Comments on NISTIR 8269 (A Taxonomy and Terminology of Adversarial Machine Learning)
• White Paper
Feedback to the U.S. National Institute of Standards and Technology (NIST) about NIST IR 8269, a draft report detailing the proposed taxonomy and terminology of Adversarial Machine Learning (AML).
Publisher
Software Engineering Institute
Topic or Tag
Abstract
The U.S. National Institute of Standards and Technology (NIST) recently held a public comment period on their draft report on proposed taxonomy and terminology of Adversarial Machine Learning (AML). NIST IR 8269 is an important effort to improve understanding and build a community that includes academic ML as well as other areas of academia, government, and industry. To support that broad community building, April Galyardt, Nathan VanHoudnos, and Jonathan M. Spring collaborated to provide feedback to NIST.