The initial public draft of NIST AI 100-2 (2003 edition), Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations, is now available for public comment.
This NIST report on artificial intelligence (AI) develops a taxonomy of attacks and mitigations and defines terminology in the field of adversarial machine learning (AML). Taken together, the taxonomy and terminology are meant to inform other standards and future practice guides for assessing and managing the security of AI systems by establishing a common language for understanding the rapidly developing AML landscape. Future updates to the report will likely be released as attacks, mitigations, and terminology evolve.
NIST is specifically interested in comments on and recommendations for the following topics:
- What are the latest attacks that threaten the existing landscape of AI models?
- What are the latest mitigations that are likely to withstand the test of time?
- What are the latest trends in AI technologies that promise to transform the industry/society? What potential vulnerabilities do they come with? What promising mitigations may be developed for them?
- Is there new terminology that needs standardization?
The public comment period for this draft is open through September 30, 2023. See the publication details for a copy of the draft and instructions for submitting comments. NIST intends to keep the document open for comments for an extended period of time to engage with stakeholders and invite contributions to an up-to-date taxonomy that serves the needs of the public
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