Recoverable Secure Data Streams Using Generator Matrix Encoding
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Solution Overview
Problem
Existing systems for handling and processing plaintext data lack effective redundancy mechanisms for data recovery and protection, often exposing data to unauthorized access and failing to utilize redundant streams for recovery purposes.
Innovation Solution
The method involves transforming input data using Galois field operations and a generator matrix to create multiple output data streams, allowing for recovery of the original data from any subset of the streams, thereby providing redundancy and protecting the plaintext from unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If plaintext data is stored and processed in readily accessible format, then ease of operation is improved, but security is worsened due to exposure to unauthorized access
Solution Approach 1:
The patent segments plaintext data into multiple data streams using encoding techniques. The original data is divided into W data inputs that are transformed into H output data streams, where no single stream contains the complete plaintext. This segmentation allows the system to maintain data accessibility through distributed storage while preventing unauthorized access, as compromising one stream does not reveal the original data.
Solution Approach 2:
The patent introduces encoded data streams as intermediaries between the original plaintext and storage/transmission media. These intermediary streams contain transformed data that cannot be directly interpreted as the original plaintext, thereby protecting against unauthorized access while still enabling recovery of the original data when sufficient streams are combined through the decoding process.
2Reliability
If data is divided into smaller portions for storage and transmission, then loss resistance is improved, but data recovery capability is worsened when loss occurs
Solution Approach 1:
The patent applies preliminary encoding actions to the data before storage or transmission. By pre-processing the plaintext into W data inputs and transforming them into H output data streams with built-in redundancy, the system prepares the data to withstand potential loss. This preliminary transformation ensures that even if some streams are lost, the original data can be recovered from the remaining streams.
Solution Approach 2:
The patent changes the parameters of the data representation by transforming plaintext into encoded streams using mathematical transformations. The encoding process modifies the data parameters to create redundant representations, where H output streams are generated from W input streams. This parameter transformation enables the system to tolerate loss of up to H-W streams while maintaining full data recovery capability.
3Reliability
If redundant data streams are created for recovery purposes, then reliability is improved, but device complexity is worsened
Solution Approach 1:
The patent creates a universal encoding framework that can handle various data types and recovery scenarios through a single transformation process. The encoding mechanism using W data inputs and H output streams serves multiple functions: data protection, loss resistance, and recovery capability. This multi-functional approach reduces overall system complexity by consolidating multiple protective measures into a unified transformation framework.
Data Source
AI summary
Systems and methods are disclosed for processing data. In one exemplary implementation, there is provided a method of generating H output data from W data input streams produced from input data. Moreover, the method may include generating the H discrete output data components via application of the W data inputs to one or more transforming components or processes having specified mathematic operations and/or a generator matrix functionality, wherein the W data inputs are recoverable via a recovery process capable of reproducing the W data inputs from a subset (any W members) of the H output data streams.