Database Result Set Sensitivity Determination
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Solution Overview
Problem
Database systems face challenges in efficiently determining and providing result set sensitivity information, especially when data is sourced from disparate data sources with varying sensitivity levels, which hinders secure processing and transmission of results.
Innovation Solution
The system identifies table columns underlying a query result set by analyzing the query and database schema, determines sensitivity information using metadata, and contemporaneously provides result set sensitivity information within the result set metadata to the client application, allowing for real-time security measures and data protection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the database system determines sensitivity information for each data source individually, then the sensitivity determination is thorough and accurate, but the processing time and system complexity increase significantly
Solution Approach 1:
The system pre-determines and stores sensitivity information for each data source in metadata before queries are executed. When a query is processed, the database system retrieves pre-stored sensitivity information rather than determining it in real-time, significantly reducing processing time while maintaining accurate sensitivity determination
Solution Approach 2:
The system divides the sensitivity determination process into separate components: individual data source sensitivity assessment, result set generation, and sensitivity information aggregation. Each data source's sensitivity is determined independently and stored separately, allowing parallel processing and efficient retrieval during query execution
2Reliability
If the database system provides detailed sensitivity information for all data sources, then downstream applications can make informed security decisions, but the amount of metadata transmitted and processed increases
Solution Approach 1:
The system attaches sensitivity information specifically to the result set and relevant data columns rather than providing universal sensitivity metadata for all data sources. This localized approach ensures downstream applications receive only the sensitivity information necessary for making security decisions about the actual query results, reducing unnecessary metadata transmission
Solution Approach 2:
The system extracts and provides only the essential sensitivity information needed for security decisions—specifically, the sensitivity level of the result set and affected columns—rather than transmitting complete sensitivity profiles of all underlying data sources. This extraction focuses metadata on what is actually needed for security processing
3Reliability
If the system processes sensitivity information for every query result set, then data protection is comprehensive, but the computational overhead and processing complexity increase
Solution Approach 1:
The database system automatically determines and attaches sensitivity information to result sets without requiring external intervention or complex manual processing. The system uses pre-stored metadata and automated aggregation logic to handle sensitivity processing, reducing operational complexity while maintaining comprehensive data protection
Solution Approach 2:
The system combines sensitivity determination with the existing query execution and result set generation processes. Instead of treating sensitivity processing as a separate complex workflow, it integrates sensitivity metadata attachment into the standard data retrieval operations, reducing overall system complexity while ensuring comprehensive protection
Data Source
AI summary
A system includes reception of a database query, determination of result set output columns associated with the database query, and determination, for each of the determined result set output columns, of one or more data sources associated with the result set output column. Sensitivity information is determined for each of the one or more data sources based on metadata, and result set sensitivity information is determined based on the determined sensitivity information. A result set is determined based on the database query, and the result set and the result set sensitivity information are transmitted.