Biometrics in Everyday Life Biometrics

Biometrics in Everyday Life

Biometrics is becoming an increasingly popular method of identifying unique human characteristics as a means of authenticating an individual's identity. Where it used to be employed exclusively in crime solving endeavors and high powered corporate or government security, the science of biometrics is quickly becoming about as commonplace as the personal computer.

The science of biometrics is ultimately based on the analysis of distinctive physical traits, such as fingerprints and retinal scans; as well as personal characteristics such as physical, biological and behavioral patterns. Examples of personal characteristics include voice pattern recognition and handwriting analysis. The overall goal of biometrics is to use modern technology to identify individuals, and authenticate their identity, in a more effective and efficient manner. According to Allan Turner "Biometric recognition can be used in the identification mode or the verification mode. In the identification mode, the system identifies a person from the entire population by searching a database for a match. In the verification mode, the biometric system authenticates a person's claimed identity from his or her previously enrolled pattern" (26).

In the business world, biometrics is primarily used as a security measure to prevent unauthorized personnel from accessing confidential data. As Clarke and Furnell, explain, in business, biometrics is based "not on what the user knows, or what they carry, but who the user is, some unique characteristic." (2) One method that is becoming more and more popular is keystroke analysis, which "authenticates the user based upon their typing characteristics" (Clarke and Furnell 1).

Keystroke analysis studies keystroke latency, or the time between successive keystrokes, as well as hold-time characteristic, or the time to press and release a key. These factors are unique to individuals, especially as research has lead from pattern recognition approach such as linear and non-linear distance techniques, z-tests and Bayesian classifiers, to algorithms such as the feed forward multi-layered perceptions algorithm, the radial basis function algorithm, and the generalized regression neural network among others. Using neural network classifiers Clarke and Furnell were able to perform classification with an error rate of only about 12%, suggesting that this approach provides cell phone users with more and better security. Overall, "the investigation has shown that ability for classification algorithms to correctly discriminate between the majority of users with a relatively good degree of accuracy based on the hold-time of a key" (9).

Clarke and Furnell go on to describe how the data collection, classification and authentication engines would work without inconveniencing the user. The system is best used by users who use cell phones regularly and is not for users with "large variations in their handset interactions" (16). In the future, cell phones with built in videoconferencing cameras could adapt facial recognition to strengthen mobile security.

Biometrics is not just used in the business world, but it is becoming a part of home security as well. For example, according to Tracy Wilson, "Biometric security systems, like the fingerprint scanner available on the IBM ThinkPad T43, is becoming more common for home use" (1). Furthermore, biometric door locks are becoming increasingly popular in home use because they are convenient (no need to fumble around looking for keys) and they are more reliable security-wise than traditional locks. They can be used by scanning one's fingerprints, retina or other parts of the body that make an individual entirely unique ("Biometric Access Control" 1).

Even public schools are not immune to the growing biometrics trend, as the scanning of the literal 'student body' is becoming commonplace. Some schools use portable scanners to collect digital images of the students' fingerprints, which need to be updated regularly as the students grow and their fingers change. Biometrics is used for everything from the authentication of new transfer students, to providing the ability to buy lunch in the cafeteria without cash, to checking out books from the library to recording student attendance (Graziano 1).

As this trend continues to grow, there is some concern about privacy issues, which are especially sensitive when minors are involved. For example, Claudia Graziano reports in the article Learning to Live with Biometrics, Chris Hoofnagle, associate director of the Electronic Privacy Information Center in Washington, D.C. believes that fingerprint scanning schools "sets a dark precedent, conditioning students at a young age to embrace the idea of Big Brother-style biometric tracking...If ever there was a generation that would not oppose a government system for universal ID, it's this one" (1)

It is certainly understandable that biometrics would conjure up images of futuristic Orwellian disaster scenarios. However according Graziano the main complaint of using fingerprint scanning schools is not about privacy but about a lack of efficiency and convenience. Graziano reports that Bob Engen, president of Educational Biometric Technology, suggests that "speed, not security or privacy, seems to be students' biggest concern with the system. The fingerprint-recognition systems tend to run slowly - slower than manually punching in a number, for instance - if a school is using a computer that is more than a few years old. Additionally, large student populations can slow the system since it has to run through every stored image before identifying the best match" (1).