EXAMPLE CLASS – IT 
54500
COURSE OVERVIEW 
• This course examines biometric technology as 
it relates to security, access control, and the 
authentication of individuals.
• Introduction to biometrics, examining basic terminology 
• Understanding of biometric modalities, potential uses, concentrating on 
the applied nature, to enable business practitioners to understand how 
biometric modalities work 
• Evaluation and analysis of biometric data, and interpretation of data 
• Critiquing media on biometrics, and understanding misconceptions for 
integration 
• Conducting analysis, answering challenges 
• Understand the role of biometric standards 
• Recall the main biometric vendors and understand the state of the art 
products 
LEARNING OBJECTIVES
COURSE LAYOUT 
•Main course activities 
•Class project 
• Individual project 
•Dissemination
BUILDING BLOCKS 
•Each course is divided up into building blocks, 
including 
• Fundamentals 
• Modalities 
• Integration 
• Research
FUNDAMENTAL BUILDING BLOCKS 
• Overview of the historical events 
• Identification 
• General Biometric Model 
• Decision Making, Identification and Verification 
• Seven biometric attributes 
• Ten system attributes 
• Biometric integration 
• Biometric matching errors 
• Introduction to performance
MODALITIES BUILDING BLOCKS 
•Four module blocks that cover fingerprint, face, 
iris, and others
FINGERPRINT RECOGNITION 
• Introduction to fingerprint recognition, including the 
formation of fingerprints, skin anatomy, Henry 
classifications, and global and local features 
• Historical players and key events 
• Feature recognition and extraction 
• Sensors 
• Deployments
IRIS RECOGNITION 
• Structure of the eye 
•Deployments 
• Enrollment challenges 
•Components of the eye 
• Acquisition technology 
• Image quality
FACE RECOGNITION 
• History 
•General concepts 
• Feature extraction 
•Performance 
• Acquisition
OTHER BIOMETRIC MODALITIES 
• Corneal topography 
• Ear recognition 
• Retina recognition 
• Dynamic signature verification 
• Dynamic signature forgery 
• Hand geometry 
• Vein sensors
INTEGRATION BUILDING BLOCKS 
•Four modules that provide an overview to 
accessing and integrating biometrics
BIOMETRIC MATCHING BASICS 
• Enrollment 
• Genuine and impostor distributions 
• Score histograms 
• Threshold 
• ROC and DET 
• Calculation of EER 
• Interpretation of performance reports
HUMAN BIOMETRIC SENSOR 
INTERACTION 
• Historical context 
• Basic definitions 
•Token HBSI 
• False claim HBSI 
• Attack presentation HBSI
BIOMETRIC FUSION 
•Overview of biometric fusion 
• Multi-sensor biometric fusion 
• Multi-algorithm biometric fusion 
• Multi-instance biometric fusion 
• Multi-sample biometric fusion
BIOMETRIC STANDARDS 
• Introduction to standards 
•Importance of standards 
•ISO/IEC 
• Standardization activity in biometrics
DESIGNING AND CONDUCTING A TEST 
•Basic concepts 
•Developing a test protocol 
•Test administrator error 
•Design errors 
• Best practices
WRITING A TEST REPORT 
•Components of a test report 
• Interpreting a test report
INTEROPERABILITY 
• Sensor interoperability 
• Benefits of interoperability 
•Fingerprint interoperability – research use case
RESEARCH 
• Opportunities for individual research projects
ANSWERING RESEARCH CHALLENGES 
•Working through research challenges
EXAMPLES INCLUDE: PERFORMANCE AND 
ZOO METHODOLOGY 
•Zoo menagerie 
• Zoo plots 
•Zoo and force level research
COURSE AVAILABILITY 
•Available online, on-demand, and on the West 
Lafayette, IN campus 
•Offered fall / spring semesters 
• 3 credit hours

IT 54500 overview

  • 1.
  • 2.
    COURSE OVERVIEW •This course examines biometric technology as it relates to security, access control, and the authentication of individuals.
  • 3.
    • Introduction tobiometrics, examining basic terminology • Understanding of biometric modalities, potential uses, concentrating on the applied nature, to enable business practitioners to understand how biometric modalities work • Evaluation and analysis of biometric data, and interpretation of data • Critiquing media on biometrics, and understanding misconceptions for integration • Conducting analysis, answering challenges • Understand the role of biometric standards • Recall the main biometric vendors and understand the state of the art products LEARNING OBJECTIVES
  • 4.
    COURSE LAYOUT •Maincourse activities •Class project • Individual project •Dissemination
  • 5.
    BUILDING BLOCKS •Eachcourse is divided up into building blocks, including • Fundamentals • Modalities • Integration • Research
  • 6.
    FUNDAMENTAL BUILDING BLOCKS • Overview of the historical events • Identification • General Biometric Model • Decision Making, Identification and Verification • Seven biometric attributes • Ten system attributes • Biometric integration • Biometric matching errors • Introduction to performance
  • 7.
    MODALITIES BUILDING BLOCKS •Four module blocks that cover fingerprint, face, iris, and others
  • 8.
    FINGERPRINT RECOGNITION •Introduction to fingerprint recognition, including the formation of fingerprints, skin anatomy, Henry classifications, and global and local features • Historical players and key events • Feature recognition and extraction • Sensors • Deployments
  • 9.
    IRIS RECOGNITION •Structure of the eye •Deployments • Enrollment challenges •Components of the eye • Acquisition technology • Image quality
  • 10.
    FACE RECOGNITION •History •General concepts • Feature extraction •Performance • Acquisition
  • 11.
    OTHER BIOMETRIC MODALITIES • Corneal topography • Ear recognition • Retina recognition • Dynamic signature verification • Dynamic signature forgery • Hand geometry • Vein sensors
  • 12.
    INTEGRATION BUILDING BLOCKS •Four modules that provide an overview to accessing and integrating biometrics
  • 13.
    BIOMETRIC MATCHING BASICS • Enrollment • Genuine and impostor distributions • Score histograms • Threshold • ROC and DET • Calculation of EER • Interpretation of performance reports
  • 14.
    HUMAN BIOMETRIC SENSOR INTERACTION • Historical context • Basic definitions •Token HBSI • False claim HBSI • Attack presentation HBSI
  • 15.
    BIOMETRIC FUSION •Overviewof biometric fusion • Multi-sensor biometric fusion • Multi-algorithm biometric fusion • Multi-instance biometric fusion • Multi-sample biometric fusion
  • 16.
    BIOMETRIC STANDARDS •Introduction to standards •Importance of standards •ISO/IEC • Standardization activity in biometrics
  • 17.
    DESIGNING AND CONDUCTINGA TEST •Basic concepts •Developing a test protocol •Test administrator error •Design errors • Best practices
  • 18.
    WRITING A TESTREPORT •Components of a test report • Interpreting a test report
  • 19.
    INTEROPERABILITY • Sensorinteroperability • Benefits of interoperability •Fingerprint interoperability – research use case
  • 20.
    RESEARCH • Opportunitiesfor individual research projects
  • 21.
    ANSWERING RESEARCH CHALLENGES •Working through research challenges
  • 22.
    EXAMPLES INCLUDE: PERFORMANCEAND ZOO METHODOLOGY •Zoo menagerie • Zoo plots •Zoo and force level research
  • 23.
    COURSE AVAILABILITY •Availableonline, on-demand, and on the West Lafayette, IN campus •Offered fall / spring semesters • 3 credit hours