Database Masking via Internal Redo Records
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Solution Overview
Problem
Conventional data masking methods for databases require external tools, leading to inefficient and frequent processing of entire datasets, resulting in outdated masked data and increased computational costs, as well as disruptions to normal database operations.
Innovation Solution
The database infrastructure generates masked data using its internal mechanisms, leveraging disaster recovery infrastructure to create a masked database by applying masked redo records, allowing for continuous data masking without external tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If external tools are used to generate masked data by exporting and processing the entire production dataset, then data masking can be achieved, but computational costs increase and data becomes outdated quickly
Solution Approach 1:
The patent segments the data masking process into two parts: (1) initial full dataset masking using external tools, and (2) incremental updates using internal database mechanisms. This segmentation allows the system to avoid repeatedly processing the entire dataset while maintaining data freshness through continuous incremental masking of changes.
Solution Approach 2:
The patent applies preliminary action by performing the computationally expensive full dataset masking once before production use, then prepares the database for incremental updates by enabling triggers and logging mechanisms in advance. This preliminary setup allows subsequent incremental masking to occur efficiently without repeated full-processing costs.
2Reliability
If the masking process is performed frequently to maintain data freshness, then data accuracy improves, but database operations are disrupted and system latency increases
Solution Approach 1:
The patent implements continuity of useful action by establishing continuous incremental masking through database triggers and logging mechanisms that automatically mask new data changes as they occur. This continuous process maintains data accuracy without requiring periodic interruptions for batch processing, allowing the database to handle normal operations continuously.
Solution Approach 2:
The database system performs self-service masking by using its own internal triggers, logs, and replication mechanisms to automatically mask incoming data changes. This eliminates the need for external tools to continuously intervene, reducing disruptions and allowing the database to serve its primary function while autonomously maintaining masked data integrity.
3Ease of manufacture
If the production database is shut down or placed in holding state for masking, then complete data export can be performed, but normal database operations are interrupted
Solution Approach 1:
The patent applies dynamics by transitioning the masking approach from static batch processing (requiring database shutdown) to dynamic incremental processing. The system dynamically adapts to ongoing database operations by using triggers and logs to capture and mask changes in real-time, allowing the database to remain operational while masking is performed continuously in the background.
Data Source
AI summary
Disclosed is a system, method, and computer program product that generates masked data from within a database infrastructure. Instead of requiring an external tool to generate masked data, a database generates masked data using its internal processing mechanisms.