Biometrics Course Notes

Agenda

• Comprehensive Overview of Biometric Systems

• Detailed Goals & Syllabus Overview

• Laboratory Work & Evaluation Criteria

What is Biometrics?

• Definition: Biometrics refers to the automated recognition of individuals based on unique physiological or behavioral characteristics. This identification process relies on:

  • Behavioral Characteristics: Traits such as voice, handwriting, or typing patterns that vary depending on an individual’s behavior.

  • Biological Characteristics: Tangible attributes like fingerprints, facial recognition, iris patterns, and more which are inherent and unique to every person.

  • Standards compliance: Refers to the International Organization for Standardization (ISO) understanding of biometrics as defined in ISO/IEC JTC1 2382-37:2012.

• Origins of the term: The word "biometrics" is derived from the Greek roots "Bios" meaning life and "Metron" meaning measure, first conceptualized in 1875 by mathematician William Morris.

Why Use Biometrics?

• Enhances Security by Utilizing:

  • What You Have: This encompasses items like identification cards or tokens, which are vulnerable to loss or theft, heightening the need for biometric systems.

  • What You Know: Relies on knowledge-based security measures such as passwords that may be vulnerable to forgetting or hacking.

  • What You Are: The focus is on unique, stable, and natural features—biometric traits— that are difficult to forget, replicate or crack.

• Application Areas:

  • E-commerce: Safeguarding online transactions to prevent unauthorized access.

  • Passport Controls: Enhancing border security by using biometric verification in travel documentation.

  • Secured Systems for Access: Implementing biometric authentication for accessing sensitive information or facilities.

  • Statistics: The realm of biometrics addresses significant issues with identity fraud, evidenced by statistics like the $40 billion lost in double-dipping cases in social welfare and $450 million annually lost to credit card fraud linked to identity theft.

Common Biometric Applications

1. Iris Recognition: An advanced method of identifying individuals through the unique patterns of their irises.

2. Hand Geometry: Measures the shape and size of a person's hand for identification purposes.

3. Fingerprint Scanning: The oldest and one of the most widely used methods of biometric identification.

4. Facial Recognition at Airports: Used for identifying travelers to ensure security compliance.

5. Smart Cards with Embedded Fingerprints: Enhancing card security via biometric data storage.

Understanding Biometrics

• Key Considerations:

  • Security and Accuracy are the paramount concerns in biometric systems ensuring that the data processed remains secure and reliable leading to effective identification.

• Explore:

  • Examination of various biometric modalities (e.g., fingerprints, facial recognition) and understanding the computational processes that allow for data processing and matching based on unique traits.

Goals & Syllabus Overview

• Topics Include:

  • Image Processing for Biometric Recognition: Techniques and algorithms used to enhance biometric data.

  • Performance Measures: Metrics that evaluate the effectiveness of biometric systems.

  • Modality Comparison: Deep dive into fingerprint, face, and iris modalities to understand strengths and weaknesses.

• Textbooks Recommended:

  • Gonzalez & Woods, "Digital Image Processing" for foundational understanding of image processing principles.

  • Jain, Ross, & Nandakumar, "Introduction to Biometrics" for a comprehensive exploration of biometric technologies and applications.

Evaluation Criteria

1. Assignments (10 marks): Group-based practical tasks emphasizing collaboration and practical application of concepts.

2. Project (20 marks): A hands-on project aimed at implementing and comparing various biometric recognition methodologies.

3. Midterm Exam (15 marks): Evaluating understanding and knowledge acquired in the first half of the course.

4. Quiz (5 marks): Short formative assessment to gauge ongoing understanding of the material.

5. Final Exam (50 marks): Comprehensive evaluation covering all aspects of the course.

   Note: Students are encouraged to review their groups’ responsibilities and assignments weekly to ensure collaborative efficiency.

Course Logistics

• Learning Management System (LMS/Teams): All relevant course materials, announcements, and updates will be made accessible.

• Weekly Office Hours: Set times to discuss issues, clarify concepts, and ask questions relating to assignments or course material.

• Communication Protocol: Communication will be facilitated through one-way announcements on LMS/Teams; issues should be reported via complaint forms, with immediate matters addressed through designated channels.

Honor Code Policies

• Strict adherence to academic integrity is expected, prohibiting any unpermitted aid in assignments or exams.

• Violations, including but not limited to plagiarism and unauthorized collaboration, will be dealt with seriously to maintain academic standards.

How Biometrics Work

• Architecture Involves:

  • Effective handling of user exceptions to ensure seamless enrollment and recognition processes in biometric systems.

• Enrollment Tasks:

  1. Supervised Sample Collection: Collecting users' biometric data under controlled conditions for accuracy.

  2. Template Generation and Storage: Creating a unique template for each individual and securely storing that data for future reference.

Practical Implementation of Biometrics

• Recognition Process:

  1. Reading biometric templates during verification.

  2. Single sample verification through comparative analysis of the user's biometric data against stored templates.

  3. Matching scores output based on the degree of similarity, leading to informed decision making regarding identity verification.

Types of Biometrics

• Physical Properties: These are static characteristics that remain relatively unchanged over time (e.g., fingerprints, facial features).

• Behavioral Properties: Dynamic traits that may vary with context, such as voice patterns and keystrokes, are often used in combination to enhance security.

Applications of Biometrics

1. Identity & Access Management: Implementing controls to accurately verify identity for secure access.

2. Law Enforcement & Forensics: Utilizing biometrics to solve crimes by identifying suspects or victims through fingerprints and facial recognition.

3. Varying Cooperative & Uncooperative Environments: Adapting biometric technologies to suit both cooperative subjects (e.g., voluntarily providing data) and uncooperative conditions where traditional methods may fail.

Evolution of Biometrics

• Historical Trends:

  • 1960s-1970s: Introduction of early applications in voice recognition and fingerprint analysis paved the way for biometric systems.

  • 1990s-Present: Rapid growth in large-scale implementations like electronic passports showcases biometrics as a pillar of modern security.

Unresolved Problems in Biometrics

1. Distinctiveness of Biometric Traits: Ensuring that each biometric trait is unique enough to avoid false positives.

2. Stability and Persistence of Traits Over Time: Addressing how biometric traits may change as individuals age.

3. Security Considerations & User Privacy: Balancing the need for security with protecting individuals’ privacy and data.

4. Potential Biases: Recognizing bias in biometric systems that can disproportionately affect certain genders or races, and working to mitigate these biases in technology design.

References

• Adam Czajka, "Biometrics CSE 40537/60537", University of Notre Dame, 2014-2019.

• Jain, Anil K., et al., "50 years of biometric research: Accomplishments, challenges, and opportunities."