Authorized Role Prediction and Registration for ERP Access
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Solution Overview
Problem
Existing ERP systems face challenges in efficiently determining and managing authorized roles due to the complexity arising from organization-dependent factors such as size, security levels, and number of owners, leading to delays in granting or denying access to enterprise resources.
Innovation Solution
An authorized roles tool utilizing a data management model generated through machine learning techniques to predict and register unregistered actions and permissions, automating the role assignment process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual role definition and access management is performed in ERP systems, then security and protection of enterprise resources is ensured, but the complexity of defining roles increases significantly due to organization-dependent factors such as size, security levels, and number of owners
Solution Approach 1:
The system automatically determines authorized roles by analyzing user profiles, system configurations, and enterprise resources without requiring manual intervention. The role determination is performed autonomously by the processor executing the patent's methodology, eliminating the need for complex manual role definition processes while maintaining security requirements.
2Reliability
If manual role definition and access management is performed in ERP systems, then access control to enterprise resources is implemented, but delays occur in granting or denying access to systems, computer applications, or data sets
Solution Approach 1:
The system pre-determines authorized roles by automatically analyzing user profiles, system configurations, and enterprise resources before access requests are made. This preliminary automated role determination eliminates delays in granting or denying access, as the system can immediately evaluate access requests against pre-computed role assignments.
3Productivity
If automated role determination using machine learning is implemented, then the time required to authorize or deny access is reduced, but the complexity of the system increases due to the need for data management models and training processes
Solution Approach 1:
The patent introduces a data management model as an intermediary layer between the automated role determination process and the ERP system. This model, trained on organizational data, mediates the complex machine learning operations by providing structured inputs and outputs that integrate smoothly with existing ERP infrastructure, thereby reducing the perceived complexity while maintaining high productivity.
Data Source
AI summary
According to an embodiment of the present disclosure, an authorized roles tool includes an analyzer to determine a type of request received from a user including an unregistered action, an unregistered permission, or a combination thereof, a predictor to predict, using a data management model, a role with which to associate the unregistered action, the unregistered permission, or the combination thereof, and a registrar to register the unregistered action, the unregistered permission, or the combination thereof to the role.