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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).
Biometric systems use a characteristic of the user that is generally universal, stable, and unique.
Examples of biometric characteristics are fingerprints, iris images, and voice characteristics.
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.
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.It could be something as simple as a run away script or learning how to better use E-utilities, for more efficient work such that your work does not impact the ability of other researchers to also use our site.To restore access and understand how to better interact with our site to avoid this in the future, please have your system administrator contact [email protected], there is inevitably a trade-off where attempts to minimize the false matches of a system tend to decrease the frequency of true matches.System designers often have to adjust threshold values to get the best combination of true and false performance measures, and sometimes these adjustments are also available to customers who want to fine-tune their own biometric deployments.They may also write their username and password down in a place where it is easily found (e.g., taped to their computer monitor), or they may share their passwords with friends and family.Usernames and passwords can also be stolen by a variety of means, including accessing corporate databases and eavesdropping on network communications.ABSTRACT Despite the long history of using fingerprints, some key concerns still remain about the accuracy of identification, the usability of fingerprint systems in different situations, and acceptance by the users.This paper provides a review of those concerns and it provides recommendations for people considering adopting fingerprint recognition systems.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.