Homomorphic Compression Pipeline for Secure Low-Bandwidth Data Analysis
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Solution Overview
Problem
Current data storage technologies face challenges in efficiently combining data compression and encryption, leading to increased computational overhead, vulnerabilities, and inefficiencies in handling diverse data types.
Innovation Solution
A system employing fully homomorphic encryption and multi-stage compression techniques, utilizing adaptive neural networks for enhancing lossy compressed data, maintains encryption throughout processing, and supports recursive encryption layers for secure data transmission and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional compression algorithms are applied to reduce data size, then data storage efficiency is improved, but security is not provided and data structure information may be leaked
Solution Approach 1:
The patent combines compression and encryption into a unified homomorphic encryption system that performs both functions simultaneously. The system encrypts data in a compressed form by integrating the compression algorithm structure into the encryption scheme, allowing data to be both compact and secure without requiring separate compression and encryption passes.
Solution Approach 2:
The homomorphic encryption system provides multiple functions including compression, encryption, and secure computation capabilities in a single framework. The system can perform arithmetic operations on encrypted compressed data without decryption, making it universally applicable to various data types and computational needs while maintaining both size efficiency and security.
2Reliability
If data is first compressed and then encrypted in two separate passes, then both compression and encryption are achieved, but computational overhead and processing time increase
Solution Approach 1:
The patent merges compression and encryption into a single homomorphic encryption process that operates in one pass. The encryption scheme is designed to inherently compress data while providing security, eliminating the need for sequential compression-then-encryption processing and reducing overall computational overhead.
Solution Approach 2:
The system performs compression as a preliminary action within the encryption process itself rather than as a separate preceding step. The homomorphic encryption scheme is constructed to automatically compress data during the encryption operation, so compression is built into the encryption workflow rather than being an independent preparatory stage.
3Quantity of substance
If compression algorithms analyze data for patterns and redundancies, then data size is reduced, but information about data structure may be leaked that could be exploited in cryptographic attacks
Solution Approach 1:
The patent inverts the traditional approach by encrypting data in its compressed form rather than compressing already-encrypted data. The homomorphic encryption system compresses data while maintaining cryptographic security, ensuring that pattern analysis occurs on encrypted data structures rather than plaintext, thereby preventing information leakage that could aid cryptographic attacks.
Solution Approach 2:
The homomorphic encryption scheme acts as an intermediary that allows compression operations to be performed on encrypted data without exposing the underlying data structure. The system enables pattern recognition and compression on ciphertext, preventing direct analysis of plaintext patterns while still achieving compression through the encrypted representation.
4Quantity of substance
If multiple compression stages are applied to achieve higher compression ratios, then data size is further reduced, but device complexity and processing requirements increase
Solution Approach 1:
The patent integrates multiple compression stages into a unified homomorphic encryption framework rather than applying separate compression algorithms in sequence. The system achieves high compression ratios through a single multi-stage homomorphic encryption process that combines compression operations, reducing the need for multiple independent compression systems and simplifying the overall architecture.
Solution Approach 2:
The homomorphic encryption system employs nested compression stages where inner compression operations are embedded within outer encryption layers. The multi-stage compression is structured as nested transformations within the encryption scheme, allowing complex compression to be achieved through layered operations that maintain a unified system structure rather than requiring separate independent systems.
Data Source
AI summary
A multi-stage process for homomorphic end-to-end data compression and encryption is claimed. The first stage analyzes input data, applies transformations to increase compressibility and security, produces conditioned data and error streams, transforms data into a dyadic distribution, creates a transformation matrix, performs Huffman coding, and combines Huffman-encoded data with a secondary transformation stream. A second stage further processes the compressed and encrypted output, either repeating the first stage's steps or using an autoencoder for additional compression. The system supports multiple compression stages, each building on the previous one. Decompression reverses these stages while maintaining homomorphic encryption throughout. This approach enables secure data transmission, storage, and analysis in bandwidth-constrained environments, adapting to various data types and compression levels while preserving data quality and security.