AI Access Checking for Multi-Resource Permission Decisions
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Solution Overview
Problem
Conventional systems lack an efficient and reliable method for managing complex data access permissions across multiple resources and repositories, leading to inefficiencies and potential errors in access control management.
Innovation Solution
A data-access management system utilizing an AI model, such as a large language model (LLM), to generate and manage access controls, check permissions, and provide explanations for access decisions, integrating role-based, attribute-based, and classification-based access controls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems are used for managing data access permissions, then implementation is simpler, but reliability and accuracy of access control management deteriorates due to inefficiencies and potential errors
Solution Approach 1:
The patent introduces an AI model as an intermediary component between users and data resources. This AI model automatically checks access permissions by analyzing user identities, resource requirements, and policy rules, thereby improving access control reliability without requiring complex manual management systems. The AI model acts as a smart mediator that handles the complexity of permission verification internally.
Solution Approach 2:
The system enables self-service access control checking where the AI model autonomously evaluates permission requests without human intervention. The model automatically determines whether users have adequate access rights by processing their identities and resource requirements against stored policies, eliminating the need for manual access control management and reducing errors.
2Productivity
If manual methods are used for checking access permissions, then system complexity is lower, but productivity and efficiency deteriorates due to time-consuming verification processes
Solution Approach 1:
The patent replaces manual mechanical processes of access permission checking with an AI-based automated system. The AI model processes permission requests by analyzing user identities, resource requirements, and policy rules computationally, dramatically improving checking efficiency. This substitution of mechanical manual verification with intelligent automated processing eliminates time-consuming human review while managing complexity through algorithmic approaches.
3Reliability
If detailed access control management is implemented across multiple resources, then security improves, but ease of operation deteriorates due to complex permission tracking
Solution Approach 1:
The patent extracts the complex task of access control management from human operators and encapsulates it within the AI model. The model internally handles the intricate analysis of user identities, resource requirements, and policy rules, presenting a simplified interface to users. This extraction of complexity into the automated system maintains high security through detailed permission tracking while improving ease of operation by eliminating manual management burdens.
Data Source
AI summary
In some examples, systems and methods for checking data access are provided. For example, a method includes: receiving a checking request about a user, the checking request including a user identifier of the user and a resource indication of a resource; determining one or more components referenced by the resource; for each component of the one or more components referenced by the resource, determining permission information indicating whether the user access to at least a part of the one or more components; and determining permission information indicating whether the user is permitted to access the resource.