Dyadic Data Compression and Encryption for Adaptive Codebook Sync
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The rapid growth of data storage demand outstrips the capacity to store it, and existing methods like data compression and physical storage expansion are inadequate, while transmission bandwidth and data security are becoming bottlenecks, especially with the advent of quantum computing.
Innovation Solution
A system and method for data storage, transfer, and security using automated model monitoring and training with a load-adaptive cache, incorporating a dyadic distribution-based algorithm for simultaneous compression and encryption, and a codebook training system to adapt to data drift.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is used to increase storage capacity, then storage capacity is improved, but data loss occurs (either through lossless compression limiting retention or lossy compression degrading data)
Solution Approach 1:
The patent extracts only the essential features and characteristics of data into a compact representation model, storing the compressed data structure rather than the complete original data. This allows significant storage capacity improvement while preserving the core information needed for data reconstruction, effectively separating the data's essential properties from its full representation.
Solution Approach 2:
The patent changes the parameter representation of data by transforming it into a different format or model that occupies less space. By altering how data is represented (e.g., using statistical parameters, feature vectors, or compressed structures instead of raw data), the system achieves higher storage capacity while maintaining the ability to retrieve essential information.
2Reliability
If traditional encryption methods are used for data security, then security is improved, but they become vulnerable to quantum computing attacks
Solution Approach 1:
The patent implements dynamic encryption key generation and transformation mechanisms that can adapt to different computational environments. The encryption system dynamically adjusts its parameters and algorithms based on the threat model, making it versatile enough to resist both classical and quantum computing attacks while maintaining strong security.
Solution Approach 2:
The patent changes the cryptographic parameters and algorithms used for encryption to be quantum-resistant. By transitioning from traditional encryption parameters vulnerable to quantum attacks to post-quantum cryptographic parameters and algorithms, the system maintains security reliability while gaining adaptability to quantum computing threats.
3Quantity of substance
If physical storage capacity is increased to meet demand, then storage capacity is improved, but manufacturing capacity cannot keep up with demand
Solution Approach 1:
The patent segments data into compressed representations that occupy significantly less physical space. By dividing and compressing data before storage, the system achieves equivalent or superior storage capacity from the same physical manufacturing capacity, effectively decoupling logical storage capacity from physical manufacturing constraints.
Solution Approach 2:
The patent transitions from storing data in its full dimensional form to storing a compressed representation that captures the essential information in a reduced-dimensional space. This dimensional transformation allows the same physical storage medium to hold effectively more information, overcoming manufacturing capacity limitations.
4Speed
If data transmission bandwidth is increased to handle large datasets, then transmission speed is improved, but bandwidth becomes a bottleneck
Solution Approach 1:
The patent extracts the essential information from large datasets into a compressed form before transmission. By sending only the compressed representation rather than the complete dataset, the system achieves faster effective transmission speeds while reducing the bandwidth requirements and avoiding the bottleneck problem.
Solution Approach 2:
The patent transmits a partial representation of the data (the compressed essence) rather than the complete dataset. This partial transmission action is sufficient for most purposes and achieves the desired transmission speed improvement while dramatically reducing bandwidth requirements.
Data Source
AI summary
A system and method for efficient data storage, transfer, synchronization, and security using automated model monitoring and training. The system analyzes test datasets to detect data drift, retraining encoding and decoding algorithms as needed. New data sourceblocks are created and assigned codewords, compiling an updated codebook for distribution to connected devices. A novel dyadic distribution subsystem simultaneously compresses and encrypts data by transforming input streams into a dyadic distribution. This process generates a compressed main data stream and a secondary stream of transformation information, which are combined into a secure output. The system includes a network device manager for optimizing codebook distribution based on device resource usage. Operating in both lossless and lossy modes, the system offers flexible, efficient, and secure data handling across various network configurations.