Persona Credential Engine Dynamic Trust Authentication
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Solution Overview
Problem
Current identity verification systems are vulnerable to deception and data breaches, with increasing costs due to cybercrime, and lack effective methods for nonrepudiation and secure authentication, especially in online transactions.
Innovation Solution
The Persona Credential Engine (PCE) provides a dynamic, multi-dimensional, and passive identity verification system that uses predictive trust models and trust levels to authenticate users based on their behavior patterns, biometrics, and environmental data, reducing the need for direct user input and enhancing security by constantly updating and refreshing trust levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional identity verification methods are used, then authentication can be performed, but the system is vulnerable to deception and data breaches
Solution Approach 1:
The patent implements dynamic trust levels that continuously adapt based on behavioral biometrics and contextual factors. The system transitions from static authentication to dynamic verification, where trust scores are constantly updated based on user behavior patterns, device characteristics, and environmental context, making the system resistant to deception and adaptive to emerging threats
Solution Approach 2:
The patent introduces behavioral biometrics as an intermediary layer between traditional authentication methods and security verification. This intermediary analyzes subtle user behaviors, device interactions, and contextual signals to create a mediating trust assessment that enhances security without requiring direct user input or disrupting the authentication flow
2Reliability
If multi-factor authentication is implemented, then security is improved, but user friction and complexity increase
Solution Approach 1:
The patent enables the system to automatically perform authentication verification using passive behavioral biometrics collected during normal user interactions. The system self-services the authentication process by continuously monitoring and analyzing user behaviors, device characteristics, and contextual signals without requiring active user participation or additional authentication steps
Solution Approach 2:
The patent performs preliminary authentication assessments by continuously collecting and analyzing behavioral biometrics during normal system usage. Trust levels are established and updated in advance based on accumulated behavioral data, so that when authentication is needed, the verification is already complete or can be rapidly finalized without user friction
Data Source
AI summary
A system for a dynamically evolving cognitive architecture for the development of a secure key and confidence level based data derived from biometric sensors and a user's behavioral activities. The system comprises one or more processors, one or more sensors, one or more databases, and non-transitory computer readable memory. The non-transitory computer readable memory comprises a plurality of executable instructions wherein the instructions, when executed by the one or more processors, cause the one or more processors to process operations comprising creating a set of policies based on user data sets and inputs, creating a faceted classification, establishing a Trust Level, processing sensor data, comparing data to one or more databases, correlating data, updating Trust Levels, updating security keys, and storing the keys in memory. In certain embodiments, the stored data is used to create a usage schema independent from a user's actual identity.