Data Structure Cell Scrambling for Privacy and Analysis
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Solution Overview
Problem
Current data analytics systems face challenges in protecting data privacy while allowing for meaningful data analysis, as encryption can hinder analysis and redacting or restricting access to specific data columns can result in loss of context and valuable information.
Innovation Solution
The system provides a method for scrambling cells of a data structure, rearranging at least a subset of cells such that each cell is located in a different row or column, and determining user access to either the initial or scrambled data structure based on user privilege levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If encryption is used to protect data privacy, then data protection is improved, but data analysis capability deteriorates
Solution Approach 1:
The patent segments the data structure by scrambling only specific cells (subset of data) rather than encrypting the entire dataset. This allows selective protection of sensitive information while preserving analysis capability on non-sensitive data, resolving the contradiction between comprehensive protection and analysis productivity.
Solution Approach 2:
The patent applies different treatment to different parts of the data structure - scrambling is applied locally to specific cells identified as needing protection, while other cells remain accessible. This local quality approach enables privacy protection where needed without hindering overall data analysis.
2Object-affected harmful factors
If redaction or restriction of access to specific data columns is applied, then data privacy is improved, but context and valuable information are lost
Solution Approach 1:
Instead of redacting entire columns or rows, the patent segments and scrambles only specific individual cells within the data structure. This preserves the contextual relationships and structure of the data while protecting only the specific sensitive information contained in those cells.
Solution Approach 2:
The patent introduces a scrambling mechanism as an intermediary between the raw data and user access. This intermediary allows data to be transformed into a protected form that maintains structural integrity and context while preventing direct access to sensitive information, avoiding the information loss associated with redaction.
3Object-affected harmful factors
If conventional encryption methods are used, then data protection is improved, but computing resource usage increases
Solution Approach 1:
The patent applies partial scrambling to only the necessary subset of cells rather than applying encryption to the entire data structure. This partial action reduces computing resource consumption while maintaining adequate protection for sensitive data, resolving the contradiction between protection effectiveness and resource usage.
Data Source
AI summary
A method includes identifying, by a processing device, a data structure including cells to store data, wherein the cells are arranged within rows and columns of the initial data structure. A scrambled data structure is created in which at least a subset of cells of the initial data structure is rearranged such that each cell of the rearranged subset of cells is located in at least one of a different row or a different column of the initial data structure. Responsive to receiving a user request to access the data of the initial data structure, the processing device determines whether to provide the user with access to the initial data structure or the scrambled data structure.