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Evaluating biometrics by using a hybrid MCDM model.

Hung-Jia Tsuei1, Guiping Shen2, Gwo-Hshiung Tzeng3

  • 1College of Artificial Intelligence, Yango University, Fuzhou, 350015, Fujian, China.

Scientific Reports
|October 22, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a hybrid decision-making model to enhance biometric system performance. Usability is the top priority for improvement, while universality significantly influences all factors.

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Area of Science:

  • Computer Science
  • Information Security

Background:

  • Biometrics technology is widely adopted across industries like consumer electronics, IoT, and finance.
  • Effective evaluation and improvement of biometric system performance are crucial for administrators.

Purpose of the Study:

  • To develop a decision-making model for evaluating and enhancing biometric system performance.
  • To identify key criteria and their interrelationships for optimizing biometric system design.

Main Methods:

  • Employs a hybrid multiple criteria decision-making (MCDM) model.
  • Integrates Decision-Making Trial and Evaluation Laboratory (DEMATEL) and DEMATEL-based Analytic Network Process (DANP).

Main Results:

  • Empirical results reveal self-effect relationships among biometric criteria.
  • Usability is identified as the primary dimension for administrators to enhance.
  • Universality emerged as the most influential criterion, systematically affecting others.

Conclusions:

  • The hybrid MCDM model provides a framework for optimizing biometric systems.
  • Administrators should prioritize usability and consider universality for comprehensive system improvement.
  • Improving recognition rates, biometric conditions, and permanence are key areas for performance enhancement.