Abstract

This study provides a thorough analysis of the various biometric types, including their advantages and disadvantages. It compares the different types and provides details about false acceptance and false rejection rates, along with their equations. Biometric screening systems are used to test and identify persons using their physiological or behavioral characteristics. Using only one recognition device is not suitable for identification systems. Multi-factor authentication can improve system security by using two or more kinds of security types, such as passwords and cards, but this is not an ideal security scheme. Passwords may be forgotten or inputted incorrectly, or the identification card may be stolen. To verify and classify people using their physiological attributes, biometric devices are used. These technologies can be classified as either behavioral or physiological biometrics. The former has many shortcomings, such as noisy data, inter-class similarity, intra-class variability, spoofing and universality, which reduce the system’s accuracy. The success rate of recognition and verification is, however, substantially improved by multimodal biometric sensing and processing systems, which leverage the detection or processing of two or more behavioral or physiological traits.

Highlights

  • Biometrics screening is a field of science concerned with the statistical analysis of biological data of individuals

  • A software-based biometric system consists of multiple vital components that are important for the overall identification and verification process

  • Recent progress in biometric technology has led to greater precision at a lower cost for some the biometric types, such as fingerprint and facial recognition; biometric systems are the foundation for many extremely secure identification solutions and personalized testing

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Summary

Introduction

Biometrics screening is a field of science concerned with the statistical analysis of biological data of individuals. Enterprise networks and server records are other approaches that can be used for, e.g., smart or credit cards These figures represent an improvement from specific studies published by Unisys in September 2005, which found that 61% of the world’s leading businesses considered biometrics the tool of choice to tackle fraud and money laundering. This is usually achieved using fingerprints, voice recognition, or eyeball-scanning devices when, for example, an individual is about to unlock a door or make a purchase (Galdi et al, 2013)

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