Credential Authentication Technology with Camera System (CAT-2) and AutoCAT (CAT-2 in an e-gate form factor)
Description
Improving the detection of imposters.
Detailed example
The system produces a recommendation to the Transportation Security Officer (TSO) to indicate if person presenting the identity document is similar to the face on the photo ID document. In the event of a non-match, the TSO is responsible for additional identity verification steps to verify the identity of the traveler.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
The Transportation Security Administration (TSA) uses AI-based, one-to-one (1:1) and one-to-many (1:n) facial matching technologies at some checkpoints to assist human reviewers with traveler identity verification. The purpose and expected benefits of the technology include increased speed and accuracy of identity verification at the checkpoint while improving detection of imposters.
Controls / human review
ATO: Yes; PIA: https://www.dhs.gov/sites/default/files/publications/privacy-pia-tsa046b-tdc-june2020.pdf
Data needed
During the development, the original equipment manufacturer trained the technology using their own data for 1:1 facial comparison. Prior to initial deployment, DHS S&T conducted evaluation of the biometrics algorithms using volunteers for facial matching validation. During TSA's continuous evaluation, a photo is taken of the passenger and compared to the photo on the identification to determine whether it was an actual match to the individual.