Biometric Identity Verification With Adaptive Weighting for Match Accuracy
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Solution Overview
Problem
Existing identity verification technologies are inadequate in authenticating users based on false acceptance rate and false rejection rate, lack combination methods, and do not utilize weighted analysis, necessitating improved methods for self-optimizable biometrics identity verification.
Innovation Solution
A method and system for self-optimizable biometrics identity verification that involves obtaining and matching user data, determining match accuracy, generating a verification result, and authorizing user interactions, utilizing a comprehensive elemental weighting analysis algorithm to combine multiple biometric characteristics for optimized authentication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional identity verification methods are used, then the verification process is simple, but the authentication accuracy is low with high false acceptance and rejection rates
Solution Approach 1:
The patent combines multiple biometric verification methods (fingerprint, facial recognition, iris scan, voice recognition) into a unified verification system. This merging of multiple authentication techniques enables the system to achieve high authentication accuracy by cross-validating multiple biometric characteristics simultaneously, thereby resolving the contradiction between simple verification and accurate authentication.
Solution Approach 2:
The patent employs a composite verification approach that integrates different types of biometric data (physiological and behavioral characteristics) to create a multi-layered authentication mechanism. This composite verification strategy enhances measurement precision by leveraging the complementary strengths of various biometric modalities while managing system complexity through structured integration.
2Reliability
If multiple biometric verification methods are combined, then the authentication accuracy improves, but the system complexity increases
Solution Approach 1:
The patent implements dynamic verification requirements that adapt to different interaction scenarios. The system can adjust the number and type of biometric verification methods based on the security level required for specific operations, allowing the verification reliability to be optimized without permanently increasing system complexity. This dynamic approach enables flexible configuration of combination methods.
Solution Approach 2:
The patent applies different verification strategies to different parts of the authentication process. By assigning specific biometric methods to specific verification requirements and using localized weighting for different biometric characteristics, the system achieves high reliability where needed while keeping overall complexity manageable through differentiated verification approaches.
3Measurement precision
If weighted analysis of combination methods is implemented, then the false acceptance and rejection rates are minimized, but the computational complexity increases
Solution Approach 1:
The patent utilizes parameter-based weighting where each biometric characteristic is assigned a weight value that reflects its reliability and importance. By changing the parameters (weights) of different biometric methods based on their performance characteristics and the specific verification context, the system achieves precise match accuracy without requiring excessive computational power, as the weighting provides a straightforward mathematical approach to optimization.
4Adaptability or versatility
If personalized weight adjustments are applied, then the environmental adaptability improves, but the processing time increases
Solution Approach 1:
The patent performs preliminary weight assignments for different biometric characteristics based on pre-analyzed environmental factors and verification requirements. By preparing the weighting parameters in advance rather than calculating them in real-time during each verification, the system achieves environmental adaptability while minimizing processing time. This preliminary action allows the system to quickly apply pre-determined weights to verification results.
Data Source
AI summary
Disclosed herein is a method for facilitating self-optimizable biometrics identity verification of users, in accordance with some embodiments. Accordingly, the method includes obtaining one or more verifying data. The method includes retrieving one or more first verifying data of the user based on the verification requirement. The method includes matching the one or more verifying data with the one or more first verifying data of the user. The method includes determining an accuracy of a match between the one or more verifying data and the one or more first verifying data. The method includes generating a result for the self-optimizable biometrics identity verification based on the accuracy of the match. The method includes transmitting the result to a device. The method includes a step of authorizing the user for an interaction based on the result.