{"total":53,"rows":[{"id":"2204.08570","title":"A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability","created":"2022-04-18","cited_by_count":118,"area":null},{"id":"2205.07424","title":"Trustworthy Graph Neural Networks: Aspects, Methods and Trends","created":"2022-05-16","cited_by_count":89,"area":null},{"id":"2403.04468","title":"A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges","created":"2024-03-07","cited_by_count":54,"area":null},{"id":"2110.08760","title":"Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications","created":"2021-10-17","cited_by_count":52,"area":null},{"id":"2112.08331","title":"Model Stealing Attacks Against Inductive Graph Neural Networks","created":"2021-12-15","cited_by_count":50,"area":null},{"id":"2203.00949","title":"GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation","created":"2022-03-02","cited_by_count":46,"area":null},{"id":"2201.11692","title":"SSLGuard: A Watermarking Scheme for Self-supervised Learning Pre-trained Encoders","created":"2022-01-27","cited_by_count":45,"area":null},{"id":"2109.08907","title":"Releasing Graph Neural Networks with Differential Privacy Guarantees","created":"2021-09-18","cited_by_count":32,"area":null},{"id":"2201.07513","title":"Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders","created":"2022-01-19","cited_by_count":31,"area":null},{"id":"2208.11180","title":"Auditing Membership Leakages of Multi-Exit Networks","created":"2022-08-23","cited_by_count":27,"area":null},{"id":"2308.16375","title":"A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications","created":"2023-08-31","cited_by_count":22,"area":null},{"id":"2209.01100","title":"Group Property Inference Attacks Against Graph Neural Networks","created":"2022-09-02","cited_by_count":21,"area":null},{"id":"2205.10014","title":"A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection","created":"2022-05-20","cited_by_count":20,"area":null},{"id":"2207.13766","title":"Label-Only Membership Inference Attack against Node-Level Graph Neural Networks","created":"2022-07-27","cited_by_count":19,"area":null},{"id":"2301.12951","title":"Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks","created":"2023-01-30","cited_by_count":16,"area":null},{"id":"2304.08566","title":"GrOVe: Ownership Verification of Graph Neural Networks using Embeddings","created":"2023-04-17","cited_by_count":16,"area":null},{"id":"2306.09104","title":"On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation","created":"2023-06-15","cited_by_count":16,"area":null},{"id":"2306.08604","title":"A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy","created":"2023-06-14","cited_by_count":14,"area":null},{"id":"2202.02575","title":"Differentially Private Graph Classification with GNNs","created":"2022-02-05","cited_by_count":12,"area":null},{"id":"2304.08928","title":"ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees","created":"2023-04-18","cited_by_count":12,"area":null},{"id":"2311.06888","title":"Preserving Node-level Privacy in Graph Neural Networks","created":"2023-11-12","cited_by_count":11,"area":null},{"id":"2411.10023","title":"Model Inversion Attacks: A Survey of Approaches and Countermeasures","created":"2024-11-15","cited_by_count":11,"area":null},{"id":"2203.09205","title":"SoK: Differential Privacy on Graph-Structured Data","created":"2022-03-17","cited_by_count":10,"area":null},{"id":"2312.07861","title":"GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks","created":"2023-12-13","cited_by_count":8,"area":null},{"id":"2402.09299","title":"Trained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code","created":"2024-02-14","cited_by_count":8,"area":null},{"id":"2405.03911","title":"Federated Graph Condensation with Information Bottleneck Principles","created":"2024-05-07","cited_by_count":8,"area":null},{"id":"2210.00538","title":"Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation","created":"2022-10-02","cited_by_count":6,"area":null},{"id":"2209.01688","title":"On the Privacy Risks of Cell-Based NAS Architectures","created":"2022-09-04","cited_by_count":5,"area":null},{"id":"2506.07888","title":"SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark","created":"2025-06-09","cited_by_count":5,"area":null},{"id":"2110.13980","title":"Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions","created":"2021-10-26","cited_by_count":4,"area":null},{"id":"2501.10985","title":"GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models","created":"2025-01-19","cited_by_count":4,"area":null},{"id":"2506.00808","title":"Unlearning Inversion Attacks for Graph Neural Networks","created":"2025-06-01","cited_by_count":4,"area":null},{"id":"2308.13513","title":"Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs","created":"2023-08-25","cited_by_count":3,"area":null},{"id":"2405.05784","title":"Link Stealing Attacks Against Inductive Graph Neural Networks","created":"2024-05-09","cited_by_count":3,"area":null},{"id":"2405.12295","title":"Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks","created":"2024-05-20","cited_by_count":3,"area":null},{"id":"2406.16963","title":"Large Language Models for Link Stealing Attacks Against Graph Neural Networks","created":"2024-06-22","cited_by_count":3,"area":null},{"id":"2508.04894","title":"Adversarial Attacks and Defenses on Graph-aware Large Language Models (LLMs)","created":"2025-08-06","cited_by_count":3,"area":null},{"id":"2508.19641","title":"Intellectual Property in Graph-Based Machine Learning as a Service: Attacks and Defenses","created":"2025-08-27","cited_by_count":3,"area":null},{"id":"2210.11730","title":"Privacy-Preserved Neural Graph Similarity Learning","created":"2022-10-21","cited_by_count":2,"area":null},{"id":"2211.05766","title":"Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks","created":"2022-11-10","cited_by_count":2,"area":null},{"id":"2310.10124","title":"A Comprehensive Study of Privacy Risks in Curriculum Learning","created":"2023-10-16","cited_by_count":2,"area":null},{"id":"2401.12824","title":"MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage","created":"2024-01-23","cited_by_count":2,"area":null},{"id":"2410.02826","title":"LinkThief: Combining Generalized Structure Knowledge with Node Similarity for Link Stealing Attack against GNN","created":"2024-10-01","cited_by_count":2,"area":null},{"id":"2503.19070","title":"Graph-Level Label-Only Membership Inference Attack against Graph Neural Networks","created":"2025-03-24","cited_by_count":2,"area":null},{"id":"2111.05628","title":"Machine Learning Models Disclosure from Trusted Research Environments (TRE), Challenges and Opportunities","created":"2021-11-10","cited_by_count":1,"area":null},{"id":"2311.16139","title":"GNNBleed: Inference Attacks to Unveil Private Edges in Graphs with Realistic Access to GNN Models","created":"2023-11-03","cited_by_count":1,"area":null},{"id":"2403.10995","title":"Edge Private Graph Neural Networks with Singular Value Perturbation","created":"2024-03-16","cited_by_count":1,"area":null},{"id":"2601.17130","title":"Impact of Graph Structure on Membership-Inference Risk for Graph Neural Networks","created":"2026-01-23","cited_by_count":1,"area":null},{"id":"2410.01272","title":"\"No Matter What You Do\": Purifying GNN Models via Backdoor Unlearning","created":"2024-10-02","cited_by_count":0,"area":null},{"id":"2411.02809","title":"Query-Efficient Adversarial Attack Against Vertical Federated Graph Learning","created":"2024-11-05","cited_by_count":0,"area":null},{"id":"2412.05830","title":"Large Language Models Merging for Enhancing the Link Stealing Attack on Graph Neural Networks","created":"2024-12-08","cited_by_count":0,"area":null},{"id":"2507.19964","title":"Who Owns This Sample: Cross-Client Membership Inference Attack in Federated Graph Neural Networks","created":"2025-07-26","cited_by_count":0,"area":null},{"id":"2608.25727","title":"Auditing Privacy Risks in LLM-Enhanced Graph Neural Networks","created":"2026-08-26","cited_by_count":0,"area":null}],"next_cursor":null}