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation	🔐Certification	📝KDD'2021	Code	2021
135	Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks	🔐Certification	📝ICLR'2021	Code	2021
136	Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks	🔐Certification	📝NeurIPS'2020	Code	2020
137	Efficient Robustness Certificates for Discrete Data: Sparsity - Aware Randomized Smoothing for Graphs, Images and More	🔐Certification	📝ICML'2020	Code	2020
138	Certifiable Robustness of Graph Convolutional Networks under Structure Perturbation	🔐Certification	📝KDD'2020	Code	2020
139	Certifiable Robustness and Robust Training for Graph Convolutional Networks	🔐Certification	📝KDD'2019	Code	2019
140	Certifiable Robustness to Graph Perturbations	🔐Certification	📝NeurIPS'2019	Code	2019
141	Towards a Unified Framework for Fair and Stable Graph Representation Learning	⚖Stability	📝UAI'2021	Code	2021
142	Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data	⚖Stability	📝NeurIPS'2021	Code	2021
143	When Do GNNs Work: Understanding and Improving Neighborhood Aggregation	⚖Stability	📝IJCAI Workshop'2019	Code	2019
144	Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts	🚀Others	📝arXiv‘2023	Code	2023
145	A Systematic Evaluation of Node Embedding Robustness	🚀Others	📝LoG‘2022	Code	2022
146	FLAG: Adversarial Data Augmentation for Graph Neural Networks	🚀Others	📝arXiv'2020	Code	2020
147	Training Robust Graph Neural Network by Applying Lipschitz Constant Constraint	🚀Others	📝CentraleSupélec'2020	Code	2020
148	DeepRobust: a Platform for Adversarial Attacks and Defenses	⚙Toolbox	📝AAAI’2021	DeepRobust	2021
149	GreatX: A graph reliability toolbox based on PyTorch and PyTorch Geometric	⚙Toolbox	📝arXiv’2022	GreatX	2022
150	Evaluating Graph Vulnerability and Robustness using TIGER	⚙Toolbox	📝arXiv‘2021	TIGER	2021
151	Graph Robustness Benchmark: Rethinking and Benchmarking Adversarial Robustness of Graph Neural Networks	⚙Toolbox	📝NeurIPS'2021	Graph Robustness Benchmark (GRB)	2021