Trojan Detection Software Challenge - Round 3 Training Dataset

The data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 1008 adversarially trained, human level, image classification AI models using a variety of model architectures. The models were trained on synthetically created image data of non-real traffic signs superimposed on road background scenes. Half (50%) of the models have been poisoned with an embedded trigger which causes misclassification of the images when the trigger is present.

Data and Resources

Field Value
accessLevel public
bureauCode {006:55}
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identifier ark:/88434/mds2-2320
issued 2020-10-30
landingPage https://data.nist.gov/od/id/mds2-2320
language {en}
license https://www.nist.gov/open/license
modified 2020-10-23 00:00:00
programCode {006:045}
publisher National Institute of Standards and Technology
resource-type Dataset
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theme {"Information Technology:Software research","Information Technology:Cybersecurity","Information Technology:Computational science"}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • ckan
  • geo
  • geoss
  • national
  • north-america
  • trojan-detection-artificial-intelligence-ai-machine-learning-adversarial-machine-learning
  • united-states
isopen False
license_id other-license-specified
license_title other-license-specified
maintainer Michael Paul Majurski
maintainer_email michael.majurski@nist.gov
metadata_created 2025-11-22T21:30:52.923202
metadata_modified 2025-11-22T21:30:52.923207
notes The data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers. This dataset consists of 1008 adversarially trained, human level, image classification AI models using a variety of model architectures. The models were trained on synthetically created image data of non-real traffic signs superimposed on road background scenes. Half (50%) of the models have been poisoned with an embedded trigger which causes misclassification of the images when the trigger is present.
num_resources 29
num_tags 9
title Trojan Detection Software Challenge - Round 3 Training Dataset