Mark12Ding / GNN-Practical-Attack
Code for Towards More Practical Adversarial Attacks on Graph Neural Networks (NeurIPS 2020)
☆26Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for GNN-Practical-Attack
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆28Updated last year
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆37Updated 11 months ago
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆28Updated last year
- G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)☆26Updated 2 years ago
- Defending graph neural networks against adversarial attacks (NeurIPS 2020)☆58Updated last year
- Pytorch implementation of gnn meta attack (mettack). Paper title: Adversarial Attacks on Graph Neural Networks via Meta Learning.☆19Updated 3 years ago
- Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem☆18Updated 3 years ago
- Official repository for AAAI'23 paper: Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinf…☆21Updated last year
- code for paper TDGIA:Effective Injection Attacks on Graph Neural Networks (KDD 2021, research track)☆18Updated 3 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆25Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆82Updated last year
- A PyTorch implementation of "Backdoor Attacks to Graph Neural Networks" (SACMAT'21)☆33Updated 3 years ago
- Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22☆17Updated 2 years ago
- ☆21Updated 2 years ago
- Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph M…☆91Updated last year
- Adversarial training for Graph Neural Networks☆59Updated 3 years ago
- source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".☆26Updated 5 months ago
- Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track☆21Updated 2 months ago
- ☆52Updated 2 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆83Updated 3 weeks ago
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆57Updated last year
- Official implementation of "Graph Unlearning" (ACM CCS 2022)☆38Updated last year
- Data poisoning attack of recommend system using the algorithm of MF.☆29Updated 6 years ago
- [ICML 2023] "On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation"☆31Updated 11 months ago
- ☆25Updated last week
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆32Updated 2 years ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆60Updated 6 months ago
- This is the implementation of OODGAT from KDD'22: Learning on Graphs with Out-of-Distribution Nodes.☆22Updated 2 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆90Updated 8 months ago
- A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models☆36Updated 3 years ago