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“Phishing” is a recent phenomenon where users are tricked into giving their username and password to strangers when they are lured to counterfeit login pages that appear to be legitimate services (e.g., Internet banking sites).Because of these inherent problems with password-based systems, designers are starting to look at alternatives, including biometric security systems.New users are provided, or asked to choose, a unique name and secret password that are associated with their account.
NOTE: This essay started out as a commissioned technical report, and then was revised as a book chapter for a book that was eventually canceled.
Since I have not found a good venue for it, I am putting it here.
Developers of biometric systems attempt to maximize this measure.
False Acceptance Rate (FAR) / False Match Rate (FMR): this measure represents the degree or frequency where biometric information from one person is falsely reported to match the biometric information from another person. True Rejection Rate (TRR) / True Non-Match Rate (TNMR): this measure represents the frequency of cases when biometric information from one person is correctly not matched to any records in a database because, in fact, that person is not in the database. False Rejection Rate (FRR) / False Non-Match Rate (FNMR): this measure represents the frequency of cases when biometric information is not matched against any records in a database when it should have been matched because the person is, in fact, in the database. These measures of biometric accuracy are interdependent in biometric systems.
The measurement of biometric accuracy is usually expressed as a percentage or proportion, with the data coming from simulations, laboratory experiments, or field trials.
There are four main measures of biometric accuracy: True Acceptance Rate (TAR) / True Match Rate (TMR): this measure represents the degree that the biometric system is able to correctly match the biometric information from the same person.First, there is a mathematical relationship between the corresponding true and false rates so that if one rate is known, the other can be calculated using 100% – X when working with percentages or 1.0 – X when working with proportions.For example, if the TMR is 98%, the FMR must be 100% – 98% = 2%.System designers must make sure that users are who they claim to be, and that the service or system is only accessed by people with the authority to do so.The most common method for implementing authentication and access control is a username and password.With a biometric access control system, the user first enrolls in a system or service and provides a biometric sample, such as a fingerprint.When they want to use the system later, they must show their biometric characteristic, usually by presenting themselves to some form of scanner, and the characteristic is compared to the previously-stored biometric “template.” If the characteristics match, then the user is granted access to the system.THE STATE OF THE ART IN BIOMETRIC PERFORMANCE Measuring Biometric Accuracy One of the most important factors in the success of a biometric system is its accuracy.This is a measure of how well the system is able to correctly match the biometric information from the same person and avoid falsely matching biometric information from different people.Your access to the NCBI website at gov has been temporarily blocked due to a possible misuse/abuse situation involving your site.This is not an indication of a security issue such as a virus or attack.