Application of Biometrics

Course Description:

The Application of Biometrics course examines biometric technology as it relates to security, access control, and the authentication of individuals. Each module covers the uses and applications of biometrics and introduces the student to biometric standards and how to undertake basic research in biometrics using case studies.

Students will Learn:

  • To evaluate, analyze, and interoperate biometric data.
  • The role of biometric standards and analyze misconceptions surrounding integration by critiquing media coverage on biometrics.

Course Modules:

Module 1 – Biometric Matching Basics

  • Learning Objective: Differentiate between correct and incorrect users, recognize imposter and genuine scores, describe the function of the ROC curve, define sensitivity, understand hypothesis testing, and explain cost functions.

Module 2 – Human Biometric Sensor Interaction

  • Learning Objective: Analyze the importance of the HBSI Model, label different types of sensor interactions, define different types of token errors, explain when the False Claim HBSI Model is used, and describe the interaction classifications on the Attack Presentation HBSI Model.

Module 3 – Biometric Fusion

  • Learning Objective: List the advantages and disadvantages of single modality and multibiometrics, define multi-sensor fusion, illustrate how a multi-algorithm fusion system works, describe multi-instance fusion, and explain the advantages and disadvantages of a multi-sample fusion system.

Module 4 – Biometric Standards and Test Design

  • Learning Objective: Identify what a standard is, understand national and international standards committees, describe the work that OASIS participates in, differentiate between technology and scenario evaluations, list different types of tests and data, describe the steps of test protocol, understand the process for data collection from both the perspective of subjects and test administrators, define administrator and design errors, and list the main components of the test report.

Module 5 - Access, Interoperability, Performance, Zoo Methodology, & Research Challenges

  • Learning Objective: Describe the advantages and disadvantages of biometrics in access control, determine the right biometric for the access control scenario, identify common mistakes in the media coverage of biometrics, define entropy, list the advantages and disadvantages of interoperability, define zoo classifications, and list the steps of conducting research.

Recommended Background:

  • The course is targeted at professionals interested in learning about biometric technology and its applications.

Other Courses in the Series:

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