DHS · DHS-134 · record R1798

Synthetic data for improved Automated Threat Recognition (ATR) in checkpoint screening

Department of Homeland Security · TSA

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: High-impactSource: a) High-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: Not reported

Mission

Topic area: Transportation
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Images are used to train Automated Threat Recognition (ATR) and other AI models and systems to detect prohibited items in the screening processes.

Expected benefits

To create synthetic data that can be used to improve Automated Threat Recognition (ATR) algorithm development. Synthetic data can be quicker to produce which will improve effectiveness by addressing and adapting to new threats quicker. Accessible Property Screening (APS) and On-Person Screening (OPS) are working with vendors and evaluating AI-based synthetic data generation techniques to bolster the pool of training data available to develop machine learning algorithms in ATR applications.

System outputs

Images that mimic the human body and various threats.

Technology

AI classification: Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported