NIST experts discuss how biometric devices are helping law enforcement

A number of scientists, engineers and program managers discussed the many ways the agency is helping law enforcement improve investigations that depend on collecting biometric data from digital devices, at last week’s National Institute of Standards and Technology (NIST) forensics conference, according to a report by Fed Scoop.

Though the majority of the presentations focused on digital forensics, NIST scientists also discussed the recent technological advancements in human forensics, especially involving biometrics.

Elham Tabassi, an electrical engineer at NIST, discussed the agency’s Statistical Friction Ridge Analysis program, which is designed to improve the overall accuracy of fingerprint analysis.

SFRA uses a well-known methodology called Analysis, Comparison, Evaluation, and Verification, or ACE-V, in which examiners assess the value of latent fingerprints, mark features in the latent images, and identify the pairs of latent images and their potential matches using reference databases.

Though fingerprints have long been admissible in court, the lack of scientific basis of the ACE-V procedure has led many lawyers and law experts to question the forensic examiner’s bias.

A paper written by NIST experts addresses the many issues involving human error, including how an examiner’s decision can be impacted by the level of expertise, bias after being exposed to additional information in the case, or workload that can often hinder focus and attention to detail.

Tabassi discussed how these human errors can be dangerous, citing the case study of Brandon Mayfield, an American lawyer who was falsely connected to the 2004 bombing of a Madrid train station because of a fingerprint misidentification.

Under the SFRA program, NIST experts are working toward developing a universal vocabulary for explaining fingerprint analysis uncertainty in court as well as researching emerging innovative biometric technologies.

Article Topics

analysis  |  biometrics  |  fingerprint biometrics  |  forensics  |  NIST