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World Class Standards

Finger Vein AuthenticationSony Finger Vein Verification Technology

for Mobile Apparatus

4th ETSI Security Workshop - Sophia-Antipolis, 13-14 January 2009

Hideo Sato

[email protected] Corporation

© ETSI 2007. All rights reserved4th ETSI Security Workshop

for Mobile Apparatus


Biometrics for Mobile Apparatus� Forge resistance

� Fake Physical Biometric ~ Iris / Fingerprint /Face� Latent fingerprint

� High accuracy / Low FTR (Failure To enrol Rate)� False Acceptance Rate (FAR) ~ Brute-force attack� False Rejection Rate (FRR)� False Rejection Rate (FRR)� Inability to enroll some users ( Fingerprint : FTR = 3~4%)

� Environmentally free� Affected by skin condition (Dry or Wet)

� Limited Resource Environments � CPU / Memory size ⇔⇔⇔⇔ Performance

� Biometric Sensor� Small size� Low cost

4th ETSI Security Workshop - Sophia-Antipolis, 13-14 January 2009 2


Forge resistance

� Fake Physical Biometric� Impact of Artificial "Gummy" Fingers*� Direct attacks using fake images in iris verification** ~ infrared camera

� Japanese banks have adopted a vein based system for verifying cardholders at the ATM.


Latent fingerprintOK!!

Gummy FingerGelatin LiquidEnhanceFake Physical Biometric

Smart Card

*** Report of Economic and Financial Developments (JAPAN)(Institute for Monetary and Economic Studies, Bank of Japan)


Finger vein / Finger Print

� Finger Vein Authentication is extremely hard to forge.� Failure to Enroll Rate(FTE) ≒≒≒≒0% (Finger Print 3~4%)� High accuracy� Environmentally free

Fingerprint Image Finger minutiae


Finger print

VEIN

OUTSIDE

INSIDEVascular Image Template

Fingerprint Image Finger minutiae


Vein Authentication for ATM / Mobile� Banking on vein at the ATM

� It is the de facto standard for biometrics ATM cards in Japan.• Hitachi 81% Fujitsu 7% (2008)

� Weak point of conventional Vein Authentication systems� Size of device >> Cellar Phone� Authentication speed < Finger print Hitachi Finger vein� Authentication speed < Finger print� Guide to fix hand or finger� High cost

� Sony Finger Vein Authentication systemThe target is Mobile Apparatus.� Size of device << 1ml� Authentication speed >> Finger print� No guide to fix finger� Low cost


Hitachi Finger vein

Fujitsu Hand vein


Comparison Chart

Diffused LightReflection

CMOS Imager

Transparent/ReflectionCCD Imager

Pressure Sensor、、、、Line Sensor etc.

Sensor

Device

Sony F. Vein

Vein

FingerPrint

Modality FAR

◎◎◎◎

◎◎◎◎

○○○○

FRR

○○○○(No Guide)

△△△△(Guide)

△△△△

TemplateData Size

◎◎◎◎

▲▲▲▲

◎◎◎◎

ResponseSpeed

▲▲▲▲

◎◎◎◎

▲▲▲▲

SensorSize

◎◎◎◎

◎◎◎◎

▲▲▲▲

Anti-Sun

○○○○

N/A

?


MIC

Line Sensor etc.

Image Sensor

Image Sensor

Image Sensor

Mouse, Tablet,Pressure Sensor

Print

Iris

FaceImage

HandShape

Voice

Sig-nature

◎◎◎◎

××××

▲▲▲▲

××××

××××

××××

××××

○○○○

××××

××××

××××

××××

◎◎◎◎

××××

××××

▲▲▲▲

▲▲▲▲

－－－－

－－－－

－－－－

▲▲▲▲

▲▲▲▲

△△△△

△△△△

××××

××××

××××

N/A

N/A

×××× or N/A


� Biometric sensor� Open Type Capability � Small sensor << 1ml� Low-cost CMOS device ( Hitachi , Fujitsu = CCD)

Sony Finger vein Technology (1)

Infra-red LED Image : Prototype Phone

CCDCCDCCDCCDSensorSensorSensorSensor

InfraInfraInfraInfra----Red Red Red Red LEDLEDLEDLED

HitachiTransparent Type


Infra-red LED Unit

Flap Type Phone

Sensor Module

Image : Prototype Phone

Finger Position DiffusionDiffusionDiffusionDiffusion

LightLightLightLight

InfraInfraInfraInfra----Red Red Red Red LEDLEDLEDLED

CMOS CMOS CMOS CMOS SensorSensorSensorSensor

Vein

Finger

Transparent Type

SonyOpen Type



� Feature Extraction Algorithm for Vein Blood Flow� Detecting from Low Contrast Image/Noise Removal

• Possible to use the general CMOS Image sensor

� Detecting the Center Line of the Vein • Robust for the variation of the climate and the health condition


Vein Image

Feature Extraction

Skelton Pattern

CMOSSensor



� New compact-fast-matching algorithm� Quick Response ：：：： 250ms ( Mobile Phone @ARM9 150MHz )� High Accuracy ：：：： FAR 0.0001% FRR 0.1%� No Guide to set the finger position

No Finger


.Finger Aligned axis Rotation

Rotation/ZoomingRejection

X-Y MovingRejection

CMOS Sensor

Vein PatternMatching

Feature SpaceMatching

Finger

2D CombinationalMatching / Decision

Mapping to FeatureSpace

Templates

No FingerGuides



� Vein Pattern Data Compression with keeping the accuracy� Transform from Vein Pattern to Geometric Information� Compression as Geometric Information Base

with Accuracy Compensation to 112Byte• Suit for Smart card storing• Quick Response

LSI

Template size112Byte/Pattern

Smart card• Quick Response


ExtensionTransformation

Vein Pattern

Compression

GeometricInformation

CompressedInformation

ExtendedVein Pattern

Smart card


� These technologies enable the use of finger vein authentication for mobile devices and smart cards, etc.

Conclusion : Sony Finger vein Authentication

2. Quick Response

1. High Accuracy - Better than Fingerprint based

- Less than 250ms （@ Mobile Phone)Reducing Retry Times

4th ETSI Security Workshop - Sophia-Antipolis, 13-14 January 2009 114th ETSI Security Workshop - Sophia-Antipolis, 13-14 January 2009

5. Small Data Template

4. Using Environment

3. Small Size

2. Quick Response Reducing Retry Times- No Guide to set the finger position

- Smaller than 1ml.

- Possible to verify under the Sun Light

- Suitable Size for storing into Smart card :Less than 128byte


ISO-standard and others

� ISO/IEC� Biometric data interchange formats -- Part 9: Vascular image data

(ISO/IEC 19794-9)� Conformance testing methodology for biometric data interchange

formats -- Part 9: Vascular image data(ISO/IEC 29109-9)


(ISO/IEC 29109-9)

� JIS(JP)� Evaluation Method for Accuracy of Vein Authentication Systems

(JIS-TR X0079)


Thank you for your attention

4th ETSI Security Workshop - Sophia-Antipolis, 13-14 January 2009

4th ETSI Security Workshop


References� Impact of Artificial "Gummy" Fingers on Fingerprint Systems

Tsutomu Matsumoto , Hiroyuki Matsumoto , Koji Yamada , Satoshi Hoshino� http://www.lfca.net/Fingerprint-System-Security-Issues.pdf

� Direct attacks using fake images in iris verification ( BIOID 2008 )Virginia Ruiz-Albacete, Pedro Tome-Gonzalez, Fernando Alonso-Fernandez,Javier Galbally, Julian Fierrez, and Javier Ortega-Garcia� http://cost2101.org/BIOID2008/papers/19_BIOID_paper25.pdf� http://cost2101.org/BIOID2008/papers/19_BIOID_paper25.pdf

� A Case Study for User Identification ( ITU-T Workshop )Tsutomu Matsumoto� http://web.mit.edu/6.857/OldStuff/Fall03/ref/gummy-slides.pdf

� UK Identity Cards and Social Exclusion ( Privacy International )� http://www.privacyinternational.org/article.shtml?cmd%5B347%5D=x-347-228833

• 30/05/2005


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