Database Views for PII Masking in Non-Production Testing
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Solution Overview
Problem
Current data masking methods in non-production environments require extensive preparation, store both original and masked data, and operate inefficiently, posing security risks and compliance issues due to direct data duplication and sequential processing.
Innovation Solution
Utilize database views that do not store data but present modified data, identifying and masking personally identifiable information (PII) columns with null or anonymized values, ensuring secure and compliant data access without duplication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If production data is directly duplicated for non-production environments, then data availability for testing is improved, but data security and compliance are worsened
Solution Approach 1:
The patent creates a copy of the production data structure through database views that mirror the schema and data format, enabling testing operations. However, instead of copying sensitive values, the views apply masking transformations to hide PII while preserving data structure and relationships for effective testing.
Solution Approach 2:
Database views serve as an intermediary layer between production data and non-production environments. The views transform and mask sensitive data while allowing read-only access to the underlying data structure, enabling testing without direct exposure of raw production data.
2Reliability
If traditional data masking methods are used, then data privacy is improved, but storage requirements and processing time are worsened
Solution Approach 1:
Instead of creating physical copies of masked data, the patent uses database views that virtually present masked data on-demand. This eliminates the need to store separate masked data copies while still providing privacy protection through view-based masking.
Solution Approach 2:
The database views automatically apply masking transformations when data is accessed, without requiring pre-processing or manual intervention. The masking is performed dynamically at query time, eliminating the need for separate masking infrastructure or storage.
3Manufacturing precision
If sequential snapshot masking is used, then data masking completeness is improved, but processing efficiency and development cycle speed are worsened
Solution Approach 1:
The database views provide continuous, real-time masked data access without requiring sequential batch processing. As soon as data is available in the underlying tables, the views immediately present the masked version, enabling continuous testing operations without waiting for periodic masking cycles.
Solution Approach 2:
The masking approach transitions from static, pre-computed snapshots to dynamic, on-demand masking. The views automatically adapt to current data states and apply masking transformations in real-time, allowing flexible and efficient access to masked data whenever needed.
Data Source
AI summary
An example computer system and method for masking personally identifiable information in a non-production environment is presented. The computer system includes one or more processors and non-transitory computer-readable storage media. The encoded instructions, when executed by the one or more processors, cause the computer system to: identify columns within a database application that contain PII; register these columns in a configuration table; generate database view definitions that include instructions to replace the PII within the columns with either null values or anonymized data, thus creating compliant views; and generate these compliant views within the production environment. The method also involves extracting test data from the compliant views and loading this data into a user acceptance testing object, facilitating secure testing and development while adhering to data protection standards.