Research map / Graph learning / GNN architectures
On Stealing Graph Neural Network Models
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Closest papers by meaning
- GraphIP–Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It? (NeurIPS 2026 · similarity 0.90)
- CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition (ICML 2025 · similarity 0.89)
- Defending Against Model Stealing Attacks With Adaptive Misinformation (CVPR 2020 · similarity 0.88)
- Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (ICLR 2020 · similarity 0.87)
- Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach (NeurIPS 2024 · similarity 0.87)
- Exploring Query Efficient Data Generation Towards Data-Free Model Stealing in Hard Label Setting (AAAI 2025 · similarity 0.86)
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