Automated Biometric Attack Testing with Mechanical Arm Positioning
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Solution Overview
Problem
Current biometric recognition testing methods are inefficient and inaccurate due to the stochastic nature of machine learning algorithms, requiring extensive human resources and lengthy testing periods with high error variances, making it difficult to reproduce results.
Innovation Solution
A biometric recognition attack test method and apparatus utilizing a mechanical arm to position and pose test images or physical models within a recognition area of a biometric device, allowing for automated testing and improved accuracy by adjusting various parameters such as distance and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual testing with multiple test volunteers is used, then biometric recognition capability can be tested, but human resources are consumed and testing period is extended
Solution Approach 1:
The patent uses virtual avatars generated from test volunteer data to represent physical test subjects. These digital copies can be repeatedly tested without consuming additional human resources, allowing the same testing process to be executed multiple times to obtain statistical results, thereby resolving the contradiction between reliable testing and testing efficiency
Solution Approach 2:
The patent replaces manual physical testing with an automated testing system that uses virtual avatars and algorithmic evaluation. The mechanical process of manual observation and recording is substituted with automated image processing and statistical analysis, significantly reducing human resource consumption while maintaining testing reliability
2Reliability
If manual testing operations are used, then testing can be performed, but error variances are large and reproduction is difficult
Solution Approach 1:
The patent implements a feedback mechanism where testing results from virtual avatars are automatically analyzed and used to evaluate biometric recognition performance. The system provides quantitative feedback on recognition accuracy, false acceptance rates, and false rejection rates, enabling precise measurement and reproduction of testing results without the variability introduced by manual operations
Solution Approach 2:
The patent changes the parameters of testing by using virtual avatars with controlled characteristics and automated evaluation metrics. By standardizing the test objects (virtual avatars) and measurement methods (automated algorithms), the system eliminates the parameter variations caused by manual testing, achieving consistent and reproducible results
3Reliability
If multiple machine learning algorithms are used, then biometric recognition can be improved, but stochastic results require large quantity of attempts
Solution Approach 1:
The patent performs preliminary action by pre-generating multiple virtual avatars with different characteristics before actual testing. This allows the system to prepare a diverse set of test cases in advance, enabling efficient evaluation of multiple machine learning algorithms without requiring time-consuming real-time testing with actual volunteers for each algorithm variant
Data Source
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AI summary
Embodiments of the present specification disclose a biometric recognition attack test method, apparatus, and device. The method includes: obtaining, based on information about a target user to be tested, a test object needed for performing a biometric recognition attack on the target user, where the test object includes a test image and/or a physical model of a body part corresponding to the biometric recognition attack; controlling a mechanical arm to place the test image or the physical model of the body part in the test object in a recognition area of a biometric recognition device, and controlling the mechanical arm to adjust the test object in a plurality of different positions and poses to perform a biometric recognition attack test, to obtain a test result for the test object in each position and pose; and determining, based on the test result corresponding to the test object in each position and pose, a test result of the biometric recognition attack performed on the target user.