YAWNING TITAN is an abstract, graph based cyber-security simulation environment that supports the training of intelligent agents for autonomous cyber operations. YAWNING TITAN currently only supports defensive autonomous agents who face off against probabilistic red agents.
YAWNING TITAN has been designed with the following things in mind:
- Simplicity over complexity
- Minimal Hardware Requirements
- Support for a wide range of algorithms
- Enhanced agent/policy evaluation support
- Flexible environment and game rule setup
- Generation of evaluation episode visualisations (gifs)
YAWNING TITAN was publicly released on 20th July 2022 under MIT licence. It will continue to be developed through the Autonomous Resilient Cyber Defence (ARCD) project, overseen by Dstl.
Feedback on its operation, and suggestions for enhancements, is gratefully received via the Issues tab.
As the YAWNING TITAN project progresses, updates will be posted on this site.
In order to get YAWNING TITAN installed, you will need to have the following installed:
python3.8+python3-pipvirtualenv
- Navigate to the YAWNING TITAN folder and create a new python virtual environment
python3 -m venv <name_of_venv>- Activate virtual environment
source <name_of_venv>/bin/activate- Install
yawning-titaninto the environment along with all of it's dependencies
python3 -m pip install -e .This will install all of the dependencies including algorithm libraries. These libraries
all use torch. If you'd like to install tensorflow for use with Rllib, you can do this manually
or install tensorflow as an optional dependency by executing the following command python3 -m pip install -e .[tensorflow].
YAWNING TITAN comes with a full set of documentation created using the Sphinx documentation library and these can be built by using the following commands:
This will require the development dependencies to be installed - You can install these by executing
python3 -m pip install -e .[dev]
cd docs
make html
This will build the documentation as a collection of HTML files which uses the Read The Docs sphinx theme. Other build options are available but may require additional dependencies such as LaTeX and PDF. Please refer to the Sphinx documentation for your specific output requirements.
A collection of example notebooks have been provided in /notebooks and are the best place to start if you want to get a feel for YAWNING TITAN before builidng the docs and exploring
further.
If you would like to include a citation for YAWNING TITAN in your work, please cite the paper published at the ICML 2022 ML4Cyber Workshop.
@inproceedings{inproceedings,
author = {Andrew, Alex and Spillard, Sam and Collyer, Joshua and Dhir, Neil},
year = {2022},
month = {07},
title = {Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation},
maintitle = {International Confernece on Machine Learning (ICML)},
booktitle = {Workshop on Machine Learning for Cybersecurity (ML4Cyber)}
}YAWNING TITAN is released under MIT license. Please see LICENSE for details.