Biometric Authentication Apparatus Dynamic Impedance Threshold
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Solution Overview
Problem
Existing biometric authentication systems face challenges in accurately distinguishing between live and fake biometric data, particularly with fake objects like gummy fingers, leading to false acceptance and security concerns.
Innovation Solution
An authentication apparatus that includes a forgery data extractor, similarity calculator, difficulty calculator, and threshold setter to determine the likelihood of forgery based on impedance and matching scores, dynamically adjusting thresholds to minimize false acceptance while maintaining security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed threshold is used for determining live or fake finger, then the determination process is simple, but live fingers with similar impedance characteristics to fakes are erroneously determined as fake
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed threshold to a dynamic threshold that changes based on the measured impedance value. The determination threshold is set to a first threshold when impedance is above a reference value, and to a second threshold (lower than the first) when impedance is below the reference value. This dynamic adjustment allows the system to adapt to varying impedance characteristics and reduce false rejection of live fingers while maintaining security against fakes.
Solution Approach 2:
The patent changes the parameter of the determination threshold based on the impedance measurement results. By adjusting the threshold value according to the measured impedance (setting different thresholds for different impedance ranges), the system optimizes its ability to distinguish between live fingers and fakes across different impedance conditions, thereby improving measurement precision without requiring a single complex determination algorithm.
2Reliability
If the determination threshold is lowered to reduce false rejection of live fingers, then live fingers are less likely to be erroneously determined as fake, but fake fingers become easier to authenticate
Solution Approach 1:
The patent applies local quality by setting different determination thresholds for different impedance conditions. Instead of using a single uniform threshold, the system uses a first threshold for impedance values above the reference and a second threshold for impedance values below the reference. This localized differentiation allows the system to optimize acceptance criteria for specific impedance characteristics, reducing both false rejection of live fingers and false acceptance of fakes.
Solution Approach 2:
The system uses feedback from the impedance measurement to dynamically adjust the determination threshold. The measured impedance value is fed back to the determination unit, which then selects the appropriate threshold (first or second) based on whether the impedance is above or below the reference value. This feedback mechanism enables the system to adapt its acceptance criteria based on the actual characteristics of the object being measured, thereby reducing false acceptance while maintaining security.
3Adaptability or versatility
If a single uniform threshold is used for all impedance values, then the system is simple to operate, but it cannot accommodate variations in finger state (dry, wet, etc.)
Solution Approach 1:
The patent makes the threshold dynamic rather than static. The determination threshold automatically adjusts based on the measured impedance value, which varies with finger state (dry, wet, etc.). This dynamic behavior allows the system to adapt to different finger conditions without requiring manual reconfiguration, thereby improving adaptability while keeping the operation simple through automatic threshold selection.
Solution Approach 2:
The system performs self-service by automatically selecting the appropriate determination threshold based on the measured impedance value. Instead of requiring user input or manual adjustment for different finger states, the system autonomously adjusts its own determination criteria based on the impedance measurement, thereby achieving adaptability to various finger conditions while maintaining ease of operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively reduces erroneous determination of live biometric data as fake, enhancing security by dynamically adjusting thresholds based on forgery similarity and difficulty, thereby reducing false acceptance and rejection rates.
Implementation Method 1
generate an oscillation frequency corresponding to an electrostatic capacity of an object under test, e.g. a live finger, to detect whether the object under test is a biologic object or not by comparing the oscillation frequency to a reference signal
Implementation Method 2
apply two square-wave input voltages having different frequencies to an object under test and calculating an impedance of the object under test on the basis of the output voltage to determine that the object under test is a live finger in accordance with whether the impedance is within an impedance range of live fingers
Data Source
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AI summary
An authentication apparatus is provided. A forgery determination threshold is determined on the basis of two types of parameters, a forgery similarity and a forgery difficulty. If a calculated value for an object under test is lower than or equal to the forgery determination threshold, then, it is determined that the object is a biologic object. Thus, easiness in impersonation with a fake of a biologic object that is easy to forge may be reduced, and a false rejection due to a determination in which a biologic object is erroneously determined as a fake may be reduced.