Title Slide

Title: Biometric Technology: Revolutionizing

Security in the Digital Age
Name, Module, Date, University Logo
What Is Biometric
Technology?
• Biometric technology uses unique physical
or behavioral traits to verify or
identify individuals. Unlike passwords or
tokens, biometric data is inherently
linked to the user, making it a powerful
tool for modern security.
• Common traits: Fingerprints, iris, voice,
face, gait
• Two main operations: Verification (1:1)
and Identification (1:N)
(Jain et al., 2004)
 Why Is It Emerging Now?

TRADITIONAL AUTHENTICATION IS SURGE IN AI INTEGRATION, MOBILE INCREASING DEMAND FOR SECURE AND
PRONE TO BREACHES BIOMETRICS, CLOUD STORAGE CONTACTLESS IDENTITY SYSTEMS
POST-COVID
(NIST, 2022; RATHA ET AL., 2001)
History of
Biometrics
1800s: Fingerprint classification systems
1960s: Early facial recognition algorithms
1980s–2000s: Automated fingerprint and iris systems
2013 onward: Mobile biometric revolution (Touch ID,
Face ID)
(Wayman, 2002; Shukla & Chatterjee, 2021)
How Biometric Systems Work

Data Capture: Feature Template

Sensor collects Extraction: Key Creation: Digital
raw biometric patterns are representation is
data analyzed stored

Metrics: FAR
Matching: Input (False Accept
is compared Rate), FRR (False
against templates Reject Rate)
Common Biometric Modalities

FINGERPRINT: MOST IRIS: HIGH FACE: WIDELY USED VOICE: CONVENIENT

WIDELY ADOPTED ACCURACY, LOW IN SMARTPHONES AND BUT SPOOF-PRONE
SPOOFING SURVEILLANCE
Multimodal Biometrics
• Combining two or more traits (e.g., face +
voice) improves security and reduces spoofing
risks.
• Increases system reliability
• Useful in high-security applications like
airports or finance
(Jain & Ross, 2008)
 Authentication: Confirms
claimed identity (1:1)

Biometric
Authentica
Identification: Searches
tion vs entire database (1:N)
Identifica
tion
Identification is often
used in surveillance and
law enforcement

(Maltoni et al., 2009)

AI in
Biometric
Systems
• AI boosts biometric
performance by enabling real-
time, context-aware decisions.
• Deep learning improves face
and iris recognition accuracy
• AI helps detect spoofing
attempts using liveness
detection
(Nguyen et al., 2018;
Martinez-Diaz et al., 2020)
Mobile Biometrics
•Embedded syst=ems like Apple Face ID and Samsung
fingerprint readers
•Use secure enclaves for template storage
•Enhances user convenience and device-level
security
(Apple, 2023; Android Developers, 2022)
National ID Programs

AADHAAR (INDIA): OVER 1.3 ESTONIA: E-RESIDENCY WITH ENABLES ACCESS TO

BILLION PEOPLE ENROLLED BIOMETRIC AUTHENTICATION SERVICES LIKE BANKING AND
USING IRIS AND VOTING
FINGERPRINT

UIDAI, 2022; European Commission, 2022

 Used in ATM access,
mobile banking, and fraud
detection
Biometrics
in Banking
Voice and fingerprint
authentication are
growing in digital KYC

(Lee, 2021; Mastercard, 2023)

 Patient verification,
access to medical
records

Biometric
Reduces identity fraud
Healthcare and medical errors
Systems
Telemedicine
authentication is an
emerging trend
 eGates use facial/iris
scanning for identity
verification
Airports
Reduces queue time and
and Border enhances border safety
Security
Deployed in UAE, EU,
and US
(Frontex, 2023)
 Used for law
enforcement, public
safety, and traffic
Smart control
Cities and Real-time face
recognition in public
Surveillan spaces
ce
Raises major privacy
concerns
(Fussey & Murray, 2019)
Ethical and Social Concerns

RISK OF MASS SURVEILLANCE QUESTIONS ABOUT CONSENT HIGH-PROFILE STUDIES SHOW

AND BIAS IN AI MODELS AND CONTROL OVER PERSONAL ALGORITHMIC RACIAL BIAS
DATA

(Buolamwini & Gebru, 2018)

Data Privacy and Regulation

BIOMETRIC DATA = LAWS MANDATE USER ORGANIZATIONS MUST ENSURE

“SENSITIVE DATA” UNDER CONSENT, ENCRYPTION, AND TRANSPARENCY
GDPR RETENTION CONTROL
Spoofing and Attacks

Countermeasure
Threats: fake s: liveness
fingerprints, detection,
photos, 3D pulse
masks detection
 Merges biometrics with
cryptography

Biometric Cancelable biometrics:

Cryptosyst templates can be revoked
ems or replaced
Protects templates from
being reverse-engineered
(Uludag et al., 2004)
 Non-
Advantage transferab
s of le and
unique
Biometric Easy to
s use and
fast
Low risk
of
forgetting
or losing
Enhances
user
experience

(Jain et al., 2016)

 Limitations and Challenges

High setup
Environmental Physical
costs and
noise changes
infrastructur
(lighting, (injuries,
e needs
background) aging)

(Jain et al., 2016)

Future
Trends
•Brainwave, DNA, heartbeat
biometrics under research
•Use of wearables and biometric
blockchain systems
•Rise of behavioral biometrics
(keystroke, gait)
(Martinez-Diaz et al., 2020)
 Biometric Standards
•ISO/IEC 19794 standardizes formats and interfaces
•FIDO Alliance promotes passwordless authentication
(ISO/IEC JTC 1/SC 37, 2021)
Case
Study:
Apple Face
ID
•Uses 3D facial mapping + IR
sensors
•On-device storage enhances
privacy
•Robust spoofing detection
(Apple, 2023)
Reflection and
Conclusion
• Biometric technology is transforming
identity verification in the digital age.
While it offers unmatched security and
convenience, its widespread use also
raises ethical, legal, and technical
concerns. Future success lies in creating
transparent, inclusive, and privacy-
preserving systems that build trust.
(Jain et al., 2016; Buolamwini & Gebru,
2018)
References
• Apple (2023) About Face ID. Available at: https://support.apple.com/en-us/HT208108 (Accessed: 28 June 2025).
• Android Developers (2022) BiometricPrompt API. Available at: https://developer.android.com/training/sign-in/biometric-
auth (Accessed: 28 June 2025).
• Buolamwini, J. and Gebru, T. (2018) ‘Gender shades: Intersectional accuracy disparities in commercial gender
classification’, Proceedings of the Conference on Fairness, Accountability and Transparency, pp. 77–91.
• European Commission (2022) General Data Protection Regulation (GDPR). Available at: https://gdpr.eu (Accessed: 28 June
2025).
• Frontex (2023) Biometric Border Management. Available at: https://frontex.europa.eu/ (Accessed: 28 June 2025).
• Fussey, P. and Murray, D. (2019) ‘Independent Report on the London Metropolitan Police Service’s Trial of Live Facial
Recognition Technology’, Human Rights, Big Data and Technology Project. University of Essex.
• ISO/IEC JTC 1/SC 37 (2021) Biometrics – Standardization Roadmap. International Organization for Standardization.
• Jain, A.K., Ross, A. and Prabhakar, S. (2004) ‘An introduction to biometric recognition’, IEEE Transactions on Circuits
and Systems for Video Technology, 14(1), pp. 4–20.
• Jain, A.K., Nandakumar, K. and Ross, A. (2016) ‘50 years of biometric research: Accomplishments, challenges, and
opportunities’, Pattern Recognition Letters, 79, pp. 80–105.
• Jain, A.K. and Nandakumar, K. (2012) ‘Biometric authentication: System security and user privacy’, Computer, 45(11), pp.
87–92.
• Jain, A.K. and Ross, A. (2008) Introduction to Biometrics. Boston: Springer.
• Lee, H. (2021) ‘Biometric Authentication in Financial Services’, Journal of Financial Security, 14(3), pp. 211–222.
• Maltoni, D., Maio, D., Jain, A.K. and Prabhakar, S. (2009) Handbook of Fingerprint Recognition. 2nd edn. London:
Springer.
• Marasco, E. and Ross, A. (2014) ‘A survey on antispoofing schemes for fingerprint recognition systems’, ACM Computing
Surveys, 47(2), pp. 1–36.
• Martínez-Díaz, M., Fierrez, J., and Morales, A. (2020) ‘Deep learning in biometrics: Recent advances and research
trends’, Neurocomputing, 423, pp. 215–232.
• Mastercard (2023) Biometric Payment Authentication. Available at:
https://www.mastercard.com/biometrics (Accessed: 28 June 2025).
• Nguyen, T.T., Nguyen, T., Van Nguyen, H. and Nahavandi, S. (2018) ‘Deep learning for
biometrics: A review’, Applied Soft Computing, 86, 105954.
• NIST (2022) Biometric Testing Project. National Institute of Standards and Technology.
Available at: https://www.nist.gov/programs-projects/biometric-testing (Accessed: 28
June 2025).
• Ratha, N.K., Connell, J.H. and Bolle, R.M. (2001) ‘Enhancing security and privacy in
biometrics-based authentication systems’, IBM Systems Journal, 40(3), pp. 614–634.
• Ross, A. and Jain, A.K. (2004) ‘Multimodal biometrics: An overview’, 12th European
Signal Processing Conference (EUSIPCO), pp. 1221–1224.
• Shukla, R. and Chatterjee, A. (2021) ‘Evolution of biometric security systems: From
traditional to AI-powered models’, Journal of Cyber Security Technology, 5(4), pp. 299–
316.
• UIDAI (2022) Aadhaar Dashboard. Unique Identification Authority of India. Available at:
https://uidai.gov.in/ (Accessed: 28 June 2025).
• Uludag, U., Pankanti, S., Prabhakar, S. and Jain, A.K. (2004) ‘Biometric cryptosystems:
Issues and challenges’, Proceedings of the IEEE, 92(6), pp. 948–960.
• Wayman, J.L. (2002) ‘Biometric systems overview’, National Biometric Test Center, San
Jose State University.
• Yoon, S.W., Hsiung, C.A. and Wang, M.L. (2017) ‘Improving patient identification in
hospitals with biometric technology’, Journal of Medical Systems, 41(9), pp. 1–9.