Information Processing Method for Confidential Data Leakage Suppression
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Solution Overview
Problem
Existing information processing methods fail to effectively suppress the leakage of confidential information by accurately specifying deletion portions in processed data, allowing original data to be easily estimated from the processed data.
Innovation Solution
An information processing method that generates processed data by adding a predetermined data value to non-analysis target regions and deleting data values in analysis target regions, using a processing pattern to maintain the shape of the analysis target region and performing coordinate replacement to obscure original data relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data values are deleted from the original data to suppress confidential information leakage, then information security is improved, but the ability to accurately specify deletion portions is lost making it easy to estimate original data
Solution Approach 1:
The patent segments the original data into multiple data strings and divides deletion operations across different segments. By deleting data at different positions in different data strings rather than from a single continuous string, the deletion pattern becomes harder to reconstruct, preventing easy estimation of the original data while maintaining security.
Solution Approach 2:
The patent introduces a new dimension to the data structure by arranging data values in a two-dimensional matrix format with multiple data strings. Deletion operations are applied across this extended dimension, making it significantly more difficult to reconstruct the original data compared to simple linear deletion, thus improving information security while preserving useful analysis capabilities.
2Reliability
If data is processed to suppress confidential leakage by deleting portions, then information security is improved, but analysis accuracy deteriorates due to loss of original data characteristics
Solution Approach 1:
The patent applies different processing treatments to different regions of the data. Critical confidential portions are deleted or obscured, while other regions maintain their original characteristics for analysis purposes. This localized differential treatment preserves analysis accuracy for non-sensitive areas while protecting confidential information.
Solution Approach 2:
The patent modifies specific parameters of the data such as position coordinates and data values in a controlled manner. By changing these parameters strategically, the patent maintains the structural integrity and analytical value of the data while altering sensitive characteristics to prevent confidential information leakage.
3Reliability
If deletion processing is performed on original data, then information security is improved, but the processed data structure becomes complex making it difficult to maintain analysis target region shape
Solution Approach 1:
The patent performs preliminary organization of data into structured formats with defined analysis target regions before applying deletion operations. By pre-establishing the data structure and identifying analysis regions, the patent can apply deletions in a controlled manner that maintains the overall structural integrity and makes subsequent processing easier.
Solution Approach 2:
The patent creates processed data as a derived copy of the original data rather than directly modifying the original structure. This copying approach allows the patent to maintain the original data structure for analysis while applying security processing to generate a separate processed version, reducing complexity in managing both requirements simultaneously.
Data Source
AI summary
According to an embodiment, an information processing method is executed by a computer. The method includes generating processed data obtained by performing, on original data including a group of a plurality of data values arranged respectively at position coordinates along a predetermined direction on a map, at least one of an addition process of adding a predetermined data value representing an analysis target at position coordinates in a non-analysis target region in the original data and a deletion process of deleting data values of at least part of the position coordinates in the original data, where data values at the at least part match between a plurality of pieces of the original data.