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© Daon Confidential Strategies for Implementing National Identity Systems Nov 28 th 2007 Leo Ring Vice President, Daon
© Daon Confidential Daon – Company Profile Global provider of identity related software products –Founded in 2000 –We work with customers and partners in every region of the world –Offices in Washington DC (HQ), Dublin, London, Dubai and Canberra (Australia) We create software products that Enable a new generation of Biometric Identity Solutions –Flexible products, intended for integration –Focus on large-scale population-centric® environments –Focus on identity life-cycle –Open and multi-modal –Focus on modernization
© Daon Confidential Pre-Enrollment Provide biographic information Pay fees Receive instructions Capture Biographics Enter biographic data or Verify/correct pre-enrollment data Identity Proofing Scan identity documents Validate documents Identity Investigation Biometric duplicate checks Vetting Complete Prepare Card Data Generate templates Sign card data Card Issuance Produce Card Provide to Citizen Operational Usage Citizen presents card and biometric Capture Biometrics Capture ten fingerprints Capture iris (optional) Capture face (optional) Identity Investigation Criminal history checks Name based checks National Identity Systems
© Daon Confidential National Security – Traditional Approach – Separate Identity Systems Add Identity / Biometrics Passport Identity / Biometrics Citizen IDForeign ID Identity / Biometrics Separate Systems Passport Citizen ID Foreign ID Existing Systems
© Daon Confidential Identity Management System New Approach - Unified Identity Management IntegratedBiometricServices Refugees / Asylum Border Management Visas / Permits Foreign ID Citizen ID Passport IdentityDatabase
© Daon Confidential Biometric Identity Assurance Requirements are Evolving Authentication/Identification Identity Assurance One project at a time An infrastructure for multiple systems Engineering/Technology Led Business Process and Change Mgt Led Client-Server based Service-Oriented Architectures Fingerprint-centric Multi-Biometric Single Vendor COTS based, Multi-Vendor Framework Compliance Compliance plus Adaptability Biometric matching performance Enterprise Systems Performance Proprietary Standards-based with interoperability From To Disparate Federated
© Daon Confidential Copywrite Daon 2006 National ID Business Challenges The failure to prevent duplicate identities results in significant financial loss and questions regarding a national identity schemes integrity Biographic only duplicate checking algorithms have failed In may countries - the current issuing processes may have created a large number of duplicate identities –Identity duplication and identity creation increase the levels of fraud, waste and abuse In many cases enrolment is an offline process taking multiple days before card issuance
© Daon Confidential All Biometrics Have Limitations BiometricFARFRRFTE Face1.00%1%0.1% 0.10%2%0.1% 1-Finger1.00%0.01%2.5% 0.01%0.6%2.5% 2-Finger1.00%0.01%1.5% 0.01%0.1%1.5% 4-Finger0.10%0.01%0.8% 0.01%<0.01%0.8% 8-Finger0.10%<0.01%0.3% 0.01% 0.3% 10-Finger0.10%<0.01%0.2% <0.01%0.01%0.2% 1-Iris0.10%1.2%2.5% 0.01%1.5%2.5% 0.001%1.9%2.5% %2.0%2.5% 2-Iris0.10%0.5%4% 0.01%0.6%4% 0.001%0.8%2.5% %1.2%2.5% Iris has a high Failure-to-Enroll rate up to 2.25 Million in 45 Million population but extremely low False Accept rate Fingerprints achieve good accuracy and efficient processing only when multiple fingers are enrolled Face has a high False-Rejection rate FAR = False Accept Rate FRR = False Reject Rate FTE = Failure To Enroll
© Daon Confidential False Matches During Duplicate Checks Require Additional Processing FAR50 Million 100 Million 5%2.5M5M 2.5%1.25M2.5M 1%500,0001M 0.1%50,000100, %5,00010, %5001, %50100 Two ways to reduce these false hit rates are: Manually Automatically using a second biometric Number of False Hits Per Search High false accept rate could lead to 2.5M false hits when searching a population of 50M for duplicates.
© Daon Confidential Copywrite Daon 2006 Representative ways to address large scale National ID challenges Introduction of Multiple Modes of Biometrics Algorithms that best address most difficult challenge for this population and application –Even within a mode like fingerprints certain algorithms perform better with certain population types –Accuracy/performance tuned to population Population filtering to reduce effective biometric population Continual technology refresh: incorporating latest algorithms, devices, IT hardware and new products Continual and automatic updating of enrolled biometric data
© Daon Confidential Algorithm Accuracy/Performance tuned to population Different demographics produce different accuracies Age, ethnic origin, gender, etc. 51 to 65 year-olds significantly worse with this device-algorithm Age is a disadvantage here Opposite is true for face biometrics; an older face is more unique Configuration must be made based on observed population Tuning for deployment population is vital
© Daon Confidential Continual Technology Refresh A solution that will last for 30+ years must be prepared for major technology advancements during that time….. –Better matching algorithms (e.g ultrasound, fused hand and finger geometry) –Better biometric data capture and verification devices –New biometric types (DNA, Voice, Iris in motion…….) –Changes in process and policy –Improvements in Infrastructure Database Operating System Back office processing hardware
© Daon Confidential Continual and automatic updating of biometric data Storage of multiple instances of same biometric, captured at different times, to increase accuracy Updating of enrolment data if higher quality data later captured (e.g. at verification) Template aging – refresh of enrolment data Seamless migration to improved devices and algorithms –Through image storage and open standards Frequent reporting of biometric performance; problem prevention Ongoing threshold configuration and tuning based on offline analysis of recorded biometrics Automated detection of problem devices/sensors through increased error rates (FTE, FTA, FRR) beyond allowed deviations
© Daon Confidential 14 Which meant: Restoring the efficacy and credibility to the Nations immigration system Daons software powers the identity management platform authenticating all foreign nationals Deploying solutions in diverse locations; from detention centers to fishing boats AUSTRALIA ASKED US TO DESIGN AND IMPLEMENT AN IDENTITY AT EVENT SYSTEM TO PROTECT NATIONAL BORDERS AND IMMIGRATION
© Daon Confidential The case of Cornelia Rau
© Daon Confidential 16 The EU was faced with unprecedented movement of people (a hallmark of a modern society) requiring a pan EU biometric based VISA system Which meant: Daon helped design and is implementing a EU wide system that will prevent chronic security risks, such as VISA shopping Daon software will power a system to serve 70 million people THE EU SELECTED A DAON BASED SOLUTION TO DESIGN AND IMPLEMENT A PAN EU VISA SYSTEM FOR ALL 27 MEMBER STATES
© Daon Confidential miSenseplus - Registered Traveller Arrival in Dubai miSense card compatible with Dubai eGate infrastructure and Hong Kong equivalent. Traveller verified against local watch list database. Biometric card issued Biometric card issued and accepted a proxy for passport Fingerprint biometric and passport biographical information stored. ICAO standard encryption. ePassport version 2, similar to existing national identity cards. Identity Enrolment Dedicated enrolment station within existing UKIS facility. 13 Biometrics recorded and stored within existing UKIS biometric database. Background checks conducted and card activated within miSense system.
© Daon Confidential Summary - Common Approach to Large Populations Where possible enroll multiple biometrics –Virtually eliminates failure to enroll Consider Iris for duplicate checking Provide ICAO compliant quality facial images for human arbitration –Enables use of second biometric to improve accuracy and/or resolve false hits –Maximizes the long term payoff of the most cumbersome part of the entire processenrollment The incremental cost of enrolling multiple biometrics over time is small Take advantage of fingerprint biometrics and low cost sensors for automated 1:1 verifications of identity Populations can be divided into multiple matching subsystems tuned for specific population characteristics Develop an enroll once use many strategy Focus on implementing standards-based business processes such as BIAS
© Daon Confidential Thank You Leo Ring
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