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Evaluation of the Human Biometric Sensor Interaction using Hand GeometryCarnahan Conference| San Jose, CA| October 7th, 2010,[object Object],Biometric Standards, Performance, and Assurance Laboratory | ,[object Object],Purdue University,[object Object], www.bspalabs.org,[object Object],www.twitter.com/bspalabs,[object Object],www.slideshare.net/bspalabs,[object Object],www.linkedin.com/companies/bspa-labs,[object Object]
Agenda,[object Object],Current Testing Standards and Norms,[object Object],The Missing Link?,[object Object],What performance evaluations should also explain,[object Object],Usability & Biometrics: Our systems should be usable?,[object Object],The Human-Biometric Sensor Interaction (HBSI),[object Object],HBSI Framework,[object Object],Applicability to Hand Geometry,[object Object],Questions,[object Object]
Scope – from Mansfield & Grother’sThe Wide World of Biometric Testing,[object Object],Measure FRR after data collection,[object Object],What should be done,[object Object],Have tests been driven by what can be done ,[object Object],VS,[object Object],Observe and count mispresentation effects,[object Object]
Development of a general model ,[object Object],Wayman ,[object Object],“commonly-held knowledge and oft-repeated descriptions of biometric identification systems are more complicated than necessary because of this lack of a generally accepted system model”,[object Object]
A General Biometric System Model (ISO/IEC 19795-1),[object Object]
What do our testing standards say?,[object Object],Distinctions between technology and scenario evaluations according to ISO/IEC 19795-2:,[object Object]
What do our testing standards say?,[object Object],What about the:,[object Object],Environment,[object Object],ISO/IEC 1st WD 29197, Evaluation methodology for environmental influence in biometric systems,[object Object],Human-Sensor Interaction,[object Object],…,[object Object]
Lack of user-centric design,[object Object],(A. Adams and M.A. Sasse, “Users are Not the Enemy: Why Users Compromise Security Mechanisms and How to Take Remedial Mea- sures,” Comm. ACM, vol. 42, no. 12, 1999, pp. 41–46 explain that typical security deployments ignore, or at least leave till the end the user-centric design.,[object Object]
Aim of HBSI model ,[object Object],Provide a structure and definition to errors that are observed while undertaking biometric tests on various biometric modalities. ,[object Object]
What Performance Evaluations Should Also Explain,[object Object],Is the algorithm the cause of matching errors?,[object Object],Is the application or environment the problem?,[object Object],Is the design of the sensor the problem?,[object Object],Are the users/agents causing the issue?,[object Object],Can users/agents do what the system/sensor is asking for?,[object Object],Do users/agents understand how to use the system/sensor?,[object Object],Can users/agents produce repeatable images?,[object Object]
HBSI model and deployed system,[object Object],Understanding how users interact with the system is also important for successful deployment of the biometric system. ,[object Object],Full habituation arises when match scores are stabilized,[object Object]
The journey to match score stabilization,[object Object]
Usability & Biometrics “Usability”,[object Object],Usability,[object Object],The extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use (ISO 9241-11:1998, ISO/IEC 25062:2006),[object Object],Failure to Acquire (FTA),[object Object],Traditional measure of “usability” in biometrics,[object Object],Proportion of verification or identification attempts for which the system fails to capture or locate an image or signal of sufficient quality (ISO/IEC 19795-1),[object Object]
The Human-Biometric Sensor Interaction (HBSI),[object Object],Derived from multiple research fields to better understand and evaluate overall functionality and performance of a biometric system,[object Object]
HBSI Framework for Biometric Interactions,[object Object],Objective,[object Object],Classify every human-sensor interaction “event” with the resulting biometric system “reaction”,[object Object],Event + Reaction =  HBSI episode,[object Object],Purpose,[object Object],Understand and classify all interactions / movements / behaviors that occur with a biometric device to improve performance, quality, and usability,[object Object],Examines a biometric system from 2 perspectives:,[object Object],User & Biometric System,[object Object]
HBSI Framework for Biometric Interactions,[object Object]
Incorrect Presentation – Defective Interaction,[object Object],A defective interaction occurs when a bad presentation is made by the subject to the hand geometry machine that is not detected by the system,[object Object]
Incorrect Presentation – User Concealed Interaction,[object Object],Presentations to the hand geometry machine when the user is at fault for the erroneous presentation.,[object Object]
Incorrect Presentation – System Concealed Interaction,[object Object],The user interacts with the hand geometry machine, but does not provide a good quality sample.,[object Object]
Incorrect Presentation – System Failure to Detect,[object Object],Where the user correctly places their hand in the hand geometry machine, but the machine does nothing and times out.,[object Object]
Incorrect Presentation – External FTD,[object Object],Factors outside the control of the user impact the system,[object Object]
Incorrect Presentation – Failure to Extract,[object Object],Occurs after a sample has been collected from the hand geometry machine, but the algorithm fails to extract meaningful data,[object Object]
Incorrect Presentation – Successfully Acquired Sample,[object Object],When the sample has been detected by the system and subsequently extracted and passed through to the biometric matching system,[object Object]
Observations,[object Object],Interaction videos are interesting so that we can segment these errors,[object Object],Once these errors have been identified we can improve training,[object Object]
Examples – False Interaction,[object Object]
Examples - FTX,[object Object]
Examples – System CI ,[object Object]
Examples - FTD ,[object Object]
Example - SAS,[object Object]
Results - Enrollment,[object Object]
Results - Verification,[object Object]
Analysis and Results,[object Object]
Future Work,[object Object],Evaluate more modalities with the framework,[object Object],physical-interactive,[object Object],image-based,[object Object],behavioral,[object Object],Refinement of the metrics,[object Object],Inter-rater reliability,[object Object],T&E Standard Methodology? ,[object Object]
Any Questions?,[object Object],Follow the discussion on the research blog after the conference,[object Object],www.bspalabs.org/,[object Object]
Authors and Primary Contact Information,[object Object],Authors,[object Object],Benny Senjaya,[object Object],Graduate Researcher at BSPA Lab,[object Object],bennysenjaya@gmail.com,[object Object],Stephen Elliott, Ph.D.,[object Object],BSPA Lab Director & Associate Professor,[object Object],elliott@purdue.edu,[object Object],Eric Kukula, Ph.D.,[object Object],Visiting Assistant Professor,[object Object],ekukula@gmail.com,[object Object],Mark Wade,[object Object],Undergraduate Researcher,[object Object],Jason Werner,[object Object],Undergraduate Researcher,[object Object],Contact Information,[object Object],Stephen Elliott, Ph.D.,[object Object],Associate Professor,[object Object],Director of BSPA Labs,[object Object],elliott@purdue.edu,[object Object]

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