EasyPASS – Evaluation of face recognition performance in an operational automated border control system 

Markus Nuppeney – Federal Office for Information Security (BSI) Marco Breitenstein – secunet Security Networks AG Matthias Niesing – secunet Security Networks AG 

Markus Nuppeney Gaithersburg, March 2. 2010 1 

Motivation for usage of the new features of ePassports 

Increase security electronic security mechanisms prevent forgery biometrics prevent misuse of real documents 

Improve efficiency by using automated checking routines 

Ease of use for the holder of the document (self-service scenarios) for the border control officer (more time for critical cases) 

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Main steps towardsEasyPASS 

Nov. 2005: Issuance of the 1st generation ePassport (face) Nov. 2007: Issuance of the 2nd generation ePassport (face and finger) Nov. 2007: Start of the pilot project “Reading and Checking ePassports” 

Read and checked ePassports from 62 countries Setup of the background infrastructure to provide trusted CSCA certificates Able to check the complete chain of trust from 40 countries 

Aug. 2009: Start of the pilot project EasyPASS 

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The EasyPASS project –overview 

Pilot project of BSI and the German Federal Police Semi-automated eGate scenario 

Monitoring (and if necessary interaction) by border police officer 

4 Self-service eGates, 1 monitoring station Open for citizens of EU/EEA/CH (18+ years old) Located at Frankfurt Airport Timetable 

Start of operation was in August 2009 Initial pilot will run until March 2010 

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The EasyPASS border control process using facial recognition 

Check of entitlement 

Optical checks 

Electronic checks 

Background checks 

Capture and Comparison 

Chip image  Live imagBorder crossing 

e 

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EasyPASS – software architecture 

Software integration platform BioMiddle Modular and platform independent architecture for biometric applications Standard interfaces and protocols (SOAP, BioAPI 2.0, ISO/IEC 19794-x, etc.) Allows an easy integration of document readers, biometric components and background systems 

Electronic document reading by ePassportAPI Access to optical document reader via oPassportAPI Access to biometric components based on BioAPI 2.0 (ISO/IEC 19784) Access to INPOL/SIS and LDAP directory via Background Interface providers 

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Image acquisition Integration of camera via BioAPI Capture BSP Internal pre-qualification regarding ISO19794-5 

Verification 3 different biometric verification algorithms 

one main algorithm for each eGate two additional algorithms for statistical and evaluation purposes 

Quality measurement 3 different quality assurance (QA) tools for statistical and evaluation purposes 

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Biometric evaluation – theory and practice 

Algorithm evaluations (e.g. FRVT) Good for benchmarking But not significant for real life performance 

Real life performance depends on the specific application scenario 

Characteristic of reference data Live image source Environmental conditions User behavior Process design (allowed number of attempts, time-outs etc.) 

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EasyPASS – face biometrics 

Biometric evaluation – specific EasyPASS conditions 

Reference data DG2 images from European ePassports Should be compliant to ISO19794-5, but are they? 

Live images Source: CCD camera Configuration adjusted to the specific EasyPASS scenario 

Process design Continuous capturing of live images Successive verifications with the best of the captured images (based on the internal pre-qualification regarding ISO19794-5) Process stops when verification successful (depending on a threshold) or after time-out 

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Biometric evaluation – data collection 

“Pre-operational” project phase (Aug. – Sept. 2009) Temporary database built up with image data collected from real passengers using the EasyPASS system Database consists of images of about 9.000 passengers 

DG2 image from the ePassport Live image(s) captured within the eGate 

Operational project phase (since Oct. 2009) Genuine scores 

Comparison of DG2 image against live image(s) of the passenger Imposter scores 

Comparison of DG2 image of the current passenger against live images in the database Comparison of live image(s) of the current passenger against DG2 images in the database 

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Biometric evaluation – objectives for EasyPASS project 

Evaluation of usability and security in the real life environment 

Calculation of complete DET curves based on genuine and imposter scores for each biometric verification algorithm 

Identification of proper algorithm configurations for the specific EasyPASS application scenario Evaluation of ePassport image quality 

Specific for the different countries Correlation between image quality and verification performance 

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EasyPASS – very first statistics(since Oct. 2009, first 5 months of operation) 

Total number of users: ≈ 25.000 100 – 200 people per day 

Period to pass the eGate: ≈ 16 sec. Time from presenting the passport on the reader until the exit door is closed 

Recognition performance: ≈ 5% FRR @ 0,1% FAR Origin: 85% german nationals 

15% foreign nationals from EU/EEA/CH 

Gender: 60% male 40% female 

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EasyPASS – first lessons learned (biometrics) 

Verification thresholds recommended by vendors did not fit to the actual application scenario Appropriate thresholds have to be calculated based on the real user group and the actual system setup Recommendation for iterative system configuration 

Operate the system on a (assumed) high security level and collect genuine and impostor comparison scores Calculate verification performance in terms of FAR and FRR Update the algorithm configuration to the required security level (expected FAR) 

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EasyPASS – first lessons learned (operation) 

Passengers do not know if they have an ePassport Even there is a labelling at the EU/non-EU separation and at the document reader many passengers with an “old” passport try to use the eGates 

Passengers do not know how to put the passport onto the reader 

Results in high reading errors Reading errors where reduced by changing the user guidance and some mechanical changes 

Passengers are surprised about the fast and easy process 

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EasyPASS – summing-up key features 

Combination of different checks to ensure a secure process Validation of optical and electronic document security features Biometric comparison on a high secure level Online background checks 

Complete checking of the electronic features Biometrics are of no use, if not authenticated! Online requests for trusted CSCA certificates 

Fast and easy process (Approx. 16 sec) Innovative software architecture (BioMiddle) Detailed evaluation of real life performance 

Different biometric algorithms in the real life environment 

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EasyPASS – project partners 

BSI System design Realisation of pilot project 

Federal Police Specification of requirements Operation of EasyPASS 

FRAPORT AG (owner and operator of Frankfurt Airport) 

Provision of infrastructure 

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EasyPASS – technology providers 

secunet Security Networks AG Cognitec Systems GmbH Software framework Biometric verification algorithm System integration Biometric quality measurement 

Monitoring and evaluation NEC Deutschland GmbH Biometric verification algorithm L-1 Identity Solutions AG Biometric quality measurement (in cooperation with 

Magnetic Autocontrol GmbH) Bundesdruckerei GmbH Camera system 

Document readers eGate hardware Document database Biometric verification algorithm 

Biometric quality measurement 

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Thank you! 

Federal Office for Information Security (BSI) 

Markus Nuppeney 

markus.nuppeney@bsi.bund.de www.bsi.de 

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