Continuous Voice and Face Biometric Authentication
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Solution Overview
Problem
Traditional methods for authenticating online identities, such as using PINs, passwords, SMS-based one-time codes, and hardware tokens, are insecure, expensive, and cumbersome, failing to effectively distinguish between authorized users and fraudulent attempts, including those from bots.
Innovation Solution
A computer-implemented method utilizing fused voice and face biometric technologies, where a user's voice and visual appearance are continuously monitored over a temporal session, generating a confidence level based on the correspondence with predetermined data sets, and authenticating the user if the confidence level exceeds a predetermined value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication methods (PINs, passwords, SMS codes, hardware tokens) are used, then security credentials can be verified, but the system becomes insecure, expensive, and cumbersome to use
Solution Approach 1:
The patent combines multiple authentication factors (something you know, something you have, and biometric characteristics) into a unified continuous authentication system. Voice and facial biometrics are integrated with session monitoring to provide multi-factor authentication without requiring separate hardware tokens or SMS messages, thereby improving security while maintaining user convenience.
Solution Approach 2:
The patent replaces mechanical authentication systems (hardware tokens, card readers, SMS messaging infrastructure) with biometric-based continuous authentication using voice and facial recognition. This substitution eliminates the need for physical security credentials and complex delivery mechanisms, reducing cost and improving ease of operation while maintaining or enhancing security.
2Reliability
If multiple authentication factors are implemented, then higher levels of security are achieved, but the system becomes more complex and expensive to deliver
Solution Approach 1:
The patent creates a universal authentication framework that can accommodate multiple authentication factors (voice biometrics, facial biometrics, knowledge-based credentials) within a single continuous authentication system. This multi-functional approach provides high-level identity assurance without requiring separate complex systems for each authentication factor, as all factors are integrated into one unified process.
Solution Approach 2:
The continuous authentication system automatically monitors voice and facial characteristics throughout the user session without requiring manual intervention or complex configuration. The system self-manages the authentication process, continuously verifying identity through biometric data streams, which reduces operational complexity while maintaining high identity assurance levels.
3Object-affected harmful factors
If continuous monitoring of voice and visual appearance is performed, then fraud detection capability is improved, but the system requires sophisticated biometric analysis
Solution Approach 1:
The patent implements continuous monitoring of voice and facial biometrics throughout the user session rather than discrete authentication checks. This continuous action allows the system to detect fraud attempts at any point during the session by analyzing biometric data streams in real-time, improving fraud detection capability while the continuous nature of the monitoring simplifies the detection process compared to intermittent checks.
Solution Approach 2:
The system continuously analyzes biometric data and provides feedback on authentication confidence levels throughout the session. This feedback mechanism allows the system to adjust security measures dynamically and detect fraud attempts by identifying anomalies in biometric patterns, improving fraud detection while the automated feedback loop reduces the complexity of manual biometric analysis.
Data Source
AI summary
A computer-implemented method of authenticating an identity of a specific user is disclosed. The method comprises the steps of acquiring a first data set representative of a voice of a user over a time interval between a first and second time, and providing the first data set as input to a computing device. The method further comprises acquiring a second data set representative of a visual appearance of at least a portion of the user over the time interval between the first and second time, and providing the second data set as input to the computing device. The method further comprises maintaining a temporal synchronous of the first and second data sets over the time interval comparing the first and second data sets with predetermined data sets relating to the voice and visual appearance of at least a portion of the specific user, generating a confidence level in dependence of a relative correspondence of the first and second data sets with the predetermined data sets and authenticating the user as the specific user where the confidence level is above a predetermined value.