AI Authentication Data Structures for Dynamic Access Privileges
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Solution Overview
Problem
Conventional resource access management techniques require static subscription efforts, leading to security risks due to provisioning of resource access, especially when users change teams within an enterprise.
Innovation Solution
An artificial intelligence-based authentication system processes user-related and application-related data structures using large language models to dynamically manage resource access privileges, eliminating the need for conventional directory-based models and providing fine-grained, adaptive access control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static subscription efforts are used for resource access management, then ease of operation is improved, but security reliability deteriorates due to over-provisioning and provisioning errors
Solution Approach 1:
The patent implements dynamic access privilege management by continuously monitoring user activity data and automatically adjusting access rights based on actual usage patterns. The system transitions from static subscription-based access control to a dynamic model where privileges are granted and revoked in real-time based on observed user behavior, thereby maintaining security reliability while improving operational ease through automation.
Solution Approach 2:
The system incorporates feedback mechanisms by continuously collecting user activity data and using it to adjust access privileges. The authentication system monitors user interactions with resources and feeds this information back into the access control decisions, creating a closed-loop system that adapts to actual usage patterns and eliminates over-provisioning errors.
2Reliability
If dynamic access privilege management is implemented using AI techniques, then security reliability is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service automation where the AI authentication system autonomously manages access privileges without requiring manual intervention from administrators. The system automatically analyzes user activity data, determines appropriate access rights, and enforces policies, thereby reducing the operational complexity burden on human operators while maintaining high security reliability through intelligent automation.
Solution Approach 2:
The system replaces traditional mechanical access control mechanisms with AI-based intelligent systems. Instead of relying on static role-based access control or manual administrative processes, the patent employs machine learning models and natural language processing to automatically determine and enforce access privileges, substituting complex manual procedures with intelligent automated decision-making.
3Ease of operation
If conventional directory-based models are used, then ease of operation is maintained, but adaptability deteriorates when users change teams or roles
Solution Approach 1:
The patent implements dynamic access privilege management by continuously monitoring user activity data and automatically adjusting access rights based on actual usage patterns. The system transitions from static subscription-based access control to a dynamic model where privileges are granted and revoked in real-time based on observed user behavior, thereby maintaining security reliability while improving operational ease through automation.
Solution Approach 2:
The system dynamically changes access control parameters based on user activity patterns and contextual information. Instead of fixed role-based permissions, the patent adjusts access privileges in real-time by analyzing user behavior, device information, location, and other contextual parameters, enabling the system to adapt automatically when users change teams or roles without requiring manual reconfiguration.
Data Source
AI summary
Methods, apparatus, and processor-readable storage media for artificial intelligence-based authentication systems with processing of data structures are provided herein. An example computer-implemented method includes obtaining information pertaining to at least one authentication request between at least one user and at least one application; determining one or more commonalities pertaining to the user(s) and the application(s) by processing, using one or more artificial intelligence techniques, a first set of one or more data structures associated with user-related data and a second set of one or more data structures associated with application-related data; generating and outputting, to at least one user device associated with the user(s), one or more queries related to user activity with respect to the application(s); and performing one or more automated actions in connection with the authentication request(s) and based on one or more user responses to at least a portion of the one or more queries.