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68 results found

Trojan Detection Software Challenge - image-classification-sep2022-train

Data provided by  National Institute of Standards and Technology

Round 11 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of image classification AIs trained on synthetic image data build from Cityscapes. 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 288 AI models using a small set of model architectures.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0

NIST DART-MS Forensics Database (is-CID)

Data provided by  National Institute of Standards and Technology

The NIST DART-MS Forensics Database is an evaluated collection of in-source collisionally-induced dissociation (is-CID) mass spectra of compounds of interest to the forensics community (e.g. seized drugs, cutting agents, etc.). The is-CID mass spectra were collected using Direct Analysis in Real-Time (DART) Mass Spectrometry (MS), either by NIST scientists or by contributing agencies noted per compound. The database is provided as a general-purpose structure data file (.SDF).

Tags: Standard reference data,mass spectra,Ion Fragmentation,mass spectrometry,NIST Mass Spectral Libraries,Chemical Identification,Biosciences and Health,Security and Forensics,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - object-detection-feb2023-train

Data provided by  National Institute of Standards and Technology

Round 13 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of object detection AIs trained both on synthetic image data build from Cityscapes and the DOTA_v2 dataset. 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 128 AI models using a small set of model architectures.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - cyber-pdf-dec2022-train

Data provided by  National Institute of Standards and Technology

Round 12 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of pdf malware classification AIs trained Contaigio dataset feature vectors. 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 120 AI models using a small set of model architectures.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0

RGTM 10169

Data provided by  National Institute of Standards and Technology

NIST developed a reference material consisting of synthetic fragments of the SARS-CoV-2 virus RNA, which is the target of molecular diagnostic tests. These RNA fragments can assist in the development and validation of RT-qPCR assays for the detection SARS-CoV-2. The RNA fragments are characterized for concentration using digital PCR methods, may be used to assess limits of detection for SARS-CoV-2 assays, and may calibrate other in-house or commercial SARS-CoV-2 controls. This dataset includes data used for RTGM 10169 SARs-Cov-2 Research Grade Test Material validation.

Tags: virus,SRM,reference material,DNA,sequencing,PCR,digital PCR,Biosciences and Health,

Modified: 2024-02-22

Views: 0

NMR Interlaboratory Study of NISTmAb

Data provided by  National Institute of Standards and Technology

The NISTmAb Interlaboratory NMR Study is a joint effort between 25 organizations to evaluate the performance of two-dimensional (2D) heteronuclear NMR as used to characterize the high order structure (HOS) of proteins, with the aim of harmonizing 2D-NMR methods to support industrial use of NMR as applied to mAb therapeutics. This study features nearly equal representation between laboratories from academia, government, and industry, including 4 laboratories from regulatory agencies.

Tags: NMR,biopharmaceuticals,structure,fingerprint,comparability,biosimilarity,NISTmAb,RM 8671,Biosciences and Health,interlaboratory study,harmonization,chemometrics,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - nlp-summary-jan2022-test

Data provided by  National Institute of Standards and Technology

Round 9 Test DatasetThis is the test 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.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - nlp-summary-jan2022-holdout

Data provided by  National Institute of Standards and Technology

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.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - object-detection-jul2022-train

Data provided by  National Institute of Standards and Technology

Round 10 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of object detection AIs trained on the COCO dataset. 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 144 AI models using a small set of model architectures.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0

Trojan Detection Software Challenge - rl-lavaworld-jul2023-train

Data provided by  National Institute of Standards and Technology

Round rl-lavaworld-jul2023-train Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of Reinforcement Learning agents trained to navigate the Lavaworld Minigrid environment. 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.

Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,

Modified: 2024-02-22

Views: 0