Collective User Permissions Table for Multi-Dimensional Security
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Solution Overview
Problem
Implementing permission restrictions in multi-dimensional security systems for enterprise businesses is inefficient, particularly when pushing permissions from a relational data store to a multi-dimensional store, leading to resource consumption issues.
Innovation Solution
Generating a collective user permissions table that consolidates user and group permissions, allowing for efficient deployment and enforcement of security settings across models and dimensions, reducing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If permissions are pushed from a relational data store to a multi-dimensional store, then security enforcement is achieved, but resource consumption increases
Solution Approach 1:
The system performs preliminary action by pre-calculating and materializing the Cartesian product of dimensions and security attributes before actual security enforcement is needed. This pre-computation of security contexts allows the multi-dimensional store to avoid resource-intensive real-time permission resolution operations during user access requests.
Solution Approach 2:
The patent introduces an intermediary security context table that acts as a mediator between the relational data store containing user permissions and the multi-dimensional store. This intermediary structure stores pre-computed security contexts, enabling efficient permission resolution without direct resource-intensive operations between the two stores.
2Adaptability or versatility
If detailed user and group permissions are stored separately, then permission flexibility is maintained, but system complexity increases
Solution Approach 1:
The patent merges user permissions and group permissions into a unified security context structure that is materialized in advance. By combining these separate permission sources into a pre-computed Cartesian product table, the system maintains the flexibility of detailed permissions while reducing runtime processing complexity through pre-aggregation.
Solution Approach 2:
The system performs preliminary computation to materialize the complete security context including all user and group permission combinations before actual access control operations. This pre-computed structure stores the Cartesian product of dimensions and security attributes, allowing flexible permission queries without complex real-time processing.
Data Source
AI summary
Efficient data structures are generated to enforce permissions on a multi-dimensional representation in a performance management application. A model site is generated having at least one model with at least one dimension. User permissions and group permissions are set for the model. The user permission and the group permissions are deployed to a relational database. A collective user permission table is generated based on the user permissions and the group permissions. Thus, an end user may receive permissions associated with a model and permissions associated with particular dimensions of a model without an inefficient consumption of resources.