Trends and challenges in biometrics authentication

Trends and challenges in biometrics authentication

September 20th, FY2016

Akira Kon,

General Manager, Security Research Laboratories, NEC Corporation

About NEC

4 © NEC Corporation 2016

Profile

Company Name:

Address:

Established:

Chairman of the Board:

President and CEO:

Capital:

Consolidated Net Sales:

Operations of NEC Group:

Employees:

Consolidated Subsidiaries:

NEC Corporation

7-1, Shiba 5-chome, Minato-ku, Tokyo, Japan

July 17, 1899

Nobuhiro Endo

Takashi Niino

\ 397.2 billion - As of Mar. 31, 2016 -

\ 2,821.2 billion $ 25,189 million

- Fiscal year ended Mar. 31, 2016 –

Public, Enterprise, Telecom Carrier, System Platform, Others

NEC Corporation 22,235 - As of Mar. 31, 2016 - NEC Corporation and Consolidated Subsidiaries 98,726 - As of Mar. 31, 2016 –

217 - As of Mar. 31, 2016 -

(Note: U.S. dollar amounts are translated from yen, for convenience of the reader, at the rate of \112=U.S. $1.)


NEC Worldwide: “One NEC” formation

21

North America

Latin America

Greater China

Asia- Pacific

42

Europe, Middle East, and Africa

2,821 Billion Yen in FY2015 sales

Our affiliates, offices and laboratories North America : Canada-USA Latin America : Argentina-Brazil-Chile-Colombia-Mexico-Venezuela

Europe / Middle East / Africa : Finland-France-Germany-Greece-Hungary-Italy-Netherlands-Nigeria-Portugal-Saudi Arabia-South Africa-Spain-Sweden-Switzerland-Turkey-United Kingdom Asia Pacific : Australia-India-Indonesia-Malaysia-New Zealand-Philippines-Singapore-Thailand-Vietnam Greater China

168 Business activities in over

Countries and territories

12

28

NEC Overseas Offices

43

Japan

1

Branches 237

81

1

28

115

21

2


FY2015 Sales by segment

■Public Business

■Enterprise Business

Telecom Carrier Business■

System Platform Business■

Others■

11％

26％

25％

27％

11％

Proportion of Sales（By Operating Segments）

771.6 (B\)

300.3 (B\)

697.5(B\)

728.6 (B\)

326.8 (B\)

Biometrics Applications

8 © NEC Corporation 2015 NEC Group Internal Use Only

Biometrics Applications

Security

Access control PC log on Attendance control

Criminal Investigation

Finger print matching

Convenience

Digital camera (Face detection) Mobile phone

Robot ATM/Public terminal

Car machinery Game machine

Safe

National Security

Border control National ID control

Passport Biometrics

data

ID card


Biometrics Technologies

Physical features Behavioral features

- Vein

- Voice (Speaker Recognition)

- Iris

Signature Handwriting

Typing Rhythm

Eye Blink - Fingerprint

- Face

- DNA

- Palm print

Gait - Ear canal


Comparison table of Biometrics technologies

Biometrics Feature value Cost Safety level

User acceptability

False rejection rate [%]

False acceptance rate [%]

Data size [byte]

Application

Finger print Minutia Low Mid Psychological resistance

0.5 0.001 < 1,000 Whole

Face Facial contour, shape and arrangement of eye and nose

Mid Low Easy 1 1 1,000 Gate control

Iris Radial pattern of iris

High High Effort to registration

2.8 0 256 High-level security

Voice Feature of sound

Mid Low Easy 1 0.1 1,000 Call service

Signature Handwriting

Shape of character, stroke order, pen pressure

Low Low Easy 0.2 0.6 1,000 Secure PC

Others Shape of ear, Eye blink, Typing rhythm, etc.

Research theme

JAISA: Japan Automatic Identification Systems Association


History of Biometrics Technologies

JAISA: Japan Automatic Identification Systems Association 1970 1980 1990 2000

Fingerprint recognition

Face recognition

Forensic

Gate control (i.e. immigration)

Service (EC, banking)

Iris, Palmprint, Vein, Voice

Multibiometrics

More than 40 years history of biometrics research and development produced multiple applications

R&D

Applications

Login (PC, mobile)

2010

Surveillance

2020

EAR, Gait

Mini- computer

WS/PC Network


P-12

Fingerprint Identification


Fingerprint Identification Method

Ridge

Endings

Bifurcations

Relation Minutia

e

Clear

Zone

False

Minutiae

Unclear

Zone

Minutiae and Relation Method

Features of NEC’s technology includes: ・ Extracting minutiae and relations are based on our unique algorithem. ・ From the view point of the protection of personal information, fingerprint data is not stored as

image, rather stored as digitalized data of minutiae and their relations.

Fingerprint DB

Converted into digital data

Store the digitalized information only

Picking up minutiae and extracting their relations

Relation Network

Individual fingerprint image cannot be restored. ×

Original image of fingerprint


Contactless Hybrid Finger Scanner

Product Overview

• Contactless hybrid finger scanner

consists of fingerprint and finger vein scanners

Features

• Both data are captured by one action.

• High accuracy and high availability

• Weak points of them are complemented by each other

Market

• Applicable for both fingerprint and finger vein device market

• High secured application software such as SSO and IDM

• Embedded market such as ATM and POS.

Weak points of fingerprint Presence of thin fingerprint image Not so secure against spoofing Weak points of finger vein Accuracy is lower than fingerprint Not so secure against disguising

NEC Multimodal Technology

For detailed info: http://www.nec.com/global/solutions/security/technologies/product.html

Judge

Fingerprint

Finger vein

Mixture


P-15

Face Recognition


Advantages of facial recognition over other biometrics identifications

Unconstraint

No particular action, such as placing a finger on a scanner, is needed

Faces can be automatically verified without user’s consciousness

Natural

It is natural to recognize a specific person by face, as human also use faces to

distinguish persons.

Recorded images are useful for the visual verification


Facial recognition processes

▌Step 1: Face detection

Find face in a image

▌ Step 2: Facial feature extraction

Find facial feature points within face

▌ Step 3: Face matching

Compare face features and calculate similarity


Three key technologies

▐ Face detection: based on generalized learning vector

quantization

Search square regions from edge of image to extract facial

parts

detect position of face using generalized learning vector

quantization

▐ Facial feature extraction: Multipoint feature extraction

method

Detect position of facial features, such as the pupil, subnasal

point, mouth corners, etc. from the facial parts

Search position of facial features by finding optimum position

of each feature while constraining the alignment of features

points over entire face

▐ Face matching: Multi-dimensional feature recognition

method

Extract various features from the face, such as facial contour

and tilt

Select the most appropriate feature to distinguish a person

Enable robust personal identification that is unaffected by

changes due to aging and other factors

Face

Non-face

Person B

Person C

Person A Person C


NIST FRVT2013 Results Overview

3M/Cogent(米)

Cognitec(独)

Neurotech.(リ)

Morpho(仏)

NEC

Tsinghua U.(中) Beijing Ivsign Tech.(中)

Chinese Ac. Science (中)

Toshiba(日)

Tsinghua U.(中)

HP/Virage (米)

Zhunhai-Yisheng(中)

JunYu Tech.(中)

Decatur(米) Ayonix(日)

1.0%

10.0%

100.0%

1 10 100 1000

Search processing speed (10,000 records/second) for database with 160,000 records

Err

or

rate

NEC

NEC’s face recognition technology

achieved both high accuracy (error

rate) and high speed.


P-20

Speaker Identification


What is Speaker Identification

▐ Basic Principle Every individual has different shape in its vocal organ.

It makes distinguishable vocal features from others.

Matching against recorder voice database enables the identification of

speakers.

▐ Matching Process Image

Recorded Voice DB

matching


Features of Speaker Identification

▌Easy Installation

No need of special device

Less affected by special environmental conditions

▌Easy Data Collection

Voice data can be obtained easily with less stress.

▌Easy Usage

Text/Content independent

Language independent


Solution Sample Overview


Our biometrics experience all over the world

Deployed more than 500 systems to more than 40 Countries around the world for over 30 years

Provide face recognition system for personal identification of annual theme park pass holders

Provide fingerprint identification system for the immigration control system

Provide large-scale fingerprint identification system (50 million persons) for the national ID system

Provide fingerprint identification system for personal identification in presidential election

Provide face recognition system for the immigration control system

Provide criminal fingerprint and face recognition systems in many States

U.S.

Hong Kong

Singapore

S. Africa

Bolivia

Japan

National Identification

Criminal Investigation Entertainment

Immigration Control

Trends and challenges in biometrics authentication

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