An intro to Assessing Biometric Systems
How and where biometric systems are deployed would depend on their overall performance. Knowing what might and how to decipher the answers can help you assess the performance of those emerging solutions.
P. Jonathon Phillips Alvin Martin C. L. Wilson Mark Przybocki National Commence of Standards and Technology
and the basis of media buzz alone, you could conclude that biometric passwords will soon substitute their alphanumeric counterparts with versions that cannot be taken, forgotten, shed, or provided to another person. But you may be wondering what if the overall performance estimates of these systems is much more impressive than all their actual efficiency? To gauge the real-life overall performance of biometric systems—and to know their abilities and failings better—we need to understand the components that comprise an ideal biometric system. Within an ideal system • every members of the population have the characteristic that the biometric identiﬁes, like irises or ﬁngerprints; • each biometric personal differs by all others in the controlled inhabitants; • the biometric autographs don't change under the conditions in which they are really collected; and • the device resists countermeasures. Biometric-system evaluation quantiﬁes how well biometric systems allow for these houses. Typically, biometric evaluations require that an self-employed party style the evaluation, collect quality data, dispense the test, and analyze the results. We designed this content to provide you with sufﬁcient information to learn what inquiries to ask the moment evaluating a biometric program, and to assist you in determining if perhaps performance levels meet the requirements of your application. For example , if you are planning to use a biometric to reduce—as opposed to eliminate— fraud, then the low-performance biometric system may be sufﬁcient. However, completely exchanging
an existing home security alarm with a biometric-based one may need a high-performance biometric system, or maybe the required performance may be further than what current technology can provide. Here all of us focus on biometric applications that give the user a few control over data acquisition. These types of applications understand subjects from mug shots, passport images, and searched ﬁngerprints. Illustrations not protected include reputation from monitoring photos or perhaps from important ﬁngerprints left at against the law scene. From the biometrics that meet these kinds of constraints, tone, face, and ﬁngerprint systems have undergone the most study and testing—and as a result occupy the bulk of our debate. While eyes recognition has received much interest in the media lately, handful of independent critiques of the effectiveness have already been published.
There are two varieties of biometric systems: identiﬁcation and veriﬁcation. In identiﬁcation devices, a biometric signature of an unknown person is presented to a system. The system analyzes the new biometric signature having a database of biometric autographs of known individuals. Based on the comparison, the system studies (or estimates) the personality of the unfamiliar person out of this database. Systems that rely on identiﬁcation contain those that the authorities use to determine people by ﬁngerprints and mug pictures. Civilian applications include the ones that check for multiple applications by the same person for well being beneﬁts and driver's licenses. In veriﬁcation systems, a user presents a biometric personal and a claim that a particular identity belongs to the biometric signature. The criteria either welcomes 0018-9162/00/$10. 00 © 2000 IEEE
or perhaps rejects the claim. Alternatively, the algorithm can easily return a conﬁdence dimension of the claim's validity. Veriﬁcation applications consist of those that authenticate identity during point-of-sale deals or that control entry to computers or secure buildings. Performance figures for veriﬁcation applications vary substantially by those intended for identiﬁcation systems. The main...
Recommendations: 1 . J. P. Egan, Signal Detection Theory and ROC Research, Academic Press, New York, 75. 2 . A. Martin ain al., " The DE Curve Examination of Detection Task Overall performance, ” Proc. EuroSpeech 97, IEEE CS
Press, Mis Alamitos, Calif., 1997, pp
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