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AAAI

	Title	Type	Venue	Code	Year
0	Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning	⚔Attack	📝AAAI	Code	2023
1	Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs	⚔Attack	📝AAAI	Code	2022
2	Attacking Graph Neural Networks at Scale	⚔Attack	📝AAAI workshop		2021
3	DeHiB: Deep Hidden Backdoor Attack on Semi-Supervised Learning via Adversarial Perturbation	⚔Attack	📝AAAI		2021
4	A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models	⚔Attack	📝AAAI	Code	2020
5	Unsupervised Adversarially-Robust Representation Learning on Graphs	🛡Defense	📝AAAI	Code	2022
6	Robust Heterogeneous Graph Neural Networks against Adversarial Attacks	🛡Defense	📝AAAI		2022
7	Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision	🛡Defense	📝AAAI	Code	2022
8	UAG: Uncertainty-Aware Attention Graph Neural Network for Defending Adversarial Attacks	🛡Defense	📝AAAI		2021
9	Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks	🛡Defense	📝AAAI		2021
10	Power up! Robust Graph Convolutional Network against Evasion Attacks based on Graph Powering	🛡Defense	📝AAAI	Code	2021
11	Personalized privacy protection in social networks through adversarial modeling	🛡Defense	📝AAAI		2021
12	Randomized Generation of Adversary-Aware Fake Knowledge Graphs to Combat Intellectual Property Theft	🛡Defense	📝AAAI		2021
13	Adversary for Social Good: Protecting Familial Privacy through Joint Adversarial Attacks	🛡Defense	📝AAAI		2020
14	Bayesian graph convolutional neural networks for semi-supervised classification	🛡Defense	📝AAAI	Code	2019
15	Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning	🔐Certification	📝AAAI'2020		2020
16	A Comparative Study on Robust Graph Neural Networks to Structural Noises	📃Survey	📝AAAI DLG'2022		2022
17	DeepRobust: a Platform for Adversarial Attacks and Defenses	⚙Toolbox	📝AAAI’2021	DeepRobust	2021

IJCAI

	Title	Type	Venue	Code	Year
0	Cluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent Priors	⚔Attack	📝IJCAI	Code	2022
1	Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models	⚔Attack	📝IJCAI	Code	2021
2	GraphMI: Extracting Private Graph Data from Graph Neural Networks	⚔Attack	📝IJCAI	Code	2021
3	An Efficient Adversarial Attack on Graph Structured Data	⚔Attack	📝IJCAI Workshop		2020
4	Data Poisoning Attack against Knowledge Graph Embedding	⚔Attack	📝IJCAI		2019
5	Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective	⚔Attack	📝IJCAI	Code	2019
6	Adversarial Examples on Graph Data: Deep Insights into Attack and Defense	⚔Attack	📝IJCAI	Code	2019
7	Understanding Structural Vulnerability in Graph Convolutional Networks	🛡Defense	📝IJCAI	Code	2021
8	Adversarial Examples on Graph Data: Deep Insights into Attack and Defense	🛡Defense	📝IJCAI	Code	2019
9	Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective	🛡Defense	📝IJCAI	Code	2019
10	When Do GNNs Work: Understanding and Improving Neighborhood Aggregation	⚖Stability	📝IJCAI Workshop'2019	Code	2019

ICLR

	Title	Type	Venue	Code	Year
0	Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective	⚔Attack	📝ICLR	Code	2023
1	Understanding and Improving Graph Injection Attack by Promoting Unnoticeability	⚔Attack	📝ICLR	Code	2022
2	One Vertex Attack on Graph Neural Networks-based Spatiotemporal Forecasting	⚔Attack	📝ICLR OpenReview		2020
3	Near-Black-Box Adversarial Attacks on Graph Neural Networks as An Influence Maximization Problem	⚔Attack	📝ICLR OpenReview		2020
4	Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation	⚔Attack	📝ICLR	Code	2020
5	Structured Adversarial Attack Towards General Implementation and Better Interpretability	⚔Attack	📝ICLR	Code	2019
6	PeerNets Exploiting Peer Wisdom Against Adversarial Attacks	⚔Attack	📝ICLR	Code	2019
7	Adversarial Attacks on Graph Neural Networks via Meta Learning	⚔Attack	📝ICLR	Code	2019
8	ASGNN: Graph Neural Networks with Adaptive Structure	🛡Defense	📝ICLR OpenReview		2023
9	Empowering Graph Representation Learning with Test-Time Graph Transformation	🛡Defense	📝ICLR	Code	2023
10	Revisiting Robustness in Graph Machine Learning	🛡Defense	📝ICLR	Code	2023
11	Distributionally Robust Semi-Supervised Learning Over Graphs	🛡Defense	📝ICLR		2021
12	Ricci-GNN: Defending Against Structural Attacks Through a Geometric Approach	🛡Defense	📝ICLR OpenReview		2020
13	Towards Robust Graph Neural Networks against Label Noise	🛡Defense	📝ICLR OpenReview		2020
14	Graph Adversarial Networks: Protecting Information against Adversarial Attacks	🛡Defense	📝ICLR OpenReview	Code	2020
15	Characterizing Malicious Edges targeting on Graph Neural Networks	🛡Defense	📝ICLR OpenReview	Code	2019
16	Comparing and Detecting Adversarial Attacks for Graph Deep Learning	🛡Defense	📝RLGM@ICLR		2019
17	Localized Randomized Smoothing for Collective Robustness Certification	🔐Certification	📝ICLR'2023		2023
18	Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks	🔐Certification	📝ICLR'2021	Code	2021
19	Certifying Robustness of Graph Laplacian Based Semi-Supervised Learning	🔐Certification	📝ICLR OpenReview'2021		2021

WWW

	Title	Type	Venue	Code	Year
0	Unnoticeable Backdoor Attacks on Graph Neural Networks	⚔Attack	📝WWW	Code	2023
1	Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation	⚔Attack	📝WWW	Code	2022
2	Adversarial Attack on Community Detection by Hiding Individuals	⚔Attack	📝WWW	Code	2020
3	Adversarial Attacks on Graph Neural Networks via Node Injections: A Hierarchical Reinforcement Learning Approach	⚔Attack	📝WWW		2020
4	Robust Mid-Pass Filtering Graph Convolutional Networks	🛡Defense	📝WWW		2023
5	SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation	🛡Defense	📝WWW	Code	2022
6	Robust Network Alignment via Attack Signal Scaling and Adversarial Perturbation Elimination	🛡Defense	📝WWW		2021
7	On the Robustness of Cascade Diffusion under Node Attacks	🛡Defense	📝WWW	Code	2020
8	Friend or Faux: Graph-Based Early Detection of Fake Accounts on Social Networks	🛡Defense	📝WWW		2020
9	Adversarial Training Methods for Network Embedding	🛡Defense	📝WWW	Code	2019
10	Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing	🔐Certification	📝WWW'2020		2020

KDD

	Title	Type	Venue	Code	Year
0	Graph Structural Attack by Perturbing Spectral Distance	⚔Attack	📝KDD		2022
1	Graph Adversarial Attack via Rewiring	⚔Attack	📝KDD	Code	2021
2	TDGIA: Effective Injection Attacks on Graph Neural Networks	⚔Attack	📝KDD	Code	2021
3	SAGE: Intrusion Alert-driven Attack Graph Extractor	⚔Attack	📝KDD Workshop	Code	2021
4	VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning	⚔Attack	📝PAKDD	Code	2021
5	Single-Node Attack for Fooling Graph Neural Networks	⚔Attack	📝KDD Workshop	Code	2021
6	Adversarial Attacks on Graph Neural Networks: Perturbations and their Patterns	⚔Attack	📝TKDD		2020
7	Scalable Attack on Graph Data by Injecting Vicious Nodes	⚔Attack	📝ECML-PKDD	Code	2020
8	Attackability Characterization of Adversarial Evasion Attack on Discrete Data	⚔Attack	📝KDD		2020
9	Adversarial Attacks on Neural Networks for Graph Data	⚔Attack	📝KDD	Code	2018
10	Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN	🛡Defense	📝KDD	Code	2022
11	How does Heterophily Impact Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications	🛡Defense	📝KDD	Code	2022
12	Robust Tensor Graph Convolutional Networks via T-SVD based Graph Augmentation	🛡Defense	📝KDD	Code	2022
13	Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification	🛡Defense	📝KDD		2022
14	Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation	🛡Defense	📝ECML-PKDD		2022
15	Robust Detection of Adaptive Spammers by Nash Reinforcement Learning	🛡Defense	📝KDD	Code	2020
16	Graph Structure Learning for Robust Graph Neural Networks	🛡Defense	📝KDD	Code	2020
17	Robust Training of Graph Convolutional Networks via Latent Perturbation	🛡Defense	📝ECML-PKDD		2020
18	Graph-Revised Convolutional Network	🛡Defense	📝ECML-PKDD	Code	2020
19	Improving Robustness to Attacks Against Vertex Classification	🛡Defense	📝MLG@KDD		2019
20	Robust Graph Convolutional Networks Against Adversarial Attacks	🛡Defense	📝KDD	Code	2019
21	Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation	🔐Certification	📝KDD'2021	Code	2021
22	Certifiable Robustness of Graph Convolutional Networks under Structure Perturbation	🔐Certification	📝KDD'2020	Code	2020
23	Certifiable Robustness and Robust Training for Graph Convolutional Networks	🔐Certification	📝KDD'2019	Code	2019
24	Stability and Generalization of Graph Convolutional Neural Networks	⚖Stability	📝KDD'2019		2019
25	Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies	📃Survey	📝SIGKDD Explorations'2021		2021

ICML

	Title	Type	Venue	Code	Year
0	Practical Adversarial Attacks on Graph Neural Networks	⚔Attack	📝ICML Workshop		2020
1	Adversarial Attacks on Node Embeddings via Graph Poisoning	⚔Attack	📝ICML	Code	2019
2	Adversarial Attack on Graph Structured Data	⚔Attack	📝ICML	Code	2018
3	Robust Graph Representation Learning for Local Corruption Recovery	🛡Defense	📝ICML workshop		2022
4	Integrated Defense for Resilient Graph Matching	🛡Defense	📝ICML		2021
5	Information Obfuscation of Graph Neural Network	🛡Defense	📝ICML	Code	2021
6	Elastic Graph Neural Networks	🛡Defense	📝ICML	Code	2021
7	Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks	🛡Defense	📝ICML		2021
8	Robust Graph Representation Learning via Neural Sparsification	🛡Defense	📝ICML		2020
9	Batch Virtual Adversarial Training for Graph Convolutional Networks	🛡Defense	📝ICML	Code	2019
10	Latent Adversarial Training of Graph Convolution Networks	🛡Defense	📝LRGSD@ICML	Code	2019
11	Efficient Robustness Certificates for Discrete Data: Sparsity - Aware Randomized Smoothing for Graphs, Images and More	🔐Certification	📝ICML'2020	Code	2020
12	When Does Self-Supervision Help Graph Convolutional Networks?	🚀Others	📝ICML'2020		2020

TKDE

	Title	Type	Venue	Code	Year
0	Model Inversion Attacks against Graph Neural Networks	⚔Attack	📝TKDE		2022
1	LOKI: A Practical Data Poisoning Attack Framework against Next Item Recommendations	⚔Attack	📝TKDE		2022
2	Adversarial Attack on Large Scale Graph	⚔Attack	📝TKDE	Code	2021
3	Time-aware Gradient Attack on Dynamic Network Link Prediction	⚔Attack	📝TKDE		2021
4	Spectral Adversarial Training for Robust Graph Neural Network	🛡Defense	📝TKDE	Code	2022
5	NetFense: Adversarial Defenses against Privacy Attacks on Neural Networks for Graph Data	🛡Defense	📝TKDE	Code	2021
6	Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure	🛡Defense	📝TKDE	Code	2019
7	Graph Vulnerability and Robustness: A Survey	📃Survey	📝TKDE'2022		2022

CIKM

	Title	Type	Venue	Code	Year
0	Are Gradients on Graph Structure Reliable in Gray-box Attacks?	⚔Attack	📝CIKM	Code	2022
1	Single Node Injection Attack against Graph Neural Networks	⚔Attack	📝CIKM	Code	2021
2	Projective Ranking: A Transferable Evasion Attack Method on Graph Neural Networks	⚔Attack	📝CIKM		2021
3	A Graph Matching Attack on Privacy-Preserving Record Linkage	⚔Attack	📝CIKM		2020
4	αCyber: Enhancing Robustness of Android Malware Detection System against Adversarial Attacks on Heterogeneous Graph based Model	⚔Attack	📝CIKM		2019
5	Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation	🛡Defense	📝CIKM	Code	2022
6	Speedup Robust Graph Structure Learning with Low-Rank Information	🛡Defense	📝CIKM		2021
7	A Feature-Importance-Aware and Robust Aggregator for GCN	🛡Defense	📝CIKM	Code	2020
8	Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters	🛡Defense	📝CIKM	Code	2020
9	αCyber: Enhancing Robustness of Android Malware Detection System against Adversarial Attacks on Heterogeneous Graph based Model	🛡Defense	📝CIKM		2019

WSDM

	Title	Type	Venue	Code	Year
0	Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem	⚔Attack	📝WSDM	Code	2022
1	Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks	⚔Attack	📝WSDM		2022
2	Robust Training of Graph Neural Networks via Noise Governance	🛡Defense	📝WSDM	Code	2023
3	Self-Supervised Graph Structure Refinement for Graph Neural Networks	🛡Defense	📝WSDM	Code	2023
4	Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels	🛡Defense	📝WSDM	Code	2022
5	Learning to Drop: Robust Graph Neural Network via Topological Denoising	🛡Defense	📝WSDM	Code	2021
6	Node Similarity Preserving Graph Convolutional Networks	🛡Defense	📝WSDM	Code	2021
7	Transferring Robustness for Graph Neural Network Against Poisoning Attacks	🛡Defense	📝WSDM	Code	2020
8	All You Need Is Low (Rank): Defending Against Adversarial Attacks on Graphs	🛡Defense	📝WSDM	Code	2020
9	Adversarial Immunization for Improving Certifiable Robustness on Graphs	🔐Certification	📝WSDM'2021		2021

NeurIPS

	Title	Type	Venue	Code	Year
0	Are Defenses for Graph Neural Networks Robust?	⚔Attack	📝NeurIPS	Code	2022
1	Imperceptible Adversarial Attacks on Discrete-Time Dynamic Graph Models	⚔Attack	📝NeurIPS		2022
2	Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias	⚔Attack	📝NeurIPS	Code	2022
3	Robustness of Graph Neural Networks at Scale	⚔Attack	📝NeurIPS	Code	2021
4	Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness	⚔Attack	📝NeurIPS		2021
5	Adversarial Attacks on Graph Classification via Bayesian Optimisation	⚔Attack	📝NeurIPS	Code	2021
6	Adversarial Attacks on Deep Graph Matching	⚔Attack	📝NeurIPS		2020
7	Towards More Practical Adversarial Attacks on Graph Neural Networks	⚔Attack	📝NeurIPS	Code	2020
8	A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning	⚔Attack	📝NeurIPS	Code	2019
9	Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions	🛡Defense	📝NeurIPS	Code	2023
10	On the Robustness of Graph Neural Diffusion to Topology Perturbations	🛡Defense	📝NeurIPS	Code	2022
11	EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks	🛡Defense	📝NeurIPS	Code	2022
12	Robustness of Graph Neural Networks at Scale	🛡Defense	📝NeurIPS	Code	2021
13	Not All Low-Pass Filters are Robust in Graph Convolutional Networks	🛡Defense	📝NeurIPS	Code	2021
14	Graph Neural Networks with Adaptive Residual	🛡Defense	📝NeurIPS	Code	2021
15	Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification	🛡Defense	📝NeurIPS	Code	2021
16	Topological Relational Learning on Graphs	🛡Defense	📝NeurIPS	Code	2021
17	Provable Overlapping Community Detection in Weighted Graphs	🛡Defense	📝NeurIPS		2020
18	Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings	🛡Defense	📝NeurIPS	Code	2020
19	Graph Random Neural Networks for Semi-Supervised Learning on Graphs	🛡Defense	📝NeurIPS	Code	2020
20	Reliable Graph Neural Networks via Robust Aggregation	🛡Defense	📝NeurIPS	Code	2020
21	Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings	🛡Defense	📝NeurIPS	Code	2020
22	Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian	🛡Defense	📝NeurIPS		2020
23	Graph Information Bottleneck	🛡Defense	📝NeurIPS	Code	2020
24	Graph Contrastive Learning with Augmentations	🛡Defense	📝NeurIPS	Code	2020
25	GNNGuard: Defending Graph Neural Networks against Adversarial Attacks	🛡Defense	📝NeurIPS	Code	2020
26	Hierarchical Randomized Smoothing	🔐Certification	📝NeurIPS'2023	Code	2023
27	(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More	🔐Certification	📝NeurIPS'2023	Code	2023
28	Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks	🔐Certification	📝NeurIPS'2022	Code	2022
29	Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks	🔐Certification	📝NeurIPS'2020	Code	2020
30	Certifiable Robustness to Graph Perturbations	🔐Certification	📝NeurIPS'2019	Code	2019
31	Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data	⚖Stability	📝NeurIPS'2021	Code	2021
32	Graph Robustness Benchmark: Rethinking and Benchmarking Adversarial Robustness of Graph Neural Networks	⚙Toolbox	📝NeurIPS'2021	Graph Robustness Benchmark (GRB)	2021

USENIX

	Title	Type	Venue	Code	Year
0	Inference Attacks Against Graph Neural Networks	⚔Attack	📝USENIX Security	Code	2022
1	Stealing Links from Graph Neural Networks	⚔Attack	📝USENIX Security		2021
2	Graph Backdoor	⚔Attack	📝USENIX Security		2021
3	SIGL: Securing Software Installations Through Deep Graph Learning	🚀Others	📝USENIX'2021		2021

ICDM

	Title	Type	Venue	Code	Year
0	BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection	⚔Attack	📝ICDM	Code	2022
1	Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks	⚔Attack	📝ICDM	Code	2022
2	Camouflaged Poisoning Attack on Graph Neural Networks	⚔Attack	📝ICDM		2022
3	Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications	⚔Attack	📝ICDM	Code	2021
4	Adversarial Label-Flipping Attack and Defense for Graph Neural Networks	⚔Attack	📝ICDM	Code	2020
5	Exploratory Adversarial Attacks on Graph Neural Networks	⚔Attack	📝ICDM	Code	2020
6	Graph-based Adversarial Online Kernel Learning with Adaptive Embedding	🛡Defense	📝ICDM		2021
7	AANE: Anomaly Aware Network Embedding For Anomalous Link Detection	🛡Defense	📝ICDM		2020
8	Provably Robust Node Classification via Low-Pass Message Passing	🛡Defense	📝ICDM		2020
9	Adversarial Robustness of Similarity-Based Link Prediction	🛡Defense	📝ICDM		2019

Arxiv

Title	Type	Venue	Code	Year

UAI

	Title	Type	Venue	Code	Year
0	Adversarial Sets for Regularising Neural Link Predictors	⚔Attack	📝UAI	Code	2017
1	Adversarial Sets for Regularising Neural Link Predictors	🛡Defense	📝UAI	Code	2017
2	Towards a Unified Framework for Fair and Stable Graph Representation Learning	⚖Stability	📝UAI'2021	Code	2021

ICSE

Title	Type	Venue	Code	Year

ECAI

	Title	Type	Venue	Code	Year
0	Abstract Interpretation based Robustness Certification for Graph Convolutional Networks	🔐Certification	📝ECAI'2020		2020

Others

	Title	Type	Venue	Code	Year
0	GUAP: Graph Universal Attack Through Adversarial Patching	⚔Attack	📝arXiv	Code	2023
1	Node Injection for Class-specific Network Poisoning	⚔Attack	📝arXiv	Code	2023
2	A semantic backdoor attack against Graph Convolutional Networks	⚔Attack	📝arXiv		2023
3	Model Stealing Attacks Against Inductive Graph Neural Networks	⚔Attack	📝IEEE Symposium on Security and Privacy	Code	2022
4	Neighboring Backdoor Attacks on Graph Convolutional Network	⚔Attack	📝arXiv	Code	2022
5	More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks	⚔Attack	📝arXiv		2022
6	Black-box Node Injection Attack for Graph Neural Networks	⚔Attack	📝arXiv	Code	2022
7	Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection	⚔Attack	📝arXiv		2022
8	Projective Ranking-based GNN Evasion Attacks	⚔Attack	📝arXiv		2022
9	GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation	⚔Attack	📝arXiv		2022
10	Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization	⚔Attack	📝Asia CCS	Code	2022
11	Bandits for Structure Perturbation-based Black-box Attacks to Graph Neural Networks with Theoretical Guarantees	⚔Attack	📝CVPR	Code	2022
12	Transferable Graph Backdoor Attack	⚔Attack	📝RAID	Code	2022
13	Adversarial Robustness of Graph-based Anomaly Detection	⚔Attack	📝arXiv		2022
14	Label specificity attack: Change your label as I want	⚔Attack	📝IJIS		2022
15	AdverSparse: An Adversarial Attack Framework for Deep Spatial-Temporal Graph Neural Networks	⚔Attack	📝ICASSP		2022
16	Label-Only Membership Inference Attack against Node-Level Graph Neural NetworksCluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent Priors	⚔Attack	📝arXiv		2022
17	Adversarial Camouflage for Node Injection Attack on Graphs	⚔Attack	📝arXiv		2022
18	Adversarial Camouflage for Node Injection Attack on Graphs	⚔Attack	📝arXiv		2022
19	What Does the Gradient Tell When Attacking the Graph Structure	⚔Attack	📝arXiv		2022
20	Sparse Vicious Attacks on Graph Neural Networks	⚔Attack	📝arXiv	Code	2022
21	Poisoning GNN-based Recommender Systems with Generative Surrogate-based Attacks	⚔Attack	📝ACM TIS		2022
22	Dealing with the unevenness: deeper insights in graph-based attack and defense	⚔Attack	📝Machine Learning		2022
23	Membership Inference Attacks Against Robust Graph Neural Network	⚔Attack	📝CSS		2022
24	Revisiting Item Promotion in GNN-based Collaborative Filtering: A Masked Targeted Topological Attack Perspective	⚔Attack	📝arXiv		2022
25	Link-Backdoor: Backdoor Attack on Link Prediction via Node Injection	⚔Attack	📝arXiv	Code	2022
26	Private Graph Extraction via Feature Explanations	⚔Attack	📝arXiv		2022
27	Towards Secrecy-Aware Attacks Against Trust Prediction in Signed Graphs	⚔Attack	📝arXiv		2022
28	Adversarial for Social Privacy: A Poisoning Strategy to Degrade User Identity Linkage	⚔Attack	📝arXiv		2022
29	Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node Classification	⚔Attack	📝Pattern Recognition		2022
30	GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections	⚔Attack	📝arXiv	Code	2022
31	Motif-Backdoor: Rethinking the Backdoor Attack on Graph Neural Networks via Motifs	⚔Attack	📝arXiv		2022
32	Adversarial Label Poisoning Attack on Graph Neural Networks via Label Propagation	⚔Attack	📝ECCV		2022
33	Adversary for Social Good: Leveraging Attribute-Obfuscating Attack to Protect User Privacy on Social Networks	⚔Attack	📝SecureComm		2022
34	PATHATTACK: Attacking Shortest Paths in Complex Networks	⚔Attack	📝arXiv		2021
35	Structack: Structure-based Adversarial Attacks on Graph Neural Networks	⚔Attack	📝ACM Hypertext	Code	2021
36	Optimal Edge Weight Perturbations to Attack Shortest Paths	⚔Attack	📝arXiv		2021
37	GReady for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack	⚔Attack	📝Information Sciences		2021
38	Membership Inference Attack on Graph Neural Networks	⚔Attack	📝arXiv		2021
39	Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge	⚔Attack	📝arXiv		2021
40	Black-box Gradient Attack on Graph Neural Networks: Deeper Insights in Graph-based Attack and Defense	⚔Attack	📝arXiv		2021
41	Joint Detection and Localization of Stealth False Data Injection Attacks in Smart Grids using Graph Neural Networks	⚔Attack	📝arXiv		2021
42	Universal Spectral Adversarial Attacks for Deformable Shapes	⚔Attack	📝CVPR		2021
43	Adversarial Diffusion Attacks on Graph-based Traffic Prediction Models	⚔Attack	📝arXiv	Code	2021
44	Explainability-based Backdoor Attacks Against Graph Neural Networks	⚔Attack	📝WiseML@WiSec		2021
45	GraphAttacker: A General Multi-Task GraphAttack Framework	⚔Attack	📝arXiv	Code	2021
46	Node-Level Membership Inference Attacks Against Graph Neural Networks	⚔Attack	📝arXiv		2021
47	Reinforcement Learning For Data Poisoning on Graph Neural Networks	⚔Attack	📝arXiv		2021
48	Graphfool: Targeted Label Adversarial Attack on Graph Embedding	⚔Attack	📝arXiv		2021
49	Towards Revealing Parallel Adversarial Attack on Politician Socialnet of Graph Structure	⚔Attack	📝Security and Communication Networks		2021
50	Network Embedding Attack: An Euclidean Distance Based Method	⚔Attack	📝MDATA		2021
51	Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation	⚔Attack	📝arXiv		2021
52	Jointly Attacking Graph Neural Network and its Explanations	⚔Attack	📝arXiv		2021
53	Graph Stochastic Neural Networks for Semi-supervised Learning	⚔Attack	📝arXiv	Code	2021
54	Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings	⚔Attack	📝arXiv	Code	2021
55	The Robustness of Graph k-shell Structure under Adversarial Attacks	⚔Attack	📝arXiv		2021
56	Poisoning Knowledge Graph Embeddings via Relation Inference Patterns	⚔Attack	📝ACL	Code	2021
57	A Hard Label Black-box Adversarial Attack Against Graph Neural Networks	⚔Attack	📝CCS		2021
58	GNNUnlock: Graph Neural Networks-based Oracle-less Unlocking Scheme for Provably Secure Logic Locking	⚔Attack	📝DATE Conference		2021
59	Spatially Focused Attack against Spatiotemporal Graph Neural Networks	⚔Attack	📝arXiv		2021
60	Derivative-free optimization adversarial attacks for graph convolutional networks	⚔Attack	📝PeerJ		2021
61	Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning	⚔Attack	📝arXiv		2021
62	Watermarking Graph Neural Networks based on Backdoor Attacks	⚔Attack	📝arXiv		2021
63	Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods	⚔Attack	📝EMNLP	Code	2021
64	COREATTACK: Breaking Up the Core Structure of Graphs	⚔Attack	📝arXiv		2021
65	UNTANGLE: Unlocking Routing and Logic Obfuscation Using Graph Neural Networks-based Link Prediction	⚔Attack	📝ICCAD	Code	2021
66	Structural Attack against Graph Based Android Malware Detection	⚔Attack	📝CCS		2021
67	Adversarial Attack against Cross-lingual Knowledge Graph Alignment	⚔Attack	📝EMNLP		2021
68	FHA: Fast Heuristic Attack Against Graph Convolutional Networks	⚔Attack	📝ICDS		2021
69	Task and Model Agnostic Adversarial Attack on Graph Neural Networks	⚔Attack	📝arXiv		2021
70	How Members of Covert Networks Conceal the Identities of Their Leaders	⚔Attack	📝ACM TIST		2021
71	Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification	⚔Attack	📝arXiv		2021
72	Semantic-preserving Reinforcement Learning Attack Against Graph Neural Networks for Malware Detection	⚔Attack	📝arXiv		2020
73	Adaptive Adversarial Attack on Graph Embedding via GAN	⚔Attack	📝SocialSec		2020
74	Scalable Adversarial Attack on Graph Neural Networks with Alternating Direction Method of Multipliers	⚔Attack	📝arXiv		2020
75	Attacking Graph-Based Classification without Changing Existing Connections	⚔Attack	📝ACSAC		2020
76	Cross Entropy Attack on Deep Graph Infomax	⚔Attack	📝IEEE ISCAS		2020
77	A Targeted Universal Attack on Graph Convolutional Network	⚔Attack	📝arXiv	Code	2020
78	Query-free Black-box Adversarial Attacks on Graphs	⚔Attack	📝arXiv		2020
79	Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs	⚔Attack	📝arXiv		2020
80	Efficient Evasion Attacks to Graph Neural Networks via Influence Function	⚔Attack	📝arXiv		2020
81	Backdoor Attacks to Graph Neural Networks	⚔Attack	📝SACMAT	Code	2020
82	Link Prediction Adversarial Attack Via Iterative Gradient Attack	⚔Attack	📝IEEE Trans		2020
83	Adversarial Attack on Hierarchical Graph Pooling Neural Networks	⚔Attack	📝arXiv		2020
84	Manipulating Node Similarity Measures in Networks	⚔Attack	📝AAMAS		2020
85	Indirect Adversarial Attacks via Poisoning Neighbors for Graph Convolutional Networks	⚔Attack	📝BigData		2020
86	Adversarial Attacks on Link Prediction Algorithms Based on Graph Neural Networks	⚔Attack	📝Asia CCS		2020
87	MGA: Momentum Gradient Attack on Network	⚔Attack	📝arXiv		2020
88	Adversarial Attacks to Scale-Free Networks: Testing the Robustness of Physical Criteria	⚔Attack	📝arXiv		2020
89	Adversarial Perturbations of Opinion Dynamics in Networks	⚔Attack	📝arXiv		2020
90	Network disruption: maximizing disagreement and polarization in social networks	⚔Attack	📝arXiv	Code	2020
91	Adversarial attack on BC classification for scale-free networks	⚔Attack	📝AIP Chaos		2020
92	Attacking Graph Convolutional Networks via Rewiring	⚔Attack	📝arXiv		2019
93	Unsupervised Euclidean Distance Attack on Network Embedding	⚔Attack	📝arXiv		2019
94	Generalizable Adversarial Attacks with Latent Variable Perturbation Modelling	⚔Attack	📝arXiv		2019
95	Vertex Nomination, Consistent Estimation, and Adversarial Modification	⚔Attack	📝arXiv		2019
96	Network Structural Vulnerability A Multi-Objective Attacker Perspective	⚔Attack	📝IEEE Trans		2019
97	Multiscale Evolutionary Perturbation Attack on Community Detection	⚔Attack	📝arXiv		2019
98	GA Based Q-Attack on Community Detection	⚔Attack	📝TCSS		2019
99	Attacking Graph-based Classification via Manipulating the Graph Structure	⚔Attack	📝CCS		2019
100	Fake Node Attacks on Graph Convolutional Networks	⚔Attack	📝arXiv		2018
101	Data Poisoning Attack against Unsupervised Node Embedding Methods	⚔Attack	📝arXiv		2018
102	Fast Gradient Attack on Network Embedding	⚔Attack	📝arXiv		2018
103	Attack Tolerance of Link Prediction Algorithms: How to Hide Your Relations in a Social Network	⚔Attack	📝arXiv		2018
104	Hiding Individuals and Communities in a Social Network	⚔Attack	📝Nature Human Behavior		2018
105	Attacking Similarity-Based Link Prediction in Social Networks	⚔Attack	📝AAMAS		2018
106	Practical Attacks Against Graph-based Clustering	⚔Attack	📝CCS		2017
107	Towards Robust Graph Neural Networks via Adversarial Contrastive Learning	🛡Defense	📝BigData		2023
108	Mind Your Solver! On Adversarial Attack and Defense for Combinatorial Optimization	🛡Defense	📝arXiv	Code	2022
109	Learning Robust Representation through Graph Adversarial Contrastive Learning	🛡Defense	📝arXiv		2022
110	GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks	🛡Defense	📝arXiv		2022
111	Graph Neural Network for Local Corruption Recovery	🛡Defense	📝arXiv	Code	2022
112	How Does Bayesian Noisy Self-Supervision Defend Graph Convolutional Networks?	🛡Defense	📝Neural Processing Letters		2022
113	Exploring High-Order Structure for Robust Graph Structure Learning	🛡Defense	📝arXiv		2022
114	GUARD: Graph Universal Adversarial Defense	🛡Defense	📝arXiv	Code	2022
115	Detecting Topology Attacks against Graph Neural Networks	🛡Defense	📝arXiv		2022
116	LPGNet: Link Private Graph Networks for Node Classification	🛡Defense	📝arXiv		2022
117	EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks	🛡Defense	📝arXiv		2022
118	Bayesian Robust Graph Contrastive Learning	🛡Defense	📝arXiv	Code	2022
119	Appearance and Structure Aware Robust Deep Visual Graph Matching: Attack, Defense and Beyond	🛡Defense	📝CVPR	Code	2022
120	Large-Scale Privacy-Preserving Network Embedding against Private Link Inference Attacks	🛡Defense	📝arXiv		2022
121	Robust Graph Neural Networks via Ensemble Learning	🛡Defense	📝Mathematics		2022
122	AN-GCN: An Anonymous Graph Convolutional Network Against Edge-Perturbing Attacks	🛡Defense	📝IEEE TNNLS		2022
123	Robust Graph Neural Networks using Weighted Graph Laplacian	🛡Defense	📝SPCOM	Code	2022
124	ARIEL: Adversarial Graph Contrastive Learning	🛡Defense	📝arXiv*·		2022
125	NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs	🛡Defense	📝arXiv		2022
126	IoT-based Android Malware Detection Using Graph Neural Network With Adversarial Defense	🛡Defense	📝IEEE IOT		2022
127	Robust cross-network node classification via constrained graph mutual information	🛡Defense	📝KBS		2022
128	Defending Against Backdoor Attack on Graph Nerual Network by Explainability	🛡Defense	📝arXiv		2022
129	FocusedCleaner: Sanitizing Poisoned Graphs for Robust GNN-based Node Classification	🛡Defense	📝arXiv		2022
130	On the Vulnerability of Graph Learning based Collaborative Filtering	🛡Defense	📝TIS		2022
131	GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks	🛡Defense	📝LoG	Code	2022
132	You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets	🛡Defense	📝LoG	Code	2022
133	Robust Graph Representation Learning via Predictive Coding	🛡Defense	📝arXiv		2022
134	FocusedCleaner: Sanitizing Poisoned Graphs for Robust GNN-based Node Classification	🛡Defense	📝arXiv		2022
135	How effective are Graph Neural Networks in Fraud Detection for Network Data?	🛡Defense	📝arXiv		2021
136	Graph Sanitation with Application to Node Classification	🛡Defense	📝arXiv		2021
137	A Robust and Generalized Framework for Adversarial Graph Embedding	🛡Defense	📝arXiv	Code	2021
138	Unveiling Anomalous Nodes Via Random Sampling and Consensus on Graphs	🛡Defense	📝ICASSP		2021
139	Improving Robustness of Graph Neural Networks with Heterophily-Inspired Designs	🛡Defense	📝arXiv		2021
140	On Generalization of Graph Autoencoders with Adversarial Training	🛡Defense	📝ECML		2021
141	DeepInsight: Interpretability Assisting Detection of Adversarial Samples on Graphs	🛡Defense	📝ECML		2021
142	Robust Counterfactual Explanations on Graph Neural Networks	🛡Defense	📝arXiv		2021
143	Enhancing Robustness and Resilience of Multiplex Networks Against Node-Community Cascading Failures	🛡Defense	📝IEEE TSMC		2021
144	Robust Graph Learning Under Wasserstein Uncertainty	🛡Defense	📝arXiv		2021
145	Towards Robust Graph Contrastive Learning	🛡Defense	📝arXiv		2021
146	Interpretable Stability Bounds for Spectral Graph Filters	🛡Defense	📝arXiv		2021
147	Unified Robust Training for Graph NeuralNetworks against Label Noise	🛡Defense	📝arXiv		2021
148	An Introduction to Robust Graph Convolutional Networks	🛡Defense	📝arXiv		2021
149	E-GraphSAGE: A Graph Neural Network based Intrusion Detection System	🛡Defense	📝arXiv		2021
150	Spatio-Temporal Sparsification for General Robust Graph Convolution Networks	🛡Defense	📝arXiv		2021
151	Robust graph convolutional networks with directional graph adversarial training	🛡Defense	📝Applied Intelligence		2021
152	Detection and Defense of Topological Adversarial Attacks on Graphs	🛡Defense	📝AISTATS		2021
153	Unveiling the potential of Graph Neural Networks for robust Intrusion Detection	🛡Defense	📝arXiv	Code	2021
154	Adversarial Robustness of Probabilistic Network Embedding for Link Prediction	🛡Defense	📝arXiv		2021
155	EGC2: Enhanced Graph Classification with Easy Graph Compression	🛡Defense	📝arXiv		2021
156	LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis	🛡Defense	📝arXiv		2021
157	Structure-Aware Hierarchical Graph Pooling using Information Bottleneck	🛡Defense	📝IJCNN		2021
158	Mal2GCN: A Robust Malware Detection Approach Using Deep Graph Convolutional Networks With Non-Negative Weights	🛡Defense	📝arXiv		2021
159	CoG: a Two-View Co-training Framework for Defending Adversarial Attacks on Graph	🛡Defense	📝arXiv		2021
160	Releasing Graph Neural Networks with Differential Privacy Guarantees	🛡Defense	📝arXiv		2021
161	A Lightweight Metric Defence Strategy for Graph Neural Networks Against Poisoning Attacks	🛡Defense	📝ICICS	Code	2021
162	Node Feature Kernels Increase Graph Convolutional Network Robustness	🛡Defense	📝arXiv	Code	2021
163	On the Relationship between Heterophily and Robustness of Graph Neural Networks	🛡Defense	📝arXiv		2021
164	Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation	🛡Defense	📝arXiv		2021
165	Towards Robust Reasoning over Knowledge Graphs	🛡Defense	📝arXiv		2021
166	Robust Graph Neural Networks via Probabilistic Lipschitz Constraints	🛡Defense	📝arXiv		2021
167	Graph Neural Networks with Feature and Structure Aware Random Walk	🛡Defense	📝arXiv		2021
168	A Novel Defending Scheme for Graph-Based Classification Against Graph Structure Manipulating Attack	🛡Defense	📝SocialSec		2020
169	Node Copying for Protection Against Graph Neural Network Topology Attacks	🛡Defense	📝arXiv		2020
170	Anti-perturbation of Online Social Networks by Graph Label Transition	🛡Defense	📝arXiv		2020
171	Adversarial Detection on Graph Structured Data	🛡Defense	📝PPMLP		2020
172	Learning Graph Embedding with Adversarial Training Methods	🛡Defense	📝IEEE Transactions on Cybernetics		2020
173	I-GCN: Robust Graph Convolutional Network via Influence Mechanism	🛡Defense	📝arXiv		2020
174	Smoothing Adversarial Training for GNN	🛡Defense	📝IEEE TCSS		2020
175	Graph Structure Reshaping Against Adversarial Attacks on Graph Neural Networks	🛡Defense	📝None	Code	2020
176	RoGAT: a robust GNN combined revised GAT with adjusted graphs	🛡Defense	📝arXiv		2020
177	ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks	🛡Defense	📝arXiv		2020
178	Adversarial Perturbations of Opinion Dynamics in Networks	🛡Defense	📝arXiv		2020
179	Adversarial Privacy Preserving Graph Embedding against Inference Attack	🛡Defense	📝arXiv	Code	2020
180	Robust Graph Learning From Noisy Data	🛡Defense	📝IEEE Trans		2020
181	How Robust Are Graph Neural Networks to Structural Noise?	🛡Defense	📝DLGMA		2020
182	On The Stability of Polynomial Spectral Graph Filters	🛡Defense	📝ICASSP	Code	2020
183	Towards an Efficient and General Framework of Robust Training for Graph Neural Networks	🛡Defense	📝ICASSP		2020
184	Robust Collective Classification against Structural Attacks	🛡Defense	📝Preprint		2020
185	Topological Effects on Attacks Against Vertex Classification	🛡Defense	📝arXiv		2020
186	Tensor Graph Convolutional Networks for Multi-relational and Robust Learning	🛡Defense	📝arXiv		2020
187	DefenseVGAE: Defending against Adversarial Attacks on Graph Data via a Variational Graph Autoencoder	🛡Defense	📝arXiv	Code	2020
188	Dynamic Knowledge Graph-based Dialogue Generation with Improved Adversarial Meta-Learning	🛡Defense	📝arXiv		2020
189	Target Defense Against Link-Prediction-Based Attacks via Evolutionary Perturbations	🛡Defense	📝arXiv		2019
190	Examining Adversarial Learning against Graph-based IoT Malware Detection Systems	🛡Defense	📝arXiv		2019
191	Adversarial Embedding: A robust and elusive Steganography and Watermarking technique	🛡Defense	📝arXiv		2019
192	Graph Interpolating Activation Improves Both Natural and Robust Accuracies in Data-Efficient Deep Learning	🛡Defense	📝arXiv	Code	2019
193	Adversarial Defense Framework for Graph Neural Network	🛡Defense	📝arXiv		2019
194	GraphSAC: Detecting anomalies in large-scale graphs	🛡Defense	📝arXiv		2019
195	Edge Dithering for Robust Adaptive Graph Convolutional Networks	🛡Defense	📝arXiv		2019
196	Can Adversarial Network Attack be Defended?	🛡Defense	📝arXiv		2019
197	GraphDefense: Towards Robust Graph Convolutional Networks	🛡Defense	📝arXiv		2019
198	Virtual Adversarial Training on Graph Convolutional Networks in Node Classification	🛡Defense	📝PRCV		2019
199	Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications	🛡Defense	📝NAACL	Code	2019
200	Robust Graph Data Learning via Latent Graph Convolutional Representation	🛡Defense	📝arXiv		2019
201	Adversarial Personalized Ranking for Recommendation	🛡Defense	📝SIGIR	Code	2018
202	Graph Adversarial Immunization for Certifiable Robustness	🔐Certification	📝arXiv'2023		2023
203	Robust Certification for Laplace Learning on Geometric Graphs	🔐Certification	📝MSML’2021		2021
204	Certified Robustness of Graph Classification against Topology Attack with Randomized Smoothing	🔐Certification	📝GLOBECOM'2020		2020
205	On the Prediction Instability of Graph Neural Networks	⚖Stability	📝arXiv'2022		2022
206	Stability and Generalization Capabilities of Message Passing Graph Neural Networks	⚖Stability	📝arXiv'2022		2022
207	Training Stable Graph Neural Networks Through Constrained Learning	⚖Stability	📝arXiv'2021		2021
208	Stability of Graph Convolutional Neural Networks to Stochastic Perturbations	⚖Stability	📝arXiv'2021		2021
209	Graph and Graphon Neural Network Stability	⚖Stability	📝arXiv'2020		2020
210	On the Stability of Graph Convolutional Neural Networks under Edge Rewiring	⚖Stability	📝arXiv'2020		2020
211	Stability of Graph Neural Networks to Relative Perturbations	⚖Stability	📝ICASSP'2020		2020
212	Graph Neural Networks: Architectures, Stability and Transferability	⚖Stability	📝arXiv'2020		2020
213	Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method	⚖Stability	📝arXiv'2020		2020
214	Stability Properties of Graph Neural Networks	⚖Stability	📝arXiv'2019		2019
215	Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts	🚀Others	📝arXiv‘2023	Code	2023
216	We Cannot Guarantee Safety: The Undecidability of Graph Neural Network Verification	🚀Others	📝arXiv'2022		2022
217	A Systematic Evaluation of Node Embedding Robustness	🚀Others	📝LoG‘2022	Code	2022
218	FLAG: Adversarial Data Augmentation for Graph Neural Networks	🚀Others	📝arXiv'2020	Code	2020
219	Dynamic Knowledge Graph-based Dialogue Generation with Improved Adversarial Meta-Learning	🚀Others	📝arXiv'2020		2020
220	Watermarking Graph Neural Networks by Random Graphs	🚀Others	📝arXiv'2020		2020
221	Training Robust Graph Neural Network by Applying Lipschitz Constant Constraint	🚀Others	📝CentraleSupélec'2020	Code	2020
222	CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks	🚀Others	📝arXiv'2021		2021
223	Perturbation Sensitivity of GNNs	🚀Others	📝cs224w'2019		2019
224	A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability	📃Survey	📝arXiv'2022		2022
225	Trustworthy Graph Neural Networks: Aspects, Methods and Trends	📃Survey	📝arXiv'2022		2022
226	A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection	📃Survey	📝arXiv'2022		2022
227	Deep Graph Structure Learning for Robust Representations: A Survey	📃Survey	📝arXiv'2021		2021
228	Robustness of deep learning models on graphs: A survey	📃Survey	📝AI Open'2021		2021
229	Graph Neural Networks Methods, Applications, and Opportunities	📃Survey	📝arXiv'2021		2021
230	A Survey of Adversarial Learning on Graph	📃Survey	📝arXiv'2020		2020
231	Graph Neural Networks Taxonomy, Advances and Trends	📃Survey	📝arXiv'2020		2020
232	Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack	📃Survey	📝arXiv'2022		2022
233	Adversarial Attacks and Defenses in Images, Graphs and Text: A Review	📃Survey	📝arXiv'2019		2019
234	Deep Learning on Graphs: A Survey	📃Survey	📝arXiv'2018		2018
235	Adversarial Attack and Defense on Graph Data: A Survey	📃Survey	📝arXiv'2018		2018
236	GreatX: A graph reliability toolbox based on PyTorch and PyTorch Geometric	⚙Toolbox	📝arXiv’2022	GreatX	2022
237	Evaluating Graph Vulnerability and Robustness using TIGER	⚙Toolbox	📝arXiv‘2021	TIGER	2021