Homomorphic Matrix Processing Using Ciphertext Transpose
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Solution Overview
Problem
Existing homomorphic encryption methods for high-dimensional matrix operations, such as ciphertext-ciphertext matrix multiplication (CCMM), require significant resources and lead to prolonged processing times due to the need for extensive computations.
Innovation Solution
An electronic apparatus and method that performs operations on plaintext matrices using a ciphertext matrix transpose (CMT) algorithm to transform row-based data into column-based data, allowing for efficient plaintext-plaintext matrix multiplication (PPMM) instead of costly ciphertext-ciphertext matrix multiplication (CCMM).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ciphertext-ciphertext matrix multiplication (CCMM) is performed on high-dimensional matrices, then secure computation in homomorphic encryption environment is achieved, but processing time and resource consumption increase significantly
Solution Approach 1:
The patent divides the CCMM operation into two distinct phases: a ciphertext phase where matrix multiplication is performed on encrypted data to maintain security, and a plaintext phase where the result is decrypted and further computation is performed. This segmentation allows the system to leverage efficient plaintext operations for the final computation while maintaining security during the encrypted phase.
Solution Approach 2:
The patent introduces a decryption intermediate step as a mediator between ciphertext operations and final plaintext results. By decrypting the ciphertext matrix multiplication result to obtain a plaintext matrix, the system can then perform additional efficient plaintext operations. This intermediary decryption step enables the system to combine the security benefits of homomorphic encryption with the computational efficiency of plaintext operations.
2Reliability
If ciphertext-ciphertext matrix multiplication (CCMM) is performed on high-dimensional matrices, then secure computation in homomorphic encryption environment is achieved, but resource consumption increases significantly
Solution Approach 1:
The patent segments the computation into encrypted-phase operations (which consume resources but maintain security) and plaintext-phase operations (which are more efficient). By performing the final computation in the plaintext phase after decryption, the system reduces overall resource consumption compared to performing all operations in the ciphertext phase.
Solution Approach 2:
The decryption intermediate step acts as a resource optimization mediator. It converts ciphertext data to plaintext, enabling the use of highly optimized plaintext linear algebra libraries and operations that consume significantly fewer resources than homomorphic operations, thereby reducing total resource consumption while maintaining security during the encrypted computation phase.
3Ease of operation
If row-based data is processed using conventional matrix multiplication, then data structure is maintained, but computational efficiency is reduced
Solution Approach 1:
The patent applies the transpose operation to convert row-based data into column-based data. This inversion of the conventional data orientation enables the system to leverage optimized plaintext matrix multiplication algorithms that work more efficiently with column-based representations, thereby improving computational efficiency while maintaining the ability to process the original row-based data structure through the transpose transformation.
Data Source
AI summary
Provided is an electronic apparatus including: at least one processor including processing circuitry; and a memory storing instructions, wherein the at least one processor is configured to obtain an operation command for performing a first multiplication operation on a first ciphertext matrix and a second ciphertext matrix, obtain a third ciphertext matrix by applying a ciphertext matrix transpose (CMT) algorithm to the first ciphertext matrix, and obtain an operation result corresponding to the operation command by performing a second multiplication operation on a plurality of plaintext matrices based on the second ciphertext matrix and the third ciphertext matrix.


