Multi-Modal Biometric Authentication With Human Cross-Checking
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Solution Overview
Problem
Current biometric authentication systems lack robustness in verifying human identity, particularly in high-risk transactions, as they rely solely on machine-based algorithms which can be vulnerable to spoofing and anomalies, necessitating a more secure multi-modal authentication method that integrates human cross-checking for enhanced reliability.
Innovation Solution
A method for high fidelity multi-modal out-of-band biometric authentication that involves receiving biometric data, performing machine-based matching, determining the need for human identity confirmation, processing the data, sending it to contacts for verification, and authenticating the user based on both machine-based and human confirmation, utilizing a combination of biometric modalities like facial recognition, voice, and behavioral patterns, with a system that weights responses based on connectivity scores and confidence levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If machine-based biometric matching is used for authentication, then authentication speed and automation are improved, but reliability and security deteriorate due to vulnerability to spoofing and anomalies
Solution Approach 1:
The patent introduces human reviewers as an intermediary layer between the machine-based biometric matching system and the final authentication decision. When the algorithmic match confidence falls below a threshold or anomalies are detected, human reviewers examine the biometric data to make the final determination, thereby maintaining both automation efficiency and human judgment reliability
Solution Approach 2:
The system implements a feedback mechanism where the results of human review are fed back into the authentication system. This feedback loop allows the system to learn from human decisions, adjust confidence thresholds, and improve the overall reliability of the authentication process while maintaining high-speed processing for clear-cut cases
2Reliability
If human identity confirmation is added to biometric authentication, then reliability and security are improved, but system complexity and processing time worsen
Solution Approach 1:
The patent applies partial action by not requiring human review for all authentication cases. Instead, human identity confirmation is selectively applied only when the machine-based algorithm's confidence score falls below a predetermined threshold or when anomalies are detected, thus improving reliability without unnecessarily increasing system complexity for routine authentications
Solution Approach 2:
The authentication system is segmented into distinct processing paths: a high-confidence automated path for routine authentications and a low-confidence manual review path for suspicious cases. This segmentation allows the system to maintain simplicity for the majority of cases while providing enhanced reliability only where needed
3Measurement precision
If multiple biometric modalities are used for authentication, then measurement precision and reliability are improved, but device complexity and processing requirements worsen
Solution Approach 1:
The patent merges multiple biometric modalities (facial recognition, voice analysis, behavioral patterns) into a unified authentication framework that processes them through a common confidence scoring system. This merging approach improves measurement precision by cross-validating multiple biometric sources while managing complexity through a standardized evaluation architecture rather than separate processing systems for each modality
Data Source
AI summary
Systems and methods for high fidelity multi-modal out-of-band biometric authentication with cross-checking are disclosed. According to one embodiment, a method for integrated biometric authentication may include (1) receiving, from a user, biometric data; (2) at least one computer processor performing machine-based biometric matching on the biometric data; (3) the at least one computer processor determining that human identity confirmation is necessary; (4) the at least one computer processor processing the biometric data; (5) the at least one computer processor identifying at least one contact for human identity confirmation; (6) the at least one computer processor sending at least a portion of the processed biometric data for the user to the at least one contact; (7) receiving, from the at least one contact, human confirmation information; and (8) the at least one computer processor authenticating the user based on the machine-based biometric matching and the human confirmation information.