Fingerprinting has been around for centuries, but new ways of identifying people are emerging every day. Advances in technology have opened up whole new world of intelligence data that brings with it many opportunities and challenges.
A multifactor biometric system from security firm FST21 has created a building access system that uses multifactor biometrics to identify registered and approved users. The company's In Motion Identification system uses face scanning, voice characteristics, and other physical and behavioral indicators to identify known users as they approach a building or access point.
FST21 told VentureBeat the product combines multiple technologies with as many as eight different identification schemes to achieve 99.7 percent accuracy, even when up to 100 people are approaching an entrance simultaneously. The company also claimed its product could have prevented the Washington Navy Yard shootings on September 16 and similar tragedies.
Mobile technologies such as AOptix Stratus for iPhone have the ability to integrate iris, face, fingerprint, and voice biometrics capabilities on the same smartphone or tablet. This allows mobile users to access classified information from consumer-grade devices.
Combining and analyzing the data obtained from systems like In Motion with more granular data from technologies like AOptix presents a wealth of opportunities for intelligence and law enforcement agencies. But it also carries enormous responsibility and introduces grave privacy concerns.
The 9/11 terrorist attacks created a "major watershed" in the use of biometrics in the US, according to an article at PBS.org. Congress decided a wider range of biometrics schemes was one of the ways to better secure US borders, and biometrics data collected for military and national security applications has grown exponentially.
Uni-factor biometrics databases, such as fingerprinting, were created first. Later on, these were combined into automatic multi-factor biometrics databases, which cataloged data of various biometric schemes for each person.
For example, the FBI's Next Generation Identification program is a current project to replace the agency's automated fingerprint identification capabilities with a big-data system that combines fingerprints, voice, iris, and facial recognition. This will help to identify many more subjects, especially those whose fingerprints may not be on record. A person's fingerprints may show strong physical characteristics in a fingerprint database template while facial or voice characteristics of that same person may not show up as well.
In addition, this year, the US Army created its Defense Forensics and Biometrics Agency (DFBA) by combining two operational entities: the agencies of Defense Forensics Science and Biometrics Identity Management Activity. The DFBA combines big-data, including biometrics and forensics, into one system. The agency uses big-data analytics to make better decisions on the battlefield and to help solve and prevent crime within the military.
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