Trojan Detection Software Challenge - nlp-summary-jan2022-holdout
Round 9 Holdout DatasetThis is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform one of three tasks, sentiment classification, named entity recognition, or extractive question answering on English text. 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 410 Sentiment Classification, Named Entity Recognition, and Extractive Question Answering AI models using a small set of model architectures. Half (50%) of the models have been poisoned with an embedded trigger which causes misclassification of the input when the trigger is present.
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"006:55"
]
|
| contactPoint |
{
"fn": "Michael Paul Majurski",
"hasEmail": "mailto:michael.majurski@nist.gov"
}
|
| description | Round 9 Holdout DatasetThis is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform one of three tasks, sentiment classification, named entity recognition, or extractive question answering on English text. 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 410 Sentiment Classification, Named Entity Recognition, and Extractive Question Answering AI models using a small set of model architectures. Half (50%) of the models have been poisoned with an embedded trigger which causes misclassification of the input when the trigger is present. |
| distribution |
[
{
"title": "nlp-summary-jan2022-holdout",
"accessURL": "https://drive.google.com/drive/folders/1Pkh41erON1xFNlHQBu1wWtlhP3rt6FqI?usp=drive_link"
}
]
|
| identifier | ark:/88434/mds2-2782 |
| issued | 2023-04-07 |
| keyword |
[
"Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;"
]
|
| landingPage | https://data.nist.gov/od/id/mds2-2782 |
| language |
[
"en"
]
|
| license | https://www.nist.gov/open/license |
| modified | 2022-01-31 00:00:00 |
| programCode |
[
"006:045"
]
|
| publisher |
{
"name": "National Institute of Standards and Technology",
"@type": "org:Organization"
}
|
| theme |
[
"Information Technology:Cybersecurity",
"Information Technology:Software research"
]
|
| title | Trojan Detection Software Challenge - nlp-summary-jan2022-holdout |
