AI Analysis of Security Access Descriptions for Entitlement Clarity
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Solution Overview
Problem
Security access descriptions often have low descriptive quality, leading to improper entitlement grants and increased security risks and resource wastage due to misunderstandings and misinterpretations.
Innovation Solution
An AI analysis system using machine learning models, including a random forest model for descriptive quality labeling and a question-answering model for component clarity, to enhance the clarity and accuracy of security access descriptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If security access descriptions are manually created, then implementation speed is improved, but descriptive quality deteriorates leading to misunderstandings and misinterpretations
Solution Approach 1:
The patent introduces an AI analysis system as an intermediary between the manual creation of security access descriptions and their final interpretation. This system includes machine learning models that automatically analyze descriptions, generate quality scores, and provide recommendations, thereby preserving the speed of manual creation while improving descriptive quality through automated assistance.
Solution Approach 2:
The system implements feedback by analyzing security access descriptions and providing quality assessments and recommendations back to the creators. The AI model generates quality scores and specific improvement suggestions, creating a feedback loop that enables continuous improvement of description quality without sacrificing implementation speed.
2Loss of energy
If security access descriptions have low descriptive quality, then resource consumption during creation is reduced, but security risks increase due to improper entitlement grants
Solution Approach 1:
The system performs preliminary analysis of security access descriptions before they are finalized and implemented. By analyzing descriptions upfront and providing quality assessments and recommendations in advance, the system prevents improper entitlement grants without requiring additional resources during the entitlement granting process itself.
Solution Approach 2:
The AI analysis system enables creators to self-improve their security access descriptions by providing automated quality assessments and specific recommendations. This allows creators to enhance description quality and reduce security risks without requiring additional expert review resources.
3Loss of information
If AI analysis systems are implemented, then descriptive quality is improved, but system complexity increases
Solution Approach 1:
The AI analysis system serves as an intermediary layer between the simple act of creating security access descriptions and the complex requirements of ensuring their quality. By placing the analytical complexity in a separate, dedicated system rather than embedding it in the entitlement management workflow, the patent improves descriptive quality while minimizing the complexity burden on the core system.
Data Source
AI summary
Some implementations described herein relate to a system for artificial intelligence analysis of security access descriptions. The system identifies a security access description. The system determines metadata information associated with the security access description. The system determines, by processing the security access description using a first set of one or more machine learning models, a descriptive quality label associated with the security access description. The system determines, by processing the security access description using a second set of one or more machine learning models, one or more descriptive components associated with the security access description and one or more descriptive component labels that correspond to the one or more descriptive components. The system provides the metadata information, the descriptive quality label, the one or more descriptive components, and/or the one or more descriptive component labels.