Biometric Template Segmentation for Secure Authentication
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Solution Overview
Problem
Current biometric registration processes cannot distinguish between single and multiple users registering their biometric features, leading to potential fraudulent activities as any registered user can authenticate as another.
Innovation Solution
A method and system that involve receiving multiple scans of a biometric feature, extracting distinct elements, recording characterization data, and updating a biometric template to ensure secure authentication by validating and updating the template with additional characterization data from subsequent scans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a single biometric template is stored during registration, then authentication speed is improved, but authentication security deteriorates because multiple users can authenticate as any registered user
Solution Approach 1:
The patent segments a single biometric template into multiple distinct biometric elements, each with its own characterization data. This segmentation allows the system to verify multiple unique biometric features while maintaining fast authentication, resolving the contradiction between speed and security.
Solution Approach 2:
The patent applies local quality by recording specific characterization data for each distinct biometric element rather than a generic template. This localized detail verification enhances security while maintaining authentication speed by focusing validation on specific biometric features.
2Reliability
If multiple distinct elements are extracted and validated, then authentication security is improved, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically extracting distinct biometric elements and generating characterization data without requiring manual configuration. This automation reduces the perceived complexity for users while maintaining high security standards.
Solution Approach 2:
The patent changes parameters by transforming raw biometric data into structured templates with distinct elements and characterization data. This parameter transformation automates the complex validation process, reducing operational complexity while enhancing security.
3Measurement precision
If characterization data is recorded for each distinct element, then biometric data uniqueness is improved, but data storage requirements increase
Solution Approach 1:
The patent extracts only the essential characterization data needed to verify each distinct biometric element, removing redundant information. This extraction maintains high measurement precision for uniqueness verification while minimizing data storage requirements.
Solution Approach 2:
The system applies partial action by recording characterization data selectively for each distinct biometric element rather than storing complete raw biometric data. This approach achieves sufficient uniqueness verification with reduced storage requirements.
Data Source
AI summary
Registering a biometric template with a computing device includes receiving a first scan of a biometric feature from a biometric sensor. The first scan includes first biometric data. The computing device extracts two or more distinct elements of the biometric feature and writes a biometric template to a memory. The first characterization data for each of the two or more distinct elements is recorded in the biometric template. After recording the first characterization data in the biometric template, the computing device receives an additional scan of the biometric feature from the biometric sensor. The additional scan includes second biometric data. The computing device validates the biometric template against the second biometric data. After validating the biometric template, the biometric template is updated with second characterization data. The second characterization data is associated with two or more additional distinct elements of the biometric feature contained in the second biometric data.