Lecture about biometrics in one hour.

utterlypanoramicSecurity

Nov 30, 2013 (3 years and 11 months ago)

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Biometrics

Viktor MINKIN

minkin@elsys.ru



Outline

Outline

Introduction

Biometric systems

Biometric characteristics

Fingerprints

Unimodal systems

Multi
-
modal systems

Problems

Links

History and future



Introduction


Biometrics [harmonized]



Automated recognition of persons based on

their biological or/and behavioral characteristics.


Automated measurement of biological or/and

behavioral characteristics of person for medical,

security or psychological purposes.



Introduction

Terms and definitions



Template



Capture



Comparison



Database



Enrollment



Matching



Token



User



Introduction

Identification of a person



Verification/Verify


Comparing one to one


“Am I who I claim I am”



Identification


Comparing one to many


“Who am I”




Introduction

Application




Passport control


Access to secured areas


Surveillance


ATMs


Computer logins


E
-
commerce


Medicine


Psychology



Introduction

Traditional means of automatic identification


(before biometrics)



Knowledge
-
based


Use “something that you know”


Examples: password, PIN



Token
-
based


Use “something that you have”


Examples: credit card, smart card, keys




Introduction

Problems with traditional approaches


Token may be lost, stolen or forgotten


PIN may be forgotten or guessed by the imposters


(25% of people seem to write their PIN on their ATM
card)

Estimates of annual identity fraud damages
per year:


$1 billion in welfare disbursements


$1 billion in credit card transactions


$1 billion in fraudulent cellular phone use


$3 billion in ATM withdrawals



Introduction


The traditional approaches are unable to differentiate

between an authorized person and an imposter



Use biometrics which relies on “who you are” or


“what you do”




Biometric Systems

Requirements for an ideal biometric



Universality


Each person should have the characteristic



Uniqueness


No two persons should be the same in terms of the
characteristic



Permanence


The characteristic should not change



Biometric Systems

Issues in a real biometric system



Performance


Identification accuracy, speed, robustness, resource
requirements



Acceptability


Extend to which people are willing to accept a particular
biometric identifier



Faked protection


How easy is it to fool the system by fraudulent methods



Biometric Systems


Identification accuracy



FAR = false acceptance rate


FRR = false rejection rate


EER = equal error rate


TER = total error rate = FAR + FRR


FER= false enrollment rate




Biometric Systems


Receiver operating characteristics (ROC)

False Rejection Rate

False Acceptance Rate

Equal Error Rate



Biometric Systems

FAR/FRR and comparison threshold



Biometric Characteristics

Static (biological) parameters

Fingerprints


Face

Iris

Hand geometry / vein

Retinal pattern

Facial thermogram

Lip information

DNA



Biometric Characteristics

Dynamic (behavior) biometric parameters


Signature

Voice

Motion

Pulse



Biometric Characteristics

Market Shares



Biometric Characteristics

Market development



Fingerprints

Accurate

Comparatively cheap hardware

Questionable acceptance



Fingerprints

Optical technology

Light reflects from the surface of the prism where the finger is not
in contact with it, while it penetrates the surface of the prism
where the finger touches the surface of the prism. The resulting
image goes through a lens into a video camera.

Light
source

Finger

Video Camera (
CCD)

Lens

Prism



Fingerprints

Capacity technology



Fingerprints

Fiber optic technology



Fingerprints

Fingerprint types

Arches Loops Whorl

Bridge

Dot Ridge Ending Bifurcation Enclosure

Minutia types




Fingerprints

Core & Deltas



Fingerprints

Fingerprint minutiae



Fingerprints

Image transformation


Source FFT Flow field Directional Directional Directional


image 1 image 2 irregularit
y

Code


Smoothing Binarization Skeleton Skeleton Minutiae


formation cleaning search



Fingerprints

Comparative testing



Fingerprints

Fingerprint information



Unimodal Systems

Facial ID

Illumination

Head pose

Occlusion



Unimodal Systems

Hand Vein

Questionable accuracy

Hand geometry



Unimodal Systems

Retinal Pattern

Highest accuracy

Even more intrusive than iris recognition



Unimodal Systems

Facial Thermo image and VibraImage


Non
-
intrusive Lie detection


View
-
dependent Emotion control


Depends heavily on Criminals detector


human factors, Medical monitoring


body temperature Psychology testing



Multi
-
modal Systems

Why
multimodal

[multiple] person
identification?


Quest for non
-
intrusive identification methods


No special purpose hardware needed


Works potentially at greater distances


“Traditional” arguments for going multimodal:


Increasing performance


Increasing robustness


Mono
-
modal recognition techniques are likely to
reach in a close future a saturation in
performance.









Multi
-
modal Systems: Fusion

“Early integration” or “sensor fusion”

Integration is performed on the feature level

Classification is done on the combined feature vector

Features

Modality 1

Classifier

Features

Modality 2

Features

Modality n
-
1

Features

Modality n

Identity



Multi
-
modal Systems

BioFinger

3
-
Elsys
includes


BiCard,


VibraImage,

3D
-
Elsys is biological and behavioral identification system




Multi
-
modal Systems

The World population in 2000 was about

6.000 M. people.


The biometric document (ID card) market is

more than $6.000.000.000


There are 3 different ID card technologies:


1. Card with additional memory (chip, CD,..)


2. Card with 2d
-
bar code


3. BiCard (3D
-
Elsys)



Problems


Errors rate


Misunderstanding of real advantages and
problems


Incomplete true about biometric systems



Links

International Biometric Group


-

http://www.biometricgroup.com


NIST


-

http://www.itl.nist.gov/div893/biometrics/


Literature


http://www.itl.nist.gov/iaui/894.03/pubs.html#fing


Patents



-

http://www.elsys.ru/patents.php



Biometrics evolution


19 century
-

not automated identification


20 century
-

biometric identification


21 century
-

emotion recognition and detection



Viktor Minkin



Biometrics



minkin@elsys.ru


Thank you!

2004