Dynamic Multi-Factor Authentication via Passive Biometric Confidence Aggregation
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Solution Overview
Problem
Traditional authentication methods are vulnerable to manipulation and are often intrusive, compromising accuracy and reliability, and leading to security vulnerabilities.
Innovation Solution
A dynamic multi-factor authentication system that uses a method comprising receiving input data related to an individual's traits, determining confidence ratios for each trait, aggregating these ratios to determine a final confidence ratio, and making an authentication decision based on this ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication methods (passwords, tokens) are used, then the authentication process is simple to implement, but the system becomes vulnerable to manipulation and security breaches
Solution Approach 1:
The authentication system is segmented into multiple independent authentication units, each responsible for verifying a specific trait or factor. This segmentation allows the system to evaluate multiple authentication factors in parallel while maintaining modularity and ease of implementation, resolving the contradiction between security reliability and system complexity.
Solution Approach 2:
The system dynamically adjusts the authentication process by evaluating confidence ratios for each trait and aggregating them to make real-time authentication decisions. This dynamic approach enhances security reliability by adaptively responding to authentication confidence levels while maintaining manageable system complexity through automated decision-making algorithms.
2Measurement precision
If biometric data collection methods (retina scanning, fingerprint scanning) are used, then authentication accuracy is improved, but the process becomes intrusive and time-consuming
Solution Approach 1:
The authentication system operates as a self-service mechanism by passively collecting biometric data from multiple sources simultaneously without requiring active user participation. The system automatically processes and evaluates the collected data, maintaining high authentication accuracy while eliminating the need for users to actively engage in intrusive scanning processes.
Solution Approach 2:
The system merges multiple passive data collection methods into a unified authentication process, combining various biometric and behavioral traits into a single confidence ratio evaluation. This integration maintains measurement precision through multi-factor verification while improving ease of operation by consolidating the user experience into a seamless, non-intrusive process.
3Reliability
If multiple authentication factors are evaluated simultaneously, then authentication reliability is enhanced, but the processing time and system complexity increase
Solution Approach 1:
The authentication process is segmented into independent evaluation units that process different traits simultaneously. By dividing the multi-factor authentication into parallel processing segments, the system enhances reliability through comprehensive evaluation while minimizing processing time through concurrent operation of authentication units.
Solution Approach 2:
The system maintains continuous authentication evaluation by processing multiple factors in parallel without sequential delays. The confidence ratio aggregation unit continuously receives and processes data from multiple authentication units, ensuring that the useful action of authentication evaluation continues uninterrupted, thereby enhancing reliability without increasing processing time.
Data Source
AI summary
Systems and methods for authenticating users are described herein. One or more inputs including of biometric data, physical trait data, and other data sources may be collected passively when an individual is present in a space. A confidence ratio associated with one or more of the collected inputs may be determined. One or more of the determined confidence ratios may be evaluated together to determine a final confidence ratio for a user, on which an authentication decision is based. An access level may be selected from a plurality of access levels with different access privileges based on the determined confidence ratio. Authentication may be continuous or ongoing.