Database Segmentation During Storage for Fine-Grained Access Control
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Solution Overview
Problem
Conventional data storage techniques in databases are inefficient and time-consuming, requiring manual sorting and extensive processing to define data access privileges after data is stored, leading to delayed utilization and exposure of crucial information, primarily handled at a table level without columnar or row-level control.
Innovation Solution
Predefine data access privilege grants using a trained AI model before data storage, segmenting data accordingly and storing metadata with the segments to enable column and row-level access control, allowing organizations to correlate roles with the database structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual sorting and extensive processing are performed to define data access privileges after data is stored, then data access control can be implemented, but the process becomes inefficient and time-consuming
Solution Approach 1:
The patent applies preliminary action by defining data access privilege grants and segmenting data according to these grants during the data storage process itself, rather than performing manual sorting and access control setup after data is stored. This preliminary segmentation and metadata assignment eliminates subsequent manual processing steps, resolving the contradiction between implementing reliable access control and maintaining storage efficiency.
2Reliability
If data access privileges are defined after data storage, then access control can be established, but data utilization is delayed
Solution Approach 1:
The patent performs the preliminary action of segmenting data and assigning metadata with access privilege grants during the data storage operation. This eliminates the time delay associated with post-storage access control setup, allowing data utilization to proceed immediately with pre-established access controls already in place.
3Ease of operation
If data is stored without pre-segmentation, then storage simplicity is maintained, but columnar or row-level access control is not achieved
Solution Approach 1:
The patent applies segmentation by dividing data into segments during storage based on pre-defined access privilege grants, with metadata stored alongside each segment. This segmentation enables fine-grained columnar or row-level access control while maintaining storage simplicity through automated processing, resolving the contradiction between operational ease and access control versatility.
4Reliability
If extensive manual processing is performed for data access control, then comprehensive security can be achieved, but human intervention increases
Solution Approach 1:
The patent performs preliminary segmentation and metadata assignment automatically during data storage, eliminating the need for extensive manual processing later. This automated preliminary action maintains comprehensive security while significantly reducing human intervention, resolving the contradiction between security comprehensiveness and automation extent.
Data Source
AI summary
A computer-implemented method, according to one embodiment, includes causing a trained artificial intelligence (AI) model to derive data access privilege grants before data is stored in a predetermined database, and segmenting the data according to the data access privilege grants during storage of the data in the predetermined database. Metadata that defines the data access privilege grants is stored with the segments of data. The method further includes receiving, from a first user device, a query requesting data stored in the predetermined database. At least some of the metadata is read to identify a segment of the data associated with a data access privilege grant associated with the query. The method further includes allowing the first user device to access the identified segment of data for fulfilling the query.