Privacy, legal issues and the use of biometric and forensic data sets are a few of the challenges that lie just ahead of adoption of biometric identification technologies. But maybe adoption is happening and we just don’t know it. Biometrics are already used in everyday life.
Have you used your fingerprint to unlock your house? How often do you use Siri to find the local weather report? Both of those are examples of the many daily uses of biometrics. The beauty is that biometrics seamlessly integrate into our human workflow.
Expanding our definition of biometrics
Biometric technologies measure physiological characteristics. And biometric identification systems are automated methods for recognizing a person based on a physical or behaviorial characteristics. The process can be used for identification (one to many) and verification (one to one). Identification answers the question, “Is this person in a given database?” Verification answers the question, “Is this person who he or she claims to be?”
Biometric identification systems broadly fit into two categories: physiological (face, fingerprint, hand geometry and iris recognition) and behavioral (signature and voice). Biometrics began in Argentina in 1891, when Juan Vucetich was creating a catalog of criminal fingerprints. This kicked off the curious history of fingerprints (the earliest general form of captured biometrics). Some believe that fingerprint ID systems were developed even earlier by Alphonse Bertillon and developed by Francis Galton’s theory of fingerprints and physiognomy.
The first step to a digitized economy
India’s Aadhaar program is the largest biometric database in the world. The Unique Identification Authority of India (UIDAI) claims that 1.05 billion Aadhar cards have been issued. This places India as a leader in the digital age: regardless of the well known social challenges India has yet to face. The Aadhaar program can be used to catalyze a national digital payments infrastructure for a country of 1.3 billion.
Often when we’re discussion biometrics, we’re talking about identification systems used in exchanges of payments. But today we’re talking about using the technology for transactions involving anything of value that can be transferred digitally, including payments in supply chain management. Initiatives undertaken for such purposes as fraud prevention, streamlining of payment standards or reinforcing a national payments infrastructure can all provide more value to consumers when combined with biometrics technology.
Examples of biometrics
There are many common examples of biometrics identifiers. What’s more interesting, however, are the uncommon examples, such as these.
- Retina recognition
- Ear recognition
- Skin reflection
- Body odor
- Lip motion
Other less common biometric identifiers that have been the focus of studies over the years include vein patterns, sweat pores, fingernail beds, hand grips, brain wave patterns, footprints and foot dynamics.
The ‘how’ behind the most commonly used biometric
Fingerprint recognition systems that use ink and paper are now less common than the inkless methods. Systems that use “live scan” fingerprint scanners are starting to emerge. These scanners use the following technological approaches: optical methods (FTIR), CMOS capacitance, thermal sensing and ultrasound sensing.
How does a fingerprint go from a scan to being useful for identification? Let’s run through the four steps.
First, after the live fingerprint scan, the technology uses the ridge ending and bifurcations on the individual’s finger to plot points known as minutiae. Every individual has different locations of the minutiae, which vary from person to person and finger to finger.
Second, with the fingerprint capture and extraction complete, the technology then creates a minutiae graph connecting the ending minutiae and the bifurcation minutiae. This forms the base for comparison.
Third, this base is then compared against an entire population for identification (one-to-many matches, as used in criminal investigations) or authentication (one-to-one matches) to compare the biometric identifier provided by someone seeking access to a system with the biometric identifier provided by the legitimate user and another piece of identifying information (password or PIN, for example). With the base completed, we can apply the security and matching technology.
Fourth, there are three primary categories of matching techniques: Image techniques, feature techniques and hybrid techniques. Image techniques apply both numerical image correlation and optical techniques to assist in matching. Feature techniques extract features from the image and construct representations from the identified extractions. Hybrid techniques combine imaging techniques and feature techniques for improved accuracy.
Biometrics standards and additional information
Interested in learning more about biometrics? There probably isn’t a better single source than the National Institute of Standards and Technology’s (NIST) biometrics standards program (with the possible exception of the ISO publications on biometrics). NIST updated its NIST Special Publication 500-290 (“Data Format for the Interchange of Fingerprint, Facial and Other Biometric Information”) with a third revision in 2015. The 615-page document is an excellent reference for anyone who wants to learn more about the details of biometrics.
Biometrics is a fascinating topic, and the underlying technology is developing quickly, with biometrics engines, workflow engines, rules engines, algorithms and databases designed for human characteristics. Simple modules such as voice biometric systems can connect to interactive voice response (IVR), automatic call distribution (ACD), computer telephony integration (CTI), customer relationship management (CRM), and desktop and mobile analytics systems to ease the consumer experience.
The next time you request access to open a bank account or begin your first day at a new job, you might be required to fill out a biometrics form for your access to company systems. Biometrics will quickly become the standard by which we measure simplicity of access to financial, medical or personal information.