Data Removal via Non-Informational Transformation
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Solution Overview
Problem
Existing data storage security methods, such as encryption and password protection, are vulnerable to attacks and hinder data management, as they require frequent updates and do not guarantee security, especially in offline attacks.
Innovation Solution
The approach involves generating non-informational data from informational data using a first function, moving it to an unrestricted domain, and managing storage in an information-restricted domain, allowing for reversible removal and regeneration of information using an inverse function, reducing the need for cumbersome security measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If encryption and password protection are used to secure data, then data security is improved, but data management complexity increases and ease of use deteriorates
Solution Approach 1:
The patent extracts the informational data from the stored data by applying a first function to generate non-informational data. This separates the sensitive information component from the storage medium, allowing the storage system to operate without handling actual information, thus improving ease of management while maintaining security through the reversible transformation process.
Solution Approach 2:
The patent introduces non-informational data as an intermediary between the original informational data and the storage system. This intermediary form allows data to be stored and managed without exposing actual information, while the inverse function can regenerate the information when needed, resolving the contradiction between security and ease of management.
2Reliability
If security features are implemented to protect data, then data protection is improved, but device complexity increases
Solution Approach 1:
By extracting and removing informational data from the storage system through the first function, the patent simplifies the storage system's operational complexity. The system manages non-informational data instead, which requires fewer security measures and simpler management procedures, while still providing protection through the reversible transformation mechanism.
Solution Approach 2:
The patent changes the fundamental parameter of data representation from informational to non-informational form. This parameter change fundamentally simplifies the system architecture and security requirements, as non-informational data does not require the same level of protection and management as actual information, thereby reducing device complexity.
3Reliability
If traditional security methods are used, then data security is improved, but vulnerability to attacks increases due to frequent updates and offline attacks
Solution Approach 1:
The patent extracts and removes actual informational data from the storage system, replacing it with non-informational data. This eliminates the vulnerability to offline attacks and data theft, as the stored data contains no meaningful information that can be stolen or exploited, while security is maintained through the reversible transformation functions.
Solution Approach 2:
The patent converts the potential harm of data theft into a benefit by transforming information into non-informational form for storage. The first function creates a secure representation that cannot be stolen or exploited, while the inverse function ensures the information can be regenerated when needed, turning the storage challenge into a security advantage.
Data Source
AI summary
Non-informational data D is generated as an output using a non-informational data E and informational data as inputs to a function on a computing device in an information-restricted domain. The function may be an XOR and the non-informational data E may be a pseudorandom string of the same length as the informational data. The non-informational data D is moved to an unrestricted domain where it may be managed normally. When the informational data is needed it can be re-generated using the non-informational data D and non-informational data E as inputs to an inverse function (XOR is its own inverse). The non-informational data E may be generated from a smaller random seed.