Jain2013-The Solved the Unsolved and the Unexplored 50 Years of Biometric Research 50 Years of...

8/12/2019 Jain2013-The Solved the Unsolved and the Unexplored 50 Years of Biometric Research 50 Years of Biometrics Research

1/58

50YearsofBiometricResearch:Almost

The Solved,The

Unsolved,

and

The

Unexplored

MichiganStateUniversity

June5,2013

1

KeynoteTalkDeliveredattheInternationalConf.onBiometrics,Madrid,Spain,June5,2013


2/58

50YearsofBiometricsResearch Fingerprint

M.Trauring,OntheAutomaticComparisonofFingerRidgePatterns,

Nature,vol.197,pp.938940,1963 o ce

S.Pruzansky,

Pattern

Matching

Procedure

for

Automatic

Talker

Recognition, J.AcousticSocietyofAmerica,vol.35,pp.354358,1963 W.W.Bledsoe,ManMachineFacialRecognition,Tech.Report

PRI

22,

Panoramic

Res.

Inc.,

1966 . ,

RecognitionofHumanFaces,DoctoralDissertation,KyotoUniversity,1973

Handgeometry

R.H.Ernst,HandIDSystem,USPatentNo.3576537,1971 Iris

L.Flom andA.Safir,IrisRecognitionSystem,USPatent4641349A,1987 J.G.Daugman,HighConfidenceVisualRecognitionofPersonsbyaTestof

StatisticalIndependence,IEEETrans.PAMI,vol.15,pp.11481160,19931960s:BeginningsofresearchinAI,patternrecognition&imageprocessing2


3/58

IdentificationforDevelopment:TheBiometricsRevolution

identificationprogramsintheLowMiddleIncomeCountries

*IdentificationforDevelopment:TheBiometricsRevolution,A.GelbandJ.Clark,CenterforGlobalDevelopment,NW,Washington

DC,WorkingPaper315,Jan.2013,http://www.cgdev.org/sites/default/files/1426862_file_Biometric_ID_for_Development.pdf

3


4/58

Objectives&Outline

Whatis

biometrics?

ow ometr csgetstarte

Whereare

we

now?

Wheredowegofromhere?

4


5/58

TheBiometricsConundrum

Demographics Credentials

Sensordata

Transaction Authentication

Privilege

User

Matchscore

Confidence

Recognizeaperson

by

body

traits

&

link

the

body

to

an

externally

assigned

identity

5


6/58

BiometricChallenge

Findarepresentation&similarity measuresuchthat

Intrasubject

similarity

is

very

high

Probe Gallery

6Similarityscore>Timpliesamatch


7/58

WhyBiometrics?

Security:Doesthepersonhaveapriorcriminalrecord?

Convenience:

Noneed

to

carry

credentials

(pw,

ID)

Fraud:

Is

the

credit

card

holder

the

rightful

owner? Deduplication:Oneperson,onedocument!

Palmvein

scanners

used

for

patient

registration

in

Houston

hospital

system;

2,488

patientsarenamedMariaGarciaand231ofthemhavethesamebirthdate

7http://www.usatoday.com/story/news/nation/2012/11/25/palmscannerstechnologyschools/1726175/


8/58

IndiasAadhaar Project

Basic demo ra hic data and biometrics

Name

Parents

Gender

1568 3647 4958

stored centrally

UID = 1568 3647 4958

DoB

PoB

Address

ngerpr n s, r ses ace mage

Central UID database

To ivethe ooranidentit

~350 million unique ID numbers have already been issued

https://portal.uidai.gov.in/uidwebportal/dashboard.do 8


9/58

PersonalizationApplications

Transactions

Healthcare

Veri ication

ConvenienceTravelSafety

9


10/58

10


11/58

HabitualCriminalAct(1869)

What is wanted is a means of

classifying the records of habitual

criminal, such that as soon as the

p r i s o n e r ( w h e t h e r

descri tion, measurements, marks, or photographs) are received, it may

be possible to ascertain readily, and

w t certa nty, w et er s case s nthe register, and if so, who he is. HabitualCriminalsReturnsBook

G.Pavlich,TheEmergenceofHabitualCriminalsin19thCenturyBritain:Implicationsfor

Criminology,Journal

of

Theoretical

and

Philosophical

Criminology,

2(1),

pp.

159,

2010 11


12/58

BertillonSystem(1882)

H.T.F.Rhodes,AlphonseBertillon:FatherofScientificDetection,Harrap,195612

Firstuseofsoftbiometricsandmultibiometrics


13/58

FrictionRidgePatternFrictionRidgePattern

Perhaps the most beautiful and

characteristic of all superficial marks

with the intervening ridges and theirpores that are disposed in a singularly

com lex et even order on the under

surfaces of the hands and feet., , ,


14/58

ThreeMostPopularBiometricTraits

Legacydatabase Legacydatabase 1:Nsearch

1:Nsearch

NISTevaluationCovert

capture

NISTevaluationHigh

accuracy

NISTevaluation


15/58

FingerprintRecognitionMilestones

1880

HenryFaulds

Articleonfingerprints

ublishedinNature

1963

MitchellTrauring

Firstpaperonautomatic

fin er rintmatchin

2004

DHS

USVISIT

2009

UIDAI

Indiastartedissuing

12di itUIDno.to

1901

ScotlandYard

AdoptedGalton/Henrysystemof

classification

AD600

China

1893

Argentina

1924

FBI

itsresidents

2008

FBI

1970s

FBI

contracts andlegal

documents

asforensicevidence

identificationdivision

~10002000B.C. 1892 1990s 20051997

AncientBabylon

Fingermarkonclayseal

JuanVucetich

Rolledinkonpaper

Livescantechnique

Opticalsensor

Solidstatesensor

Ultrasoundsensor

TBS

Touchless 3Dsensor

ThomsonCSF

Swipesensor

~1995

2003

USVISIT

http://www.alaskafingerprinting.com/Fingerprinting.html

http://commons.wikimedia.org/wiki/File:USVISIT_(CBP).jpg

http://www.biometricdirect.net/upekeikontouchfingerprintreadereikontouch700.html

http://www.thehindu.com/news/national/uidaitostartinformingaadharnumbersthroughemailssmses/article2624078.ece

http://www.idex.no/technology/swipesensor/

http://www.techneology.org/2009/10/touchless3dfingerprinting.html 15

SiemensIDmouse


16/58

FaceRecognitionMilestones

1991

Turk & Pentland

1964

Woodrow Bledsoe

1973

Takeo Kanade

2001

Viola & Jones

2006 20091997

Belhumeur et

1999

Blanz & Vetter

Eigenface

Facerecognition

FirstFRthesis Facedetector

al.

LBP

.

Sparserep.

al.

Fisherface

Morphable face

191535mmstillcamera

1991Kodak

Digitalcamera

1024p

2000Sharp

Firstcameraphone

320p

20102013

Wearablecamera

480P@30fps

GoogleGlass

April2013

SamsungGalaxyS4

1080p@30fps

1990sSurveillancecamera

480p@30fps

Bledsoe,W.W.1964.TheModelMethodinFacialRecognition,TRPRI15,PanoramicResearch,Inc.,California. http://photodoto.com/camerahistorytimeline/

M.Turk

and

A.

Pentland, Eigenfaces for

recognition.

Journal

of

Cognitive

Neuroscience

3(1):

7186,

1991.

TakeoKanade,PictureProcessingSystembyComputerComplexandRecognitionofHumanFaces,KyotoUniv.,1973.Viola,Jones:RobustRealtimeObjectDetection,IJCV2001.

Ahonen,et al.Face

Description

with

Local

Binary

Patterns:

Application

to

Face

Recognition,

PAMI,2006.

J.Wrightetal. RobustFaceRecognitionviaSparseRepresentation,PAMI,312,2009.

http://static7.businessinsider.com/image/4d013ea7cadcbb7033010000/looxcievideocamera.jpg

http://www.techinasia.com/samsunggalaxys4infographic/

720p@30fps

Belhumeur,P.N.etal.,Eigenfaces vs.Fisherfaces:recognitionusingclassspecificlinearprojection,PAMI,197,1997.

V.Blanz andT.Vetter,Amorphable modelforthesynthesisof3Dfaces,SIGGRAPH1999.

http://commons.wikimedia.org/wiki/File:Three_Surveillance_cameras.jpg


17/58

IrisRecognitionMilestones2002

USA

Useofirisrecognition

infieldoperations

2009

UIDAI

NationalID

2010

Mexico

NationalID

2011

Indonesia

NationalID

1936

FrankBurch

Conceptofusingiris

patternsforhuman

1985

Flom andSafir

1991

JohnDaugman

2001

UAE

2005

Flom andSafir

2011

JohnDaugman

Firstirisrecognition

patent

Irisrecognition

patent

1995

Deployedirisrecognition

systemforbordercontrol

Patentexpired Patentexpired

1989 20062004 2013 2013

IrisScanner System

Oneoftheearliest

commercialiriscameras

JohnDaugman

Firstiriscamera

Sarnoff

IrisontheMove

SecuriMetrics

Portableirisrecognition

device

AOptix

App&device

forsmartphone

tocaptureiris

DeltaEye

https://www.fbo.gov/index?s=opportunity&mode=form&tab=core&id=1d31acd78d7a20b1fe598bf4b4661d6bhttp://www.sri.com/engage/productssolutions/iompassportportalsystem

http://www.cnn.com/2013/04/16/tech/mobile/mashablebiometriciphonescanner

17


18/58

OtherBiometric

Traits

18


19/58

TraitswithLegacyDatabase

Traceevidence

Innocenceproject

RealtimeDNAmatching

~30%of

latents are

of

palmprints

FBIsNGIwill havelatentpalmprint

matchin ca abilit

Capabilityto

conduct

1:N

search 19


20/58

TraitsinCommercialSystems

Primarilyfor

1:1

match 20


21/58

TraitsinLaboratoryStage

21


22/58

WhichBiometric

Trait?

22


23/58

RequirementsofaBiometricTrait

Uniqueness(Isitdistinctiveacrossusers?)

Universality(Doeseveryuserhaveit?)

Collectability(Canitbemeasuredquantitatively?)

Userexperience(Isitacceptabletotheusers?)

Vulnerability(Can

it

be

easily

spoofed?)

Inte ration(Canitbeembeddedinthea lication?)

23Nobiometric

trait

is

optimal,

but

many

are

admissible


24/58

RejectedBiometricTraits

24


25/58

25


26/58

FingerprintMatching

Plaintoplainmatching . .

Latentto

rolled

matching

.

OnNISTSD27,stateoftheartrank1accuracy:~72%

C.Wilson

etal.,FingerprintVendorTechnologyEvaluation2003:SummaryofResultsandAnalysisReport,NISTIR7123,2004

M.Indovinaetal.,EvaluationofLatentFingerprintTechnologies:ExtendedFeatureSets[Evaluation#2],NISTIR7859,2012Matchingspeed:~millions/secfortenprint matchingonasingleserver

26


27/58


28/58

IrisRecognition

Irisimages

collected

from

4.3

million

eyes

(6.1

M

images)

Overthe95algorithmsevaluated,singleeyeirisfalse

negativeidentification rates(i.e.missrates)areat1.5%or

higher.Fortwoeyes,FNR=0.7%

No.offalsepositivesis25outofatotalof1013 comparisons

Pupildilation

& constriction

canimpact

iris

recognition

Templatesizevaries between1KBand20KB

http://www.nist.gov/itl/iad/ig/irexiii.cfm28


29/58

SpeakerRecognition

Givenatargetspeakerandatestspeechsegment,isthe

Atrial

consists

of:

Target

Speaker

ID

+Test

segment

NIST SRE12

Systems

tested 75 90

95

100

TestSegmentDuration 30300s

Number ofTrials ~2million 80

85TAR

(%)

KnownNon

Target

UnknownNonTarget

,

46,601

61,87170

1 2 30.01% 0.1% 1%

C.Greenberg

etal.,The2012NISTSpeakerRecognitionEvaluation,NISTSRE12,December11122012,Orlando,Florida

http://www.nist.gov/itl/iad/mig/sre12results.cfm 29


30/58


31/58

UnsolvedProblems

Fundamental roblems

Uniqueness(individuality)

Applicationdrivenproblems

Systemsecurity&userprivacy

Antispoofing

31


32/58

Uniqueness

Givena10digitPIN,no.ofuniqueidentities

thatcanberesolved=10billion

But,what

can

we

say

about

abiometric

trait?

Bodytraitvs.sensedimage

No.ofmonozygotictwinbirthrateisaboutthreeinevery1,000birthsworldwide 32


33/58

Persistence

Humanbody(hencebiometrictraits)willageovertime

Score=0.84 Score=0.76 Score=0.71 Score=0.58COTS

A

COTSB

33ImagesfromPCSOmugshot database;CourtesyScottMcCallum

h


34/58

CamerasEverywhere

1M CCTV cameras in London & 4M in U.K.; average Briton is seen by 300 cameras/day;400K cameras in Beijing provide 100% coverage of public places; 150K cameras in Seoul34


35/58


36/58

36


37/58

TopRetrievalRanks forTsarnaev Brothers

37

Bi t i S t V l biliti


38/58

BiometricSystemVulnerabilities

Insider Attacks

Enrollment FraudCollusion

Enrollment

Exception Abuse

FeatureExtraction

Verification

StoredTemplates

HillClimbing, Re

play &Man-in-the-

Middle

Spoofing &Obfuscation

Attacks

TrojanHorseAttack

TrojanHorseAttack

TemplateAttacks

Attacks

External Adversary Attacks

FakeIris Altered

Fingerprints Minutiae Reconstructed

Fingerprint

Biometric Template Protection


39/58

BiometricTemplateProtectionApplication A

FeatureExtraction

EnrollmentStoredTemplates

TemplateProtection

Matcher

Verification

Non-linkableNon-invertible

X

Application B

by preventing

cross-matching)

by preventing intrusion attacks)

StoredTemplates

Can we generate a non-invertible AND non-linkable biometric template

without compromising the matching accuracy?

Bi i K G i


40/58

BiometricKeyGeneration

Courtesy: Prof. Tyfun Agkul, Istanbul Technical University 40


41/58

Circumvention

Face Liveness


42/58

FaceLiveness

42


43/58

WhereisBiometricsGoin ?

Processor,memor &sensors

Ubiquitousbiometrics

Context

Privacy

Biometricsforsocietalgood

ersona za onBiometrics&forensics

43

Processor Memory and Sensing Technology


44/58

Processor,MemoryandSensingTechnology

Microprocessorperformancevs.cost RAMcapacityvs.cost

1892Inkandpaper

1990sOpticalsensor

1990sCapacitivesensor

1997First swipesensor

2007US

VISIT

Slapsensor2010

SAFRAN

Touchless swipesensor


45/58

Ubi uitousBiometrics

Biometrics will become more

holistic, where location, behavior and

recent interaction history fuse with

multimodal biometric ID (strong and

weak traits) to provide a strongassurance of identity. This degree of

inte ration is both inevitable and

necessary for ubiquitous biometrics.

CourtesyRob

Rowe,

Lumidigm 45


46/58

46

Google Glasses


47/58

GoogleGlasses

47

Privacy


48/58

Privacy

Cafes ban Google

glasses to protect'

Fears users of futuristic

eyewear can recordwithout permission.

http://www.dailymail.co.uk/sciencetech/article

2323578/CafesbanGoogleglassesprotectcustomers

privacyFearsusersfuturisticeyewearrecord

permission.html#ixzz2UgEfuN8F

48

Your Digital Footprint Defines You


49/58

YourDigitalFootprintDefinesYou

Browsing HistoryBookmarksPreferences

Your FavoriteWeb Services

Your Family& Friends

e-Transactions

Online Interaction Patterns++

W atyou do?

Home & Office Mobile

Whereyou are?

Whatyou are?

WHO YOU ARE

GPS Fingerprint:


50/58

GPSFingerprint:

Withjusttheanonymouslocationdata,onecanfigureoutwhoyouareby

trackingyoursmartphone.Patternsofourmovements,whentracedona

DeMontjoye,

Hidalgo,

Verleysen &

Blondel,

Unique

in

the

Crowd:

The

Privacy

Bounds

of

Human

Mobility,

Scientific

Reports,

vol.

3,

2013

map,createsomethingakintoafingerprint,uniquetoeveryperson.

50

AffectiveBiometrics


51/58

CourtesyProf.Tayfun Akgul,ITU

Cell Phone Science


52/58

CellPhoneScience(By

Bill

Gates,

Nov

09,

2010)

Most of us think of cell phones primarily as

a convenient tool to stay in touch with

people and store information. But

increasingly, scientists are exploring ways to

use cell phones to deliver critical health care

to people in developing countries.

Over1.7billionmobilephonesweresoldworldwidein2012alone

http://www.gartner.com/newsroom/id/2335616

http://www.thegatesnotes.com/Topics/Health/CellPhone

Science 52

b l h b d


53/58

MobilePhonebasedVaccinationRegistry

16monthsoldboy,rightringfinger

.

redundantdosesandincreasecoveragelevelsindevelopingcountries(MarkThomas,VaxTrak)

53http://vaxtrac.com/about

Locards Exchange Principle


54/58

Locard s ExchangePrinciple

Edmond Locard (18771966), a pioneer in forensic

science, stated that the perpetrator of a crime will bring

something into the crime scene and leave with something from

it, and that both can be used as forensic evidence.

.. Not only his fingerprints or his footprints, but his hair, thefibers from his clothes, the glass he breaks, the tool mark heeaves, e pa n e scra c es, e oo or semen e epos s

or collects. All of these and more, bear mute witness againsthim. This is evidence that does not forget. ..Only humana ure o n , s u y an un ers an , can m n s s

value.

PaulKirk,Crimeinvestigation: physicalevidenceandthepolicelaboratory.Interscience Publishers,NY1953

http://en.wikipedia.org/wiki/Locard%27s_exchange_principle 54

A Brief History of DNA Testing


55/58

ABriefHistoryofDNATesting

BeforeDNA: PCR,STRsandtheOnset Mitochondrial Rapid

Testsresults

in


56/58

Summary&Conclusions

BiometricsRecognitionisheretostay

Researchvs.Technology

Driversforacademicresearchers:

Errorrates(butwhatsthebaseline?),new

Driversfortechnologyproviders:

Requ rements error

rates,

temp ate

size,processor,throughput),seamless, ,

56

My Observations


57/58

MyObservations

1. BiometricSystem:Almostalwaysembeddedinanapplication

. ome r c ra : oop ma one, u someare e er ano ers

3. MatcherAccuracy:

Zero

error

is

neither

required

nor

guaranteed

.

5. Baseline:Improperbaselineprovidesfalsesenseofprogress

.

7. BiometricTemplate:Featureextractionisnotaonewayfunction

.

9. MatchScore:Gaussiandensityisnotadvisable.Tailsarecritical

.

57

Acknowledgement


58/58

58

Jain2013-The Solved the Unsolved and the Unexplored 50 Years of Biometric Research 50 Years of...

Documents

Transcript of Jain2013-The Solved the Unsolved and the Unexplored 50 Years of Biometric Research 50 Years of...