Lecture 1 Spring 25

Introduction to Biometrics

Course Code: SEC305

Lecture: LEC.1.1

Overview:This course provides a comprehensive investigation into biometric technology, its significance in modern security systems, and the methodologies behind its implementation.

Agenda for Lecture

• What is biometric technology? Why is it important? How does it work?

• Goals & syllabus overview: Understanding learning outcomes and expectations.

• Logistics regarding lab sessions, evaluations, and assessment structure.

What is Biometric?

Definition: Biometric technology refers to the automated recognition of individuals based on behavioral and biological characteristics, aligning with the ISO/IEC JTC1 2382-37:2012 standard. Etymology: The term biometrics derives from Greek roots, where 'bios' translates to life and 'metron' means measure, depicting the concept of measuring life characteristics for identification purposes (Morris, 1875). Source: Information obtained from "Biometrics: Past, Present and Future," presented at the IAPR/IEEE Winter School, Shenzhen, China, Jan 25, 2021.

Importance of Biometrics

Security Levels:

1. What you have: Items such as cards or tokens that can be lost or stolen.

2. What you know: Knowledge-based identifiers like passwords that are vulnerable to breaches.

3. What you are: Unique and stable biometric traits, including physical features like fingerprints, facial structure, and voice patterns.

Benefits:

• Provides natural, unique identification that is intrinsically linked to individuals.

• Difficult to forget or crack compared to traditional security measures like passwords, reducing vulnerability to unauthorized access.

Market Perspective and Statistics

• The estimated annual fraud resulting from double dipping in social welfare reaches a staggering $40 billion.

• Identity fraud accounts for approximately $450 million in Mastercard credit card fraud, highlighting the critical need for advanced security measures.

• Increasing applications in various fields such as e-commerce, passport control, and secure access systems showcase the growing relevance and importance of biometric solutions in today’s security landscape.

Applications of Biometrics

Examples:

• Iris recognition systems utilized in ATMs for secure banking transactions.

• Hand geometry recognition for secure access in various facilities.

• Fingerprint scanning technologies integrated at checkout counters for expedited customer service.

• Facial recognition technologies employed at airports for efficient passenger verification processes.

• Use of smart cards with embedded fingerprints for secure identification and access control. Source: Acuity Market Intelligence, IITD.

Processing in Biometrics

Key questions emphasize crucial areas such as fingerprint recognition, methodologies applied for facial recognition, alongside techniques for effectively distinguishing between Iris images during processing.

Course Goals & Syllabus Overview

Chapters to be Covered:

1. Biometric fundamentals (CH.1): Introduction to core concepts and principles behind biometrics.

2. Specific biometric technologies (CH.2 to CH.4): In-depth discussion of various biometric modalities and their operational functions.

3. Security concerns associated with biometrics (CH.7): Examination of security vulnerabilities and protective measures in biometric systems.

4. Performance Measures and Systems: Delve into image processing, feature extraction, and matching techniques discussed in Chapters 3, 10, 9, and 11.

Required Textbooks

• Digital Image Processing (3rd edition) by Rafael C. Gonzalez & Richard E. Woods: A foundational text on processing digital images, covering essential technical aspects.

• Digital Image Processing Using MATLAB (2nd edition) by Rafael C. Gonzalez & Richard E. Woods: An application-focused resource for implementing image processing techniques through MATLAB.

• Introduction to Biometrics by Anil K. Jain, Arun A. Ross, Karthik Nandakumar: A key resource providing detailed insights into various biometrics and their real-world applications.

Evaluation Breakdown

• Assignments (10 marks): Regular tasks that assess a student's understanding of biometric principles.

• Group Project (20 marks): Collaborative projects centered around chosen biometric implementations and a comparative analysis of their effectiveness.

• Midterm Exam (15 marks): Assessment focusing on material covered until the mid-point of the course, evaluating comprehension and analytical skills.

• Quizzes (5 marks): Short assessments to reinforce learning and ensure consistent engagement with course content.

• Final Exam (50 marks): Comprehensive evaluation covering all course material, assessing the entire range of knowledge acquired during the course.

• Note: Evaluation criteria may adapt throughout the term based on feedback and educational requirements.

Assignments

Assignments involve group-based collaboration to tackle real-world biometric-related problems, circulating approximately 4-5 throughout the term. Additionally, a project component necessitates students to analyze chosen biometric implementations critically, conducting a comparative study.

Course Policies

Strict compliance with course policies is mandatory. Students are expected to familiarize themselves with these rules to foster a productive and respectful learning environment.

Logistics Information

• Learning Management System (LMS/Teams) will serve as the primary platform for distributing course materials, resources, and updates.

• Weekly office hours will be designated for addressing student inquiries and providing additional support.

• Communication will predominantly occur through the LMS, particularly concerning announcements and addressing grade-related issues; a formal complaint protocol will be established via designated forms.

• Honor Code is in place, which emphasizes integrity in academic work including commitments against plagiarism and unauthorized assistance during assessments.

Summary of Biometrics

Biometrics represents a critical intersection of identity recognition technology within the field of Computer Science, demanding a nuanced understanding of physical or behavioral characteristics for reliable identification. Essential requirements for effective biometric systems include high processing speed, repeatability amidst varying conditions, and the flexibility of application in uncontrolled environments.

Basic Vocabulary in Biometrics

• Subject: The individual whose identity is being verified through biometric characteristics.

• Observation Domain: The range of characteristics considered for recognition, such as facial features, signatures, or other measurable metrics.

• Biometric Sample: The recorded representation of an individual's biometric characteristic, serving as a basis for recognition.

• Template: The extracted features of the biometric sample, utilized for comparison, storage, and ongoing recognition processes.

Advantages of Biometrics

• Establishes a strong and permanent identity link, enhancing security and user trust.

• Exhibits resilience against loss or forgery, unlike traditional identity verification methods.

• Offers vast applications in both identification and forensic contexts, driving innovation in security solutions.

Challenges of Biometrics

• Risks associated with stolen biometric data raise significant security concerns, emphasizing the need for robust protective measures.

• Difficulty in revoking compromised biometric traits poses challenges for users and service providers alike.

• Variability in conditions may result in false match and non-match rates, complicating the accuracy of biometric recognition systems.

Types of Biometric Recognition

1. Physical Properties: Involves static measurements such as facial recognition, fingerprints, and hand geometry.

2. Behavioral Properties: Consists of dynamic measurements, encompassing traits such as voice recognition and signature dynamics.

Application Domains in Biometrics

• Cooperative: Systems include access control (e.g., physical buildings), border security (e.g., immigration), and law enforcement applications (e.g., criminal identification).

• Non-cooperative: Use cases focus on solutions for surveillance and forensic identification without active participation from the individuals involved.

Current and Emerging Applications

Expanding utilization in airport security, cashier-less store systems, daily-use authentication processes, and national ID initiatives highlight the evolving landscape of biometric technology.

Using Biometrics: How to Choose

Critical considerations for selecting appropriate biometric solutions include aspects of distinctiveness to reduce false identification, stability of the biometric traits: ensuring they remain unchanged over time, user acceptance to foster system trust, resistance to spoofing attacks, and practical implementation feasibility within existing infrastructure.

How Biometrics Works

• Enrollment Process: Involves capturing biometric samples, which are subsequently analyzed to extract unique features, later forming the basis for template storage.

• Recognition Process: Involves matching incoming biometric data against stored templates, employing rigorous techniques for quality control and attack detection to maintain system integrity.

Evolution of Biometrics

Charting the trajectory from the 1960s, where voice and fingerprint recognition were foundational, to modern applications integrated into mobile devices and large-scale identification systems like e-passports illustrates significant advancements in the field.

State of the Art in Biometrics

Current advancements showcase the sophistication of biometric systems, highlighting evolving research opportunities and innovations in recognition technologies to address unresolved challenges.

Unresolved Problems

Ongoing issues include the distinctiveness and variability of biometric traits, the persistence of traits over time for reliable identification, along with overarching concerns surrounding security and privacy in biometric applications.