Contextually Irrelevant File Segmentation for Secure Storage
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Solution Overview
Problem
Existing data storage systems face challenges in securely storing and retrieving electronic files, as storing entire databases on a single remote storage device makes them vulnerable to security breaches if compromised.
Innovation Solution
The system segments an electronic file into multiple contextually irrelevant segments, distributing them across multiple remote storage devices. This is achieved through a data splitting engine that iteratively splits the file until each segment's context is unrelated to the original file's context, and a context determining engine that identifies the file's context for segmentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an electronic file is stored on a single remote storage device, then storage simplicity is maintained, but security vulnerability increases
Solution Approach 1:
The patent divides an electronic file into multiple segments and distributes them across multiple remote storage devices. Each segment is contextually irrelevant on its own, meaning it cannot be understood without the other segments. This segmentation approach enhances security because compromising one storage device does not expose the entire file, while still allowing the file to be stored and retrieved through a coordinated system.
2Reliability
If an electronic file is split into multiple segments, then security is enhanced, but system complexity increases
Solution Approach 1:
The patent introduces a context determining engine as an intermediary component that analyzes file segments and determines whether they contain contextually relevant information. This mediator automatically assesses each segment's contextual relevance and guides the segmentation process, reducing the manual complexity of determining how to split files while maintaining security requirements.
Solution Approach 2:
The system employs a feedback mechanism where the context determining engine continuously evaluates segments during the segmentation process. If a segment is found to retain contextual relevance to the original file, the system adjusts the segmentation strategy accordingly. This feedback loop automates the complexity management by using intelligent assessment rather than requiring predetermined segmentation rules.
3Object-affected harmful factors
If contextually irrelevant segments are created, then unauthorized disclosure is prevented, but file retrieval complexity increases
Solution Approach 1:
The patent requires that multiple contextually irrelevant segments be merged or combined to reconstruct the original electronic file. The system maintains metadata or indexing information that guides the merging process, ensuring that segments are properly reassembled in the correct sequence. This merging approach prevents unauthorized disclosure because individual segments remain meaningless, while enabling file retrieval through a coordinated assembly process.
Data Source
AI summary
The present specification describes a computer-implemented method. According to the method, an electronic file to be stored is received and a first context determined for the electronic file. The electronic file is split into multiple segments such that the first context of the electronic file is not discernible from any segment. The multiple segments are then distributed amongst multiple remote storage devices.