Biometrics is the science and technology of measuring and analyzing biological data. In information technology, this typically refers to technologies used to measure and analyze human body characteristics such as facial patterns, fingerprints, retinas, irises, voice patterns, and hand measurement. Biometrics has become a useful tool for criminal justice practitioners and for businesses that increasingly use it to market their products and to surveil consumers. Biometric technology is also increasingly being used by individuals to provide personal security as well as to protect their private information online.
This entry begins with an overview of the history of biometrics and then discusses the use of biometrics specifically for security. The entry concludes with an examination of the challenges and privacy concerns associated with the use of biometrics.
Evidence of biometrics can be traced back as far as handprints used as signatures for paintings created by cavemen. Babylonians used fingerprints on clay tablets during business transactions around 500 BCE. In 1879, the French police officer Alphonse Bertillon created the first significant advance in biometrics as a way of establishing identification among criminals. The Bertillon system established a method of measuring and recording different parts and components of the human body, especially components of the head and face, to store a detailed description of an individual that could be used in criminal investigations.
In the late 1800s, a method known as the Henry System was developed for indexing fingerprints based on the individualistic patterns and ridges of a fingerprint. This system, developed in India by police officer Azizul Haque for Inspector General of Police Edward Henry, is still widely used for classifying fingerprints. However, it has been modified so that searching can be done using computers and the Integrated Automated Fingerprint Identification System, commonly known as AFIS.
In 1936, ophthalmologist Frank Burch proposed a concept of identification using an individual’s unique iris pattern, but the first patent for the concept of an iris identification system was granted in 1987 to Drs. Leonard Flom and Aran Safir. It was not until 1995, however, that the first iris recognition product became widely available.
In the 1960s, computer scientist Woodrow W. Bledsoe developed the first semiautomatic facial recognition system. Under this system, the administrator was required to locate prominent features in photographs, such as eyes, ears, nose, and mouth, to extract useable feature points. The system was further automated in the 1970s when 21 subjective markers, such as hair color and lip thickness, were used to automate facial recognition. However, the first actual semiautomated facial recognition system was not deployed until 1988, when the Lakewood Division of the Los Angeles County Sheriff’s Department began using composite drawings of suspects to conduct database searches of digitized mugshots.
In 1986, the National Bureau of Standards—now known as the National Institutes of Standards and Technology—published a standard for the exchange of fingerprint minutiae data that was the first version of the current fingerprint interchange standards used by law enforcement agencies around the world.
True biometric systems experienced an explosion of activity in the late 1990s and early 2000s, coinciding with the emergence of computers. In 1987, mathematicians M. Kirby and L. Sirovich developed a system of eigenvectors, also known as characteristic vectors, that is associated with a system of linear equations in computer science. This helped computer scientists Matthew Turk and Alex Pentland develop a system called eigenfaces. The eigenfaces system can be used to detect faces in images, making reliable, real-time automated facial recognition possible. Besides facial recognition, the technique has also been used for handwriting analysis, lip reading, voice recognition, interpretation of sign language and hand gestures, and medical imaging analysis.
As computer technology advanced in the late 1990s and early 2000s, biometric development became more prominent, and the technology itself became faster and more accurate. Cellular telephones (and eventually smartphones) became more widely used and were equipped with biometric security features such as fingerprint scanners, which could be used to lock a person’s phone, granting exclusive access to the owner of the fingerprint. Increasingly fast and highly accurate applications, which are essentially facial recognition software, can also be purchased and downloaded onto a phone or computer tablet.
Social media platforms also use biometrics—mainly facial recognition—increasingly to promote their services. Biometrics is even being used in advertising. Companies use biometrics to measure a consumer’s emotional response at the point of engagement with an advertisement. Companies can track eye movements and facial characteristics to generate advertisements based on how people react to the advertisements they are viewing. In addition, the concept of “pay-per-gaze” has been launched, whereby viewers wear a head-mounted gaze tracker that measures the amount of time the viewer looks at an advertisement, and the advertisement is then charged accordingly.
Biometrics can be used to enhance an individual’s personal security. Biometrics offers the potential to make all passwords obsolete, and it can be used to enhance home security systems. With biometrics, a person would no longer have to remember multiple passwords because access could be granted through a simple scan of the iris, face, fingerprint, handprint, or even voice. A home could be placed on lockdown as soon as a home security system picks up some physical measurement that does not match that of a resident of the home.
Biometrics is also an advanced way to provide security for individuals and their information, and it even helps companies expand and provide more personalized products for their consumers. However, for biometrics to work there must be a database of information to run the new sample against. For a biometrics system to properly identify a person, an accurate registration sample must be taken and stored safely to guarantee that any live sample can be compared to identify that person. If the original sample is not reliable, possibly due to environmental factors or out-of-date technology, the live sample is at risk of returning a false match or false nonmatch. A false nonmatch could keep a person from accessing what is rightfully his or hers, and a false match could give a person access to an area or information that he or she should not be given.
All biometrics systems face certain obstacles that keep them from reaching perfection. Environmental factors—such as temperature, humidity, and pressure, as well as illumination and noise—can affect the ability of systems to accurately identify a person. Regardless, biometrics becomes more advanced as technology itself advances.
Public and private entities have also used biometrics for surveillance. This has raised many privacy concerns, particularly among people who are required or asked to participate in some form of biometric surveillance for work, school, or even their government. There are also concerns about the security and transparency of biometric databases. It is often difficult, if not impossible, for individuals to know exactly what data have been collected on them, how they are being used, and even how long the information is being stored. An additional concern revolves around the security of these databases. They contain valuable information and so are prime targets for hackers.
Darren A. Wheeler and Sarah Ober
See also Bioinformatics ; Biosurveillance ; Fingerprints
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