Data Lineage Classification for Lower-Cost Sensitive Data Protection
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Solution Overview
Problem
Existing data classification methods face an inverse relationship between classification accuracy and cost, necessitating a balance between the two to effectively apply data protection requirements.
Innovation Solution
A technique that records dependence relationships between data objects in a lineage repository and data classifications in a classification repository, allowing processors to associate and apply appropriate data protection based on these relationships, optimizing classification accuracy while reducing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data classification is performed utilizing a greater number of different classification models, then classification accuracy is improved, but classification cost increases
Solution Approach 1:
The patent applies preliminary action by pre-recording dependence relationships between data objects in a lineage repository before classification jobs are executed. When a data object is classified, its dependent objects automatically inherit the classification without requiring re-analysis, thereby avoiding redundant classification operations and reducing overall classification cost while maintaining accuracy
Solution Approach 2:
The patent uses copying by allowing dependent data objects to inherit classifications from their source objects through the lineage repository. Instead of applying multiple classification models to each dependent object, the system copies the classification results from the source object, significantly reducing classification cost while preserving classification accuracy
2Measurement precision
If data classification is performed utilizing a greater number of different classification models, then classification accuracy is improved, but processor cycles and computational resources increase
Solution Approach 1:
The system performs preliminary classification of source data objects and records the results in the lineage repository before dependent objects are classified. This preliminary action eliminates the need to expend processor cycles on re-classifying dependent objects, as their classifications are automatically determined from the recorded lineage relationships
Solution Approach 2:
The patent copies classification results from source objects to dependent objects through the lineage repository, avoiding the computational expense of applying multiple classification models to each dependent object. This copying mechanism significantly reduces processor cycle usage while maintaining classification accuracy
3Measurement precision
If data classification is performed utilizing a greater number of different classification models, then classification accuracy is improved, but memory use and power consumption increase
Solution Approach 1:
The patent performs preliminary classification and records the results in the lineage repository, storing only the essential classification information rather than maintaining multiple full classification models in memory. This preliminary action reduces memory usage while preserving the ability to accurately classify data objects
Solution Approach 2:
The system copies compact classification identifiers from the lineage repository to dependent objects, rather than storing and processing complete classification model outputs for each object. This copying approach significantly reduces memory requirements while maintaining classification accuracy
Data Source
AI summary
A technique of data classification and data protection includes recording, in a lineage repository, dependence relationships between data objects and recording, in a classification repository, data classifications applicable to data objects. The data classifications each indicate a respective class of sensitive data to which data protection is to be applied. Based on receiving a classification job requesting classification of a first data object, a processor determines whether the lineage repository records a dependence relationship with a second data object. Based on determining that the lineage repository records a dependence relationship with the second data object, the processor associates in the classification repository at least a particular data classification applicable to the second data object with the first data object. The processor applies data protection applicable to the particular data classification to the first data object. In some cases, the processor may order application of classification models based on cost metrics.