Column Value-Based Authorization for Statistical List Operations
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Solution Overview
Problem
Conventional authorization methods for statistical list operations in software systems lack refined control over column value permissions, leading to inefficiencies and errors in managing user permissions, especially in large-scale applications, where role-based access control mechanisms are cumbersome and prone to mistakes.
Innovation Solution
A column value-based separate authorization method that allows for selective authorization of statistical list operations by choosing specific columns and grantees, enabling granular control over data access and simplifying permission management by using templates and independent role assignments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional authorization methods are used for statistical list operations, then users can view statistical data corresponding to all column values or nothing at all, but operation permissions cannot be managed in a refined manner according to column values, greatly limiting usage
Solution Approach 1:
The patent segments the authorization mechanism by column values. Instead of treating statistical list authorization as a single unit, it divides permissions into granular column-value level units. This allows independent control of access rights for each column value combination, enabling refined permission management where different users can access different subsets of statistical data based on their roles and responsibilities.
Solution Approach 2:
The patent applies local quality by making authorization permissions location-specific to column values. Each column value in the statistical list can have its own authorization settings, allowing the system to provide different access rights for different data segments. This enables precise control where, for example, a manager can view only their department's statistical data while other departments remain restricted.
2Reliability
If a new statistical list is created for each column value to provide specific statistical data to different users, then refined permission control is achieved, but each column value involved needs to be stated in a specially created form, bringing inestimable workload
Solution Approach 1:
The patent creates a universal authorization framework that works across all statistical lists and column values. Instead of requiring separate authorization mechanisms for each statistical list or column value combination, the system provides a unified authorization interface that can control access to any column value in any statistical list. This multi-functional approach eliminates the need to create separate forms or authorization processes for each scenario.
Solution Approach 2:
The patent implements preliminary action by pre-establishing the column-value-based authorization structure and templates. The system prepares authorization configurations in advance, allowing administrators to define permission templates that can be quickly applied to multiple users and statistical lists. This preliminary setup reduces the time required for authorization configuration when new users or statistical lists are added.
3Device complexity
If the entire statistical list is provided to users to avoid creating multiple lists, then system complexity is reduced, but statistical data of other departments will be leaked, compromising data security
Solution Approach 1:
The patent introduces an intermediary authorization layer between the statistical list data and users. This intermediary mechanism controls access by filtering which column values are visible to each user based on their authorization permissions. The system acts as a mediator that allows legitimate access to authorized data while blocking access to unauthorized data, preventing data leakage without requiring complex data duplication or separate lists.
4Reliability
If conventional authorization methods are used, then operations on statistical data with null column values cannot be effectively authorized, but authorizing such data requires authorizing statistical data entries one by one, bringing huge workload and being error-prone
Solution Approach 1:
The patent applies copying by creating a standardized authorization template for null column values. Instead of requiring individual authorization for each statistical data entry with null values, the system creates a template that can be copied and applied to multiple entries simultaneously. This template-based approach maintains consistent authorization rules across all null value entries, reducing workload and minimizing errors while ensuring comprehensive coverage.
Data Source
AI summary
Disclosed is a column value-based separate authorization method for statistical list operations, said method comprising a step of authorizing a statistical list operation and a step of selecting a grantee, said step of authorizing a statistical list operation comprising the following steps: S1: selecting a statistical list needing authorization; S2: selecting a column needing authorization in the statistical list, the selected column being a column determined by selection or determined automatically; S3: authorizing the operation for statistical data corresponding to all the column values in the selected column. The present invention enables separate authorization of the operation permissions for the statistical data in the statistical list according to the column values; one statistical list can meet different actual usage requirements after the authorization of different statistical data operation permissions. Thus, the present invention is able to control the statistical data of the statistical list more strictly, improving the precision of management, meeting the usage requirements of enterprises and institutions in actual operations.