Hierarchical JSON Data Masking Rule Engine
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Solution Overview
Problem
Existing data masking technologies for NoSQL databases, such as those using JSON and BSON formats, lack flexibility and user-friendliness in defining and enforcing masking rules based on the hierarchical structure of data elements, making it difficult to effectively manage sensitive information according to changing privacy requirements.
Innovation Solution
A method and system that uses a hardware processor to receive user input for masking data elements in JSON-type documents, generating masking rules based on document hierarchy, and enforcing these rules by generating and executing scripts, allowing for flexible and context-specific data masking both online and offline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing data masking technologies are used for NoSQL databases, then data masking functionality is provided, but flexibility and user-friendliness in defining masking rules based on hierarchical structure are insufficient
Solution Approach 1:
The patent segments the data masking rule definition into hierarchical levels corresponding to the JSON document structure. Users can define masking rules at different hierarchy levels (root level, object level, array level, field level), allowing flexible and granular control over which data elements are masked based on their position in the document hierarchy, thereby improving both adaptability and ease of operation.
Solution Approach 2:
The patent introduces a hierarchical dimension to data masking rule definition by leveraging the nested structure of JSON documents. Instead of treating all data elements uniformly, the system enables rule definition along the hierarchical dimension (parent-child relationships, nesting levels), allowing users to apply masking rules contextually based on document structure, which enhances flexibility without sacrificing user-friendliness.
2Reliability
If data masking is enforced on JSON-type documents, then sensitive information is concealed, but the complexity of handling hierarchical document structures increases
Solution Approach 1:
The patent implements self-service by enabling the JSON document structure itself to guide the masking process. The hierarchical structure of the document automatically provides the context needed to apply masking rules, eliminating the need for complex external analysis. The system traverses the document hierarchy and applies rules based on predefined conditions, reducing enforcement complexity while maintaining reliable data protection.
Solution Approach 2:
The patent introduces a masking rule engine as an intermediary between the raw JSON documents and the output. This engine interprets hierarchical masking rules and automatically applies them during document traversal, shielding users from the complexity of implementing masking logic manually while ensuring reliable and consistent data protection across the hierarchical structure.
3Adaptability or versatility
If masking rules are generated based on document hierarchy, then context-specific data masking is achieved, but the time and computational resources required for rule generation increase
Solution Approach 1:
The patent applies preliminary action by pre-defining masking rules at the hierarchical level before actual data processing occurs. Users configure masking rules once based on the expected document hierarchy structure, and these rules are then automatically applied to all matching elements during document traversal. This eliminates the need to generate masking rules dynamically for each document, significantly reducing time consumption while maintaining context-specific masking capability.
Solution Approach 2:
The patent utilizes parameter changes by allowing masking rules to be defined in terms of hierarchical parameters (such as path, nesting level, parent-child relationships) rather than individual data elements. By changing the rule definition from element-specific to parameter-based, the system achieves context-specific masking through pattern matching, which is computationally more efficient and reduces rule generation time.
Data Source
AI summary
A method comprising using at least one hardware processor for: receiving input from a user with respect to masking of a data element in one or more documents of a java script object notation (JSON) type, wherein the input comprises: an identifier of the data element, and one or more constraints for masking the data element based on the hierarchy of the one or more documents of the JSON-type; and generating a masking rule for the one or more documents of the JSON-type based on the input.