Army seeks extra layer of defense

Initially considered by the Defense Department to primarily be an information assurance tool, biometrics has steadily gained momentum as a critical element in fighting the war on terrorism.

With the formation of the Biometrics Task Force (BTF) in 2006, DOD formally changed its focus on the technology to an operational level in the Army Department.

“They wanted to get the technology into the hands of the warfighters, in response to an urgent need,” said Lisa Swan, deputy director of BTF’s Integration Directorate, one of two primary components of the restructured BTF.

The other component is the Operations Directorate, which operates and maintains DOD’s authoritative database for biometrics, the Automated Biometric Identification System (ABIS).

“Offensively, biometrics are used at checkpoints to help identify potential insurgents who may be trying to blend in with the local population,” Swan said.

“Defensively, they are being used for force protection, to keep unauthorized persons from gaining access to bases.

They are also being used for census management, helping the local police to distinguish between a village’s residents and insurgents.” “In one village [in Iraq], the mayor asked U.S. forces to help him identify insurgents.

Our forces took fingerprints of people who belonged in the village and issued badges, which the residents use when they enter or leave. The badges with their electronic fingerprints are [matched with the database] at checkpoints, helping to keep strangers out. As a result, violence in this area fell dramatically.”

PROMOTING NEW TECHNOLOGY

A significant aspect of BTF’s mission is to advance biometric technology. The task force acts as a liaison for projects involving government, commercial and academic sponsors.

Gregory Alexander, a contractor at Strategic Operational Solutions, works from BTF offices to coordinate science and technology projects. He said the two main BTF initiatives are biometric technology demonstrations (BTD), which involve DOD sponsors that are seeking to improve their processes, and biometrics broad agency announcements (BAA), in which industry and academia coordinate with BTF to advance new technologies.

Noblis received funding in fiscal 2008 to work on a BAA project that seeks to expand the wavelengths at which warfighters can capture iris images.

“Current technologies capture and match iris images in the near infrared spectrum,” Alexander said. “This project will explore matching across a range of wavelengths within that spectrum, as well as into the visible spectrum.”

“A very good photograph would fall into the visible spectrum,” Alexander said. “If we could analyze that photograph against our database, we could then provide our warfighters with additional information for use in the field.” Making matches across the visual spectrum is a new technology BTF would like to see developed, he said.

Matching at different ranges across the near infrared spectrum is an existing technology, and the project would address enhancing and strengthening it to increase interoperability among systems. For fiscal 2008 and 2009, the BAA projects will receive less than $750,000.

For 2009, BTF is seeking innovative research that focuses on biometric collection and fusion. The ability to apply matching across multiple types of biometric data is considered critical because samples that rely on a single type might cause flawed results. Future technologies need to combine multiple biometric types of varying quality and origin to achieve maximum accuracy without sacrificing speed.

Funding will be made available for as many as 10 procurement contract awards that are not expected to exceed $750,000 per year.

The BTD projects, which have government sponsors, range from $100,000 to $1 million.

For example, the Army Research Office (ARO) is testing and validating an interoperable biometric fusion platform based on commercial products. The system, which would be used with large, disparate databases, can combine fingerprint, iris and facial-recognition scans and score the multiple biometric images for accuracy, then make matches based on the highest degree of accuracy available.