© 2014 IBM Corporation1

Biometrics As an Enabling Technology – Identity Assertion

Entitlement(s)

Actions

Identity

Trust

(Rules)

Status

(Environment)

Reputation

(History)

Manage

Identity

Establish Identity

© 2014 IBM Corporation2

� Data Explosion – more sensors, proliferation of data collection

� Cloud Technology – more mature

� Computer Resources – a commodity

• Big Appliances – commodity platforms and services

• Network, platform, application services become commodity – same for biometrics

� Analytics Tools – readily available

� Open Source – simply proliferated

� Standard Adoption – NIST-ITL, INCITS and many others

� Low Government Funding – mega programs (NGI, US-VISIT, UUID) don’t come often, S&T fund reducing

Different Perspective – Emerging Trends

© 2014 IBM Corporation3

A Need – Establish Identity Service in the Cloud

� Focus on Identity Assertion

• Biometrics as an enabling technology

• Avoid a race for accuracy

• Business owners have limited resources for better sensors, more data and etc.

• Business owners still want the same performance with a smaller budget

� Driven by Economics and Technology Trends

• Proliferation of data collection and mobility

• Success or advancement of Big Data infrastructureand platform technologies

• Advancement of IT industry and commoditization

• Leverage all data sources available and within the “vicinity”

� Areas of Challenges

• Security, privacy, and protection for cloud based identity information

• Secure biometrics data

• Techniques to address privacy

• Contextual information fusion through context accumulation

• Research spatial & temporal impact

• Bringing identity resolution technologies into the mix

• Other information including biographic

© 2014 IBM Corporation4

A Challenge – Working with Low Quality Data

“A fact of life”

• Low Resolution Data

• Out of Focus Image

• Unconstrained Capture

• Insufficient Color/Grayscale Information

• Limited Data Samples

• Many more

© 2014 IBM Corporation5

Dr. Charles Li Technology and StrategyIBM Federal CTO GroupCharles_li@us.ibm.com202 330 109

© 2014 IBM Corporation6

Perceptions on biometrics

technology and system

What is missing?

© 2014 IBM Corporation7

Biometrics Data at Scale – Static & Single Instance

1 Billion Arrivals 2012 world wide United States – 100-200 million international arrivals 2012

1 Exabytes traveling data

Unique Identification Authority of India (UIDAI) plans to enroll 1.2 billion citizens.(UID Program) ( enroll million /day; half billion by

2014) 3-4 Exabytes Biometrics &

Biographic Data

Prolific Usage of Mobile Phones 6 Billion Mobile Phones

6 Exabytes of behavior data

ID Cards/Border Crossings/Benefits/Multiple

Instances

7,000,000,000x(10 Print 0.5-1MB + Face 200KB +

IRIS KB)

7 Exabytes

EU VIS Biometrics Matching System (BMS) at

70 million individuals and 100K daily enrollment

~100 Terabyte

US DoS has in the range of 100 million faces & Others~ at least 10-50 Terabytes

DHS IDENT over 150 million identities; 125,000 transactions daily

~100-300 Terabytes

FBI NGI ~ over100 Million Fingerprints & More coming plus Faces/Iris

~100-200 Terabytes

1 GigaBytes = 1000MB

1 TeraBytes = 1000GB

1 PetaBytes = 1000TB

1 ExaByes = 1000PB

1 ZettaBytes = 1000EB

1 YottaBytes = 1000ZB

many instances, history, transaction, logs… data in reality

© 2014 IBM Corporation8

Other Big data examples

150 Exabytes global size of “Big Data” in Healthcare, growing between 1.2 and 2.4 EX / year

For every session, NY Stock

Exchange captures 1 Terabyte of trade information

AT&T transfers about

30 Petabytes of data through its network daily

Hadron Collider at CERN

generates 40 Terabytes of usable data / day

Facebook processes

500+ Terabytes of data daily

Google processes

> 24 Petabytes of data in a single day

Twitter processes

12 Terabytes of data daily

By 2016, annual Internet traffic

will reach 1.3 Zettabytes

We don’t have the most challenging problem!

© 2013 IBM Corporation

Biometrics Identity Service Cloud Model

Operational Cloud

Biometrics as a ServiceAdjust resources based on load

Facial

BiometricsData Sources

Elastic Compute Resources

…Finger print

Biometric and

Identity Services

Develop/Test Cloud

Test Bed

Test Data

Compute Resources

Data

Service and

algorithm Dev/Test

Mobile clients

Field Operation

User

User

User

User

Application/Integration Services

Data in Motion –

Streaming Pattern

Web 2.0

Pattern

J2EE/OLTP

Patterns

Map/Reduce

Pattern

MobileDesktop,InteroperateAnalyst – Human Examiner

• Cloud – Data, Compute, Network• Options – On-premise, Off-

Premise, Hybrid

• Enroll, Identity, Identity, Retrieve,• Subject Manipulation(create, delete,

update, retrieve),

• Biometrics and Biographic manipulation

Biometrics Identity Cloud Services

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