Data Field Mapping and Anonymization for Database Maintenance
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Solution Overview
Problem
Existing database maintenance practices face challenges in masking and verifying the confidentiality of sensitive business data stored across multiple tables, as current methods are arduous and inconvenient, especially when dealing with complex data structures and large volumes of business data.
Innovation Solution
A data management system that includes data mapping and anonymization applications to identify and link related data fields across multiple tables, allowing for the execution of anonymization logic to protect sensitive information by encrypting, masking, or camouflaging data using algorithms, ensuring confidentiality and convenience in database maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blanking queries are executed on multiple tables to mask confidential information, then data confidentiality is improved, but the complexity and inconvenience of database maintenance increases
Solution Approach 1:
The patent introduces a data masking service as an intermediary component that sits between the database and users. This service automatically masks confidential information in query results without requiring manual blanking queries on multiple tables. The masking service receives query requests, executes them, and then applies appropriate masking rules to the results before returning them, thereby maintaining data confidentiality while simplifying database maintenance operations.
Solution Approach 2:
The system implements self-service data masking through automatic detection and application of masking rules. The data masking service automatically identifies confidential data fields, determines appropriate masking strategies based on data classification, and applies masking without requiring manual intervention for each query. This self-service approach eliminates the need for arduous manual blanking queries while ensuring consistent data confidentiality protection.
2Reliability
If manual masking of confidential information is performed across multiple tables, then data protection is improved, but the time and effort required for database maintenance increases
Solution Approach 1:
The patent implements preliminary action by pre-classifying data fields as confidential or non-confidential and pre-defining masking rules for different data types. The data masking service is configured in advance with masking strategies for various confidential information types (e.g., personal identifiers, financial data). When queries are executed, the service automatically applies these pre-configured rules without requiring real-time manual masking decisions, thereby reducing database maintenance time while maintaining data protection.
Solution Approach 2:
The system performs self-service masking by automatically detecting confidential data in query results and applying appropriate masking rules without manual intervention. The data masking service continuously monitors query outputs and applies masking transformations based on pre-configured rules, eliminating the need for manual masking operations across multiple tables and significantly reducing the time required for data protection maintenance.
3Ease of manufacture
If data is stored in various tables across the database, then data organization is improved, but the difficulty of verifying masked confidential information increases
Solution Approach 1:
The patent implements feedback mechanisms through the data masking service that provides visibility into masking operations. The service logs which data fields are masked, applies which masking rules, and maintains audit trails of masking operations. This feedback system allows database administrators to verify that confidential information is properly masked across multiple tables without manually checking each table, as the service provides centralized verification capabilities and reporting on masking effectiveness.
Data Source
AI summary
To establish a link between data fields related by similar data or similar information, a data management application parses data fields of data structures residing in a data store. The attributes and attribute values corresponding to the data fields are determined. The attributes and attribute values are compared and related data fields are determined. A parent data field from the related data fields is determined. A link is established between the parent data field and the data fields from the related data fields.