Biometric is the most secure and convenient authentication tool. It can not be borrowed, stolen, or forgotten and forging one is practically impossible. Biometrics measure individual’s unique physical or behavioral characteristics to recognize or authenticate their identity. Common physical biometrics include fingerprints, hand or palm geometry, retina, iris, and facial characteristics. Behavioral characters characteristics include signature, voice, keystroke pattern, and gait. Of this class of biometrics, technologies for signature and voice are the most developed.
Biometric Technologies
There are many biometric technologies to suit different types of applications. To choose the right biometric to be highly fit for the particular situation, one has to navigate through some complex vendor products and keep an eye on future developments in technology and standards. Here comes a list of biometrics :
Fingerprints
A fingerprint looks at the patterns found on a fingertip. There are a variety of approaches to fingerprint verification, such as traditional police method, using pattern-matching devices, and things like moire fringe patterns and ultrasonics. This seems to be a very good choice for in-house systems.
Hand geometry
This involves analyzing and measuring the shape of the hand. It might be suitable where there are more users or where user access the system infrequently. Accuracy can be very high if desired, and flexible performance tuning and configuration can accommodate a wide range of applications. Organizations are using hand geometry readers in various scenarios, including time and attendance recording.
Retina
A retina-based biometric involves analyzing the layer of blood vessels situated at the back of the eye. This technique involves using a low intensity light source through an optical coupler to scan the unique patterns of the retina. Retinal scanning can be quite accurate but does require the user to look into a receptacle and focus on a given point.
Iris
An iris-based biometric involves analyzing features found in the colored ring of tissue that surrounds the pupil. This uses a fairly conventional camera element and requires no close contact between the user and the reader. Further, it has the potential for higher than average template-matching performance.
Face
Face recognition analyses facial characteristics. It requires a digital camera to develop a facial image of the user for authentication. Because facial scanning needs an extra peripheral things that are not included in basic PCs, it is more of a niche market for network authentication. However, the casino industry has capitalized on this technology to create a facial database of scam artists for quick detection by security personal
Signature
Signature verification analyses the way user signs his name. Signing features such as speed, velocity, and pressure are as important as the finished signature’s static shape. People are used to signatures as a means of transaction-related identity verification.
Voice
Voice authentication is based on voice-to-print authentication, where complex technology transforms voice into text. Voice biometrics requires a microphone, which is available with PCs nowadays. Voice biometrics is to replace the currently used methods, such as PINs, passwords, or account names. But voice will be a complementary technique for finger-scan technology as many people see finger scanning as a higher authentication form.
