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What is Biometrics?
• Biometrics: Traits of the human biological system, suitable for measurement and use in identification.
• There are two type of matching:– Verification: One to One (involves a token or
identifier).
– Identification: One to Many (used often in forensics).
• One to one is most often used in access control scenarios.
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What is Biometrics?
• A Few Biometric Applications:– Prison Visitor Systems
– Drivers license
– Canteen administration
– Benefit payment systems
– Border Control
– Forensics
– Logical Access Control
– Physical Access Control
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What is Biometrics?
• Some Possible Biometrics– Fingerprint, voice, ear, hand vein, retinal, facial, hand
geometry, DNA, keystroke, dental, signature, gait, body odor, iris.
• Desirable Biometric Traits– Universality
– Uniqueness
– Permanence
– Collectible
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What is Biometrics?
• Biometric Performance Terminology– (FAR) False Accept Rate
– (FRR) False Reject Rate
– Threshold (Sensitivity)
– ROC (Receiver Operating Characteristic) Curve• This involves plotting FAR and FRR against each other
between a varying threshold value.• Often it is difficult or impossible to change the threshold of a particular
vendor’s system.
• Often the biometrics sensor (hardware) is closely tied to the algorithm (enrollment and matching software).
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What is Biometrics?
• Two key pieces to Biometrics:
– Enrollment
– Matching (Verification or Identification)
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What is Biometrics?
Automated Biometric System:
A system which uses biological, physiological or behavioral characteristics to automatically authenticate the identity of an individual based on a previous enrollment.
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Biometrics - Industry Trends
• Sensor Improvements:– Improved temperature tolerances– Resistance to Electro-Static Discharge (SD)– Smaller footprint– Reduced power consumption– Additional hardware interfaces available
• Market is Windows-centric– Expansion into other operating environments
• Sun Solaris, Linux, embedded systems
• Maturation of standards and APIs
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Testing Fingerprint Sensors
• The most common Biometrics used is Fingerprinting.
• There are two main types of fingerprint sensors.– Capacitive
– Optical
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What We Tested
• How do environmental conditions affect fingerprint match scores with a capacitive sensor? The following tools were used:– Verifinger 4.0 software
– Authentec® capacitive fingerprint (USB)
• Fingerprint samples were colleted from friends, family, and students.
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Simulating Environmental Conditions
• Dry – Baby powder
• Hot – Heating Pad
• Cold – Ice
• Dirty – Dirt
• Oily – Motor Oil
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Analysis I
• Two tailed - Is there a relationship between sex and match score? – Ho: No relationship– Ha: There is a relationship
• One tailed – Do females receive lower match scores than males?
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Analysis I - Results
• Two tailed – Is there a relationship?– T – stat |3.54|
– T-critical 1.997
– P – value 0.0003 > 0.05
• One tailed – Is there a relationship?– T – stat |3.54|
– T-critical 1.6686
– P – value 0.0007 > 0.05
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Analysis II
• Correlation tests• Whether there is a relationship between an
environmental condition fingerprint match score and the normal fingerprint match score?
• Ho: There is no relationship between the two scores.
• Ha: There is a relationship between the two scores
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Analysis II – Normal v . Hot
• P – value (Significance F) = 5.25E-23 > 0.05– Statistical Significance
• Multiple R = 0.8542– Positive relationship (85.42%) between hot
match score and normal match score
• Accept Alternative Hypothesis
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Analysis II – Normal v. Cold
• P – value (Significance F) = 7.22E-26 > 0.05– Statistical Significance
• Multiple R = 0.8793– Positive relationship (87.93%) between cold
match score and normal match score
• Accept Alternative Hypothesis
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Analysis II – Normal v. Dry
• P – value (Significance F) = 3.21E-07 > 0.05– Statistical Significance
• Multiple R = 0.5438– Positive relationship (54.38%) between dry
match score and normal match score
• Accept Alternative Hypothesis
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Analysis II – Normal v. Dirty
• P – value (Significance F) = 4.38E-09 > 0.05– Statistical Significance
• Multiple R = 0.6084– Positive relationship (60.84%) between dirty
match score and normal match score
• Accept Alternative Hypothesis
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Analysis II – Normal v. Greasy
• P – value (Significance F) = 2.49E-10 > 0.05– Statistical Significance
• Multiple R = 0.6447– Positive relationship (64.47%) between greasy
match score and normal match score
• Accept Alternative Hypothesis
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Conclusion
• Different entrance threshold rates should be used for the different sexes
• Different entrance threshold rates should be used for the different environmental conditions– Dry and Dirty fingers need lower thresholds