These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
ATLAS - Adversarial Threat Landscape for Artificial-Intelligence Systems
The goal of this project is to position attacks on machine learning (ML) systems in an ATT&CK-style framework so that security analysts can orient themselves to these new and upcoming threats.
If you are new to how ML systems can be attacked, we suggest starting at this no-frills Adversarial ML 101 aimed at security analysts.
Or if you want to dive right in, head to Adversarial ML Threat Matrix.
About the tool
You can click on the links to see the associated tools
Objective(s):
Type of approach:
Use Cases
Would you like to submit a use case for this tool?
If you have used this tool, we would love to know more about your experience.
Add use case