awhitewhale/GUARD

Implementation of the paper "GUARD: Graph Universal Adversarial Defense"

GUARD: Graph Universal Adversarial Defense

PyTorch implementation of the paper "GUARD: Graph Universal Adversarial Defense" [arXiv].

Fig. 1. An illustrative example of graph universal defense. The universal patch p can be applied to an arbitrary node (here v1) to protect it from adversarial targeted attacks by removing adversarial edges (if exist).

Requirements

• torch==1.9
• dgl==0.7.0

Datasets

• Cora (available in data/)
• Pubmed (available in data/)
• ogbn-arxiv from OGB
• Reddit from http://snap.stanford.edu/graphsage/

Install graphattack:

cd GraphAttack
pip install -e .

Quick Start

See demo.ipynb

Reproduce results in the paper

run

python evaluate_guard.py

Cite

if you find this repo helpful, please cite our work:

@article{li2022guard,
  title   = {GUARD: Graph Universal Adversarial Defense},
  author  = {Jintang Li and Jie Liao and Ruofan Wu and Liang Chen and Changhua Meng and Zibin Zheng and Weiqiang Wang},
  year    = {2022},
  journal = {arXiv preprint arXiv: Arxiv-2204.09803}
}