Power-Based Query Compliance for Data Privacy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing database systems lack the ability to enforce customizable data usage rules and pricing schemes for queries, leading to potential privacy violations and inefficient resource allocation.
Innovation Solution
Implement a query processing system with pre-execution and runtime compliance modules to enforce query cost and usage rules, integrating provider and user management systems to manage data access and pricing dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a database system allows unrestricted query access, then ease of operation is improved, but data privacy and security deteriorate
Solution Approach 1:
The system performs preliminary actions by evaluating query cost data and determining approval status before query execution occurs. The compliance module checks whether a query is approved based on pre-calculated cost data, and only executes queries that pass this preliminary review, thereby preventing unauthorized data access while maintaining ease of operation for approved queries
Solution Approach 2:
The compliance module serves as an intermediary between query requests and data access. It receives query requests, evaluates them against cost thresholds and provider rules, and mediates the execution by allowing or blocking queries based on their cost and approval status, thus protecting data privacy while maintaining operational ease for compliant queries
2Ease of operation
If query cost data is not enforced, then ease of operation is improved, but resource allocation efficiency deteriorates
Solution Approach 1:
The system calculates and stores query cost data in advance before execution occurs. The compliance module uses this pre-calculated cost data to determine whether to approve or block queries, enabling efficient resource allocation decisions to be made beforehand without adding significant operational complexity during query execution
Solution Approach 2:
The system implements feedback mechanisms where query cost data is collected, analyzed, and used to adjust future query approvals. The compliance module receives feedback about query costs and provider rules, and uses this information to dynamically determine approval status, thereby optimizing resource allocation efficiency while maintaining ease of operation for compliant queries
3Device complexity
If customizable data usage rules are not implemented, then device complexity is reduced, but adaptability to different pricing schemes deteriorates
Solution Approach 1:
The compliance module is designed with multi-functionality, serving multiple purposes: it evaluates query costs, determines approval status, enforces provider rules, and manages pricing schemes. This universal module handles diverse pricing and access control requirements through a single integrated mechanism, thereby achieving adaptability without proportionally increasing system complexity
Solution Approach 2:
The system achieves adaptability to different pricing schemes by changing parameters such as cost thresholds, approval criteria, and provider rules rather than restructuring the entire system. The compliance module adjusts its evaluation parameters based on different pricing models and provider requirements, enabling versatility through parameter configuration rather than complex structural changes
Data Source
AI summary
A database system operates by: determining a query request corresponding to a requesting entity; generating potential query cost data based on query cost data for the query request including power consumption and further based on running query cost data for at least one previous query request corresponding to the requesting entity; generating minimum query cost compliance data for the query request based on determining whether the potential query cost data complies with a minimum query cost rule; when the minimum query cost compliance data indicates the potential query cost data complies with the minimum query cost rule: determining a query result for the query request based on execution of the query request against a database system.