Computational Methods in Biometric Authentication: Statistical Methods for Performance Evaluation (Information Science and Statistics) [Hardcover]

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Biometrics, the science of utilizing physical traits to spot individuals, is playing an increasing role in our security-conscious society and across the globe. Biometric authentication, or bioauthentication, systems are increasingly being used to secure from amusement parks to bank accounts to military installations. Yet developments on this field have not been matched by an equivalent improvement in the statistical strategies to evaluating these systems. Compensating just for this need, this excellent text/reference offers a basic statistical methodology for practitioners and testers of bioauthentication devices, supplying a collection of rigorous statistical means of evaluating biometric authentication systems. This framework of methods can be extended and generalized to get a wide selection of applications and tests. This may be the first single resource on statistical strategies to estimation and comparison of the performance of biometric authentication systems. The book targets six common performance metrics: for each metric, statistical methods are derived to get a single system that incorporates confidence intervals, hypothesis tests, sample size calculations, power calculations and prediction intervals. These methods will also be extended to permit for your statistical comparison and evaluation of multiple systems for independent and paired data. Topics and features: Provides a statistical methodology for your most popular biometric performance metrics: failure to enroll (FTE), failure to obtain (FTA), false non-match rate (FNMR), false match rate (FMR), and receiver operating characteristic (ROC) curves Presents methods for your comparison of two or more biometric performance metrics Introduces a new bootstrap methodology for FMR and ROC curve estimation Supplies greater than 120 examples, using publicly available biometric data where possible Discusses the addition of prediction intervals for the bioauthentication statistical toolset Describes sample-size and power calculations for FTE, FTA, FNMR and FMR Researchers, managers and decisions makers needing to compare biometric systems across a number of metrics will discover on this reference an invaluable group of statistical tools. Written on an upper-level undergraduate or master's level audience using a quantitative background, readers may also be likely to provide an understanding in the topics in the typical undergraduate statistics course. Dr. Michael E. Schuckers is Associate Professor of Statistics at St. Lawrence University, Canton, NY, along with a member from the Center for Identification Technology Research.