pytorch-gnn-meta-attack

pytorch implementation of gnn meta attack (mettack). This repository is the pytorch implementation of the graph attack paper: Adversarial Attacks on Graph Neural Networks via Meta Learning

Tensorflow implementation can be found here

This method is included in DeepRobust, a very easy-to-use PyTorch Attack/Defense Library.

Requirements

• Python 3.6 or newer
• numpy
• scipy
• scikit-learn
• pytorch 1.0 or newer
• matplotlib (for plotting the results)
• seaborn (for plotting the results)

Usage

To test the model, use the following command

python test_metattack.py

You can also add some additional configs

python test_metattack.py --dataset cora --ptb_rate 0.05 --model Meta-Self

The results on three datasets:

Cora	Citeseer	Polblogs