# Introduction to HEART

HEART is a Python extension library for Machine Learning Security that builds on the popular adversarial robustness
algorithms in the Adversarial Robustness Toolbox (ART).

The extension library is operation-ready and tailored for real-world DoD use cases, offering essential adversarial
robustness methods within the three evaluation tool dimensions: physical realizability, perturbation type, black/white
box. HEART allows the user to leverage core ART algorithms, while providing additional benefits to the AI Test &
Evaluation (T&E) engineer:

- Support for T&E of models for DoD use cases (developers, researchers and evaluators focused on adversarial machine
  learning capabilities)
- Alignment to MAITE protocols to access this subset of ART and other JATIC tools for seamless T&E workflows
- Essential subset of adversarial robustness methods for targeted AI security coverage
- Assessment quality assurance in the form of metadata
- In-depth support for users in the form of guides and examples
- Front-end application for low-code users: HEART Gradio Application

## Additional Resources

HEART is a curated subset of tools from the
[Adversarial Robustness Toolbox](https://github.com/Trusted-AI/adversarial-robustness-toolbox), an open-source library
maintained by Linux Foundation AI and Data Foundation.

HEART fits into a broader ecosystem of T&E tools as a part of the Joint AI Test Infrastructure Capability (JATIC). Learn
about the program and other capabilities via the [CDAO JATIC Public Documentation](https://cdao.pages.jatic.net/public/).