# Presentation: 902543

## C. L. Wilson

**C. L. Wilson**
**Manager, Image Group**

- Biometrics Overview of the PATRIOT Act

## Statutory Mandates

- USA Patriot Act (PL 107-56)
- Enhanced Border Security and Visa Entry Reform Act (PL 107-173)
- Develop and certify technology standard to
- verify identity of foreign nationals applying for a visa
- visa application at embassies and consulates
- background check against FBI criminal database and DHS databases and “watch lists”
- ensure person has not received visa under a different name
- verify identity of persons seeking to enter the U.S.
- verify that the person holding the travel document is the same person to whom the document was issued
- airports, land border crossings, sea entry points

## Statutory Mandates (cont)

- NIST worked together with Dept of Justice (including FBI & JMD) Dept of Homeland Security and Dept of State to develop a report on these activities to Congress under section 303a of the Border Security Act
- NIST must determine estimates of the accuracy of biometrics in the 303a report and subsequent mandatory reports.
- NIST must establish document authentication standards for tamper-resistant travel documents in the 303a report which should not conflict with ICAO mandates
- NIST must provide interoperability standards

## Status of NIST Patriot Act Projects

- Biometric accuracy determination requires use of large-scale databases for testing.
- Large realistic test samples of images have been obtained from the State Department, Homeland Security and Justice Departments and Texas, Ohio, and California.
- Initial testing will be of face and fingerprints. A large sample of iris data is presently being planned.
- All tests conducted by NIST use image-based biometrics. No tests using templates for face and fingerprint have been conducted. Most vendors state that their products only work when their proprietary templates are used.

## Results Presented in the Report to Congress

- Results show that fingerprints and face provide similar accuracy for verification when image quality is well controlled.  Uncontrolled face image quality results in a rapid accuracy decrease to less than 50%.
- Using realistic DHS (INS) data, one index fingerprint can provide 90% probability of verification with a 1% probability of false acceptance for  verification using current commercial technology.
- Tests show that for the best commercial systems using well controlled State Department  data, face recognition can provide 90% probability of verification with a 1% probability of false acceptance for verification. Outdoor illumination results in 47% probability of verification.
- Large scale identification requires four or more fingerprints. Ten flat fingerprints were recommended.

## BIOMERTIC TESTING IS SCALE DEPENDENT

- SAMPLE SIZE 100-1,000                   Proves feasibility
- SAMPLE SIZE 1,000-10,000                            Measures subject variation
- SAMPLE SIZE 10,000-1,000,000                     Measures operational quality control
- Existing government databases contain millions of entries and have widely varying quality.

## ONLY IMAGE BASED BIOMETRICS ARE INTEROPERABLE

- All fingerprint vendors claim significant accuracy loss using templates that are not their own unique proprietary pattern or minutia based templates.
- No common face template has been accepted.
- The only Iris template in use is proprietary. After these projects started an image based iris exchange standard was developed.

## DATA QUALITY IS CRITICAL

- Existing high quality public database will yield optimistic results.
- Archival databases contain data of widely variable quality.
- Demographic factors will affect the accuracy of future systems.

## Fingerprint Data Sets

## Face Data Sets

## FINGERPRINT STUDIES

- Data quality determines the results
- Lab Quality Data
- NIST SD published data
- Used to investigate Rolled-Rolled, Plain-Rolled, and Plain-Plain matching
- Operational Quality Data
- New live scan data
- Typical law enforcement data
- Low quality data
- Operational Systems
- Track NIST public domain matcher but with similar accuracy.

## FINGERPRINT EVALUATION IS MULTIVARIENT

- Image quality is a very critical parameter see: ftp://sequoyah.nist.gov/pub/nist_internal_reports/ir_7020.pdf
- Algorithms are important but vary widely in sensitivity to image quality.
- Multi finger fusion is required for many applications.

## Operational Fingerprint Data 

- May include failure to register data
- Can be nonstationary in the usual time series sense
- Has demographic variations which may be or may not be nonstationary
- Usually contains source specific factors which cause variations

## Comparison of Thumb and Index Finger Verification Using DHS 10 Print Data

## Large Scale Identification

- Database sizes will approach 50M
- Existing AFIS system
- Use 10 rolled fingerprints
- Filter the database to reduce the required matches
- NIST tests track with known IAFIS results
- hard and easy data sets are still hard and easy
- failure to acquire rates are similar

## Commercial AFIS Testing Is More Complex

- Commercial system usually have data screening, a primary matched, and multi-finger score resolution.
- Commercial systems use data screening to reduce database size.
- The primary matcher then matches the reduced database.
- Additional matches are used to resolve near matches.

## FACE STUDIES

- FRVT 2002 established a baseline for the capabilities of existing commercial technology.
- Demographic sources of variation were characterized using operational DOS data.
- Error rates were cut in half from the FRVT 2000 test.

## Factors Beyond the Control of the System Developers Are Important

- Demographic
- Age
- Gender
- Source Conditions
- Time Since Image Capture
- Archival
- Illumination
- Type of Input Device

## Identification as a Function of Illumination

## FACE VERIFICATION

- Used 3 copies of 37,437 well controlled visa images from the State Department
- Achieved 90% probability of verification at 1% false accept rate
- Achieved  70% probability of verification at 0.01% false accept rate
- Using outdoor illumination, face achieves 47% probability of verification at 1% false accept rate

## IDENTIFICATION USING FACES

- Used 37,437 well control1ed State Department visa pictures.
- Achieved 86% probability of identification at rank one on a gallery size of 500.
- Achieved 77% probability of identification at rank one on a gallery size of 10,000.

## NIST 303a Conclusions

- Not all subjects can be easily fingerprinted with existing technology. About 2% of subjects have damaged friction ridges.
-  The intelligence community often only has face data.
-  This indicates that a dual biometric system including two fingerprint images and a face image is needed to meet existing verification system requirements.

## NIST 303a Conclusions

- For identification 10 flat fingerprints were recommended and at least four are essential. Existing sensor technology dictates 8 or 10.
- Face may be used for hard to fingerprint individuals.

## Expect New Results

- Analysis and testing for both face and fingerprints is continuing.
- New questions are being raised by both the entry-exit agencies and Congress.
- New data is being acquired.
- New test are performed - FpVTE

## SDK Testing - 8 Algorithms, 12 datasets, 3.46G matches