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Dioptra Test Platform

Metadata Updated: September 11, 2024

Source code, documentation, and examples of use of the source code for the Dioptra Test Platform.Dioptra is a software test platform for assessing the trustworthy characteristics of artificial intelligence (AI). Trustworthy AI is: valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair - with harmful bias managed1. Dioptra supports the Measure function of the NIST AI Risk Management Framework by providing functionality to assess, analyze, and track identified AI risks.Dioptra provides a REST API, which can be controlled via an intuitive web interface, a Python client, or any REST client library of the user's choice for designing, managing, executing, and tracking experiments. Details are available in the project documentation available at https://pages.nist.gov/dioptra/.Use CasesWe envision the following primary use cases for Dioptra:- Model Testing: -- 1st party - Assess AI models throughout the development lifecycle -- 2nd party - Assess AI models during acquisition or in an evaluation lab environment -- 3rd party - Assess AI models during auditing or compliance activities- Research: Aid trustworthy AI researchers in tracking experiments- Evaluations and Challenges: Provide a common platform and resources for participants- Red-Teaming: Expose models and resources to a red team in a controlled environmentKey PropertiesDioptra strives for the following key properties:- Reproducible: Dioptra automatically creates snapshots of resources so experiments can be reproduced and validated- Traceable: The full history of experiments and their inputs are tracked- Extensible: Support for expanding functionality and importing existing Python packages via a plugin system- Interoperable: A type system promotes interoperability between plugins- Modular: New experiments can be composed from modular components in a simple yaml file- Secure: Dioptra provides user authentication with access controls coming soon- Interactive: Users can interact with Dioptra via an intuitive web interface- Shareable and Reusable: Dioptra can be deployed in a multi-tenant environment so users can share and reuse components

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

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Dates

Metadata Created Date September 11, 2024
Metadata Updated Date September 11, 2024
Data Update Frequency R/P3M

Metadata Source

Harvested from NIST

Additional Metadata

Resource Type Dataset
Metadata Created Date September 11, 2024
Metadata Updated Date September 11, 2024
Publisher National Institute of Standards and Technology
Maintainer
Identifier ark:/88434/mds2-3398
Data First Published 2024-07-11
Language en
Data Last Modified 2024-07-24 00:00:00
Category Information Technology:Cybersecurity
Public Access Level public
Data Update Frequency R/P3M
Bureau Code 006:55
Metadata Context https://project-open-data.cio.gov/v1.1/schema/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id a414de23-6287-4f6c-a013-ba196bde94c5
Harvest Source Id 74e175d9-66b3-4323-ac98-e2a90eeb93c0
Harvest Source Title NIST
Homepage URL https://data.nist.gov/od/id/mds2-3398
License https://www.nist.gov/open/license
Program Code 006:045
Source Datajson Identifier True
Source Hash 0c6e7d8c1c39999a7616f9908b685369260b554c36673f4e083acf8dd17a30e1
Source Schema Version 1.1

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