Biometrics: Identity Verification in a Networked World - download pdf or read online

By Samir Nanavati

ISBN-10: 0471099457

ISBN-13: 9780471099451

Biometrics applied sciences ensure id via features comparable to fingerprints, voices, and faces. through supplying elevated protection and comfort, biometrics have all started to determine frequent deployment in community, e-commerce, and retail functions. This booklet offers in-depth research of biometrics as an answer for authenticating staff and shoppers. prime authority, Samir Nanavati explores privateness, safeguard, accuracy, process layout, person perceptions, and classes discovered in biometric deployments. He additionally assesses the real-world strengths and weaknesses of best biometric applied sciences: finger-scan, iris-scan, facial-scan, voice-scan, and signature-scan. This available publication is an important step in figuring out and enforcing biometrics.

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Extra info for Biometrics: Identity Verification in a Networked World

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If a previously enrolled user presents his or her biometric data and is 28 Chapter 3 not matched in the database, he or she has fraudulently gained access to a resource as a result of a false nonmatch. False nonmatches occur because there is not a sufficiently strong correlation between a user’s verification and enrollment templates. 1 on pages 30 and 31): ➣ Changes in a user’s biometric data ➣ Changes in how a user presents biometric data ➣ Changes in the environment in which data is presented Because each of these is a fairly common occurrence, biometric systems are much more susceptible to false nonmatches than they are to false matches.

False match rates can be reduced by adjusting thresholds that adjust the level of correlation necessary for two templates to be judged a match. Why not simply set the threshold so that the odds of a false match are infinitesimal? Because as the false match rate is reduced, the false nonmatch rate increases. False match rate and false nonmatch rate are inversely related and must always be assessed in tandem: A system with a false match rate of 0 percent, but a false nonmatch rate of 50 percent, is secure but unusable.

Determining system false match rate requires knowledge of the single false Accuracy in Biometric Systems 27 match rate, the number of verification or identification attempts the user is allowed, the availability of usernames an imposter has access to, and other factors that can be determined only by looking at system process flow. Although ensuring a low system false match rate is a more complicated task than simply assessing a technology’s false match rate, it is a requirement of deploying secure biometric systems.

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Biometrics: Identity Verification in a Networked World by Samir Nanavati

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