gnn_testenv

Graph Neural Network Test Environment for Anomaly Detection in Provenance Graph Data

0. Download the data

https://github.com/darpa-i2o/Transparent-Computing/blob/master/README-E3.md https://drive.google.com/drive/folders/179uDuz62Aw61Ehft6MoJCpPeBEz16VFy For the example_run.ipynb the data Engegement3/data/cadets/ta1-cadets-e3-official-2.json.tar.gz is needed.

1. Install Docker

https://docs.docker.com/engine/install/

2. Start Docker Compose

First change the path in docker-compose.yml of the volume to the path were your want to store the data e.g. :/output/ -> /home/buchta/gnn_testenv/DARPA/:/output/

cd db 
docker compose up -d
cd .. 

Adminder is available at http://localhost:8080 The database is available at localhost:5432

3. Install Pytorch Geometric

https://pytorch-geometric.readthedocs.io/en/latest/install/installation.html

4. Install the requirements.txt

pip install -r requirements.txt

5. Install optional packages for PyG based on your CUDA version

e.g.

pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cu118.html

5. Install package

pip install -e .

6. Place the data in the data folder

cp ta1-cadets-e3-official-2.json.tar.gz /home/buchta/gnn_testenv/DARPA/cadets/03_record 

7. Replace the paths in the config file

configs/eng3/cadets/cadets_03_record.ini

8. Run the Example script with Juypter Notebook