AI Knowledge-Based Authentication Using One-Time Private Data
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Solution Overview
Problem
Traditional authentication systems are vulnerable to various threats such as weak passwords, password reuse, phishing attacks, brute force attacks, credential stuffing, insider threats, and social engineering, which compromise security and access management.
Innovation Solution
A computer-based system utilizing a processor and non-transitory memory for knowledge-based authentication, employing a private corpus of data, natural language processing, and artificial intelligence to generate dynamic, personalized challenge questions, ensuring secure and passwordless authentication through a system that includes a text/data preprocessing module, story telling process, multiple-choice generation, and nearest-neighbor one-time use matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional password-based authentication is used, then ease of operation is maintained, but security reliability deteriorates due to vulnerabilities to weak passwords, password reuse, and phishing attacks
Solution Approach 1:
The patent replaces the mechanical/password-based authentication system with an AI-driven knowledge-based authentication system. Instead of relying on passwords that can be guessed or reused, the system uses machine learning models to generate and validate personalized knowledge questions, substituting the traditional mechanical authentication mechanism with an intelligent one that adapts to user patterns and contexts.
Solution Approach 2:
The patent changes the parameters of authentication from static passwords to dynamic, context-aware knowledge questions. The system adjusts authentication parameters based on user behavior patterns, device context, and environmental factors, transforming the authentication process from a fixed mechanism to a flexible, adaptive one that maintains both security and ease of use.
2Reliability
If knowledge-based authentication with static questions is used, then authentication security improves, but adaptability deteriorates as questions can be predicted and reused
Solution Approach 1:
The patent implements dynamics by making authentication questions variable and context-dependent rather than static. The system generates questions dynamically based on user profiles, behavior patterns, and contextual information, ensuring that each authentication attempt presents unique questions that adapt to the specific situation, thereby preventing prediction and reuse of questions.
Solution Approach 2:
The system performs self-service by automatically generating and updating knowledge questions based on user behavior patterns and contextual data without requiring manual input. The AI models continuously learn from user interactions to create personalized, unpredictable questions, eliminating the need for user involvement in question creation while maintaining high adaptability and security.
3Adaptability or versatility
If AI-based dynamic question generation is implemented, then adaptability and security improve, but device complexity increases
Solution Approach 1:
The patent applies universality by designing a multi-functional AI system that handles multiple authentication tasks through a single integrated architecture. The same AI models and processing components generate questions, validate answers, detect fraud, and adapt to user patterns, consolidating multiple functions into one system that reduces overall complexity despite the advanced capabilities it provides.
Data Source
AI summary
Exemplary systems and methods utilize unique knowledge-based authentication techniques involving private and/or recent data. Via use of the disclosed concepts, authentication is made more robust, and is hardened against compromise techniques such as those drawing from prior data breaches, public records, and the like. In this manner, simpler and more reliable authentication is achieved.