NTT Polynomial Processing for Faster Homomorphic Encryption
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Solution Overview
Problem
Existing fully homomorphic encryption technologies face inefficiencies in computing efficiency, particularly in real-time data processing and cloud computing, due to the need for repeated decryption and encryption, which increases time and resource consumption.
Innovation Solution
Implementing a processing system and method that utilizes fast number theoretic transform (NTT) calculations and matrix multiplication to enhance computing efficiency by converting polynomial computations into point computations in the NTT domain, reducing time complexity from O(N^2) to O(NlogN) and enabling efficient homomorphic operations without decryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fully homomorphic encryption methods are used, then data security and privacy protection are improved, but computing efficiency deteriorates due to repeated decryption and encryption operations
Solution Approach 1:
The patent extracts and eliminates the unnecessary decryption-encryption cycles from the homomorphic computation process. By using pre-computed lookup tables and direct polynomial operations, the system performs computations on encrypted data without requiring intermediate decryption steps, thus maintaining security while dramatically improving efficiency
Solution Approach 2:
The patent applies preliminary action by pre-computing and storing lookup tables (such as evaluation polynomials and transformation matrices) before the actual homomorphic computation. This pre-computation phase prepares all necessary transformation data in advance, allowing the main computation to proceed efficiently without repeated decryption-encryption operations
2Reliability
If traditional fully homomorphic encryption methods are used, then encryption functionality is achieved, but time consumption increases due to repeated decryption and encryption
Solution Approach 1:
The patent removes the time-consuming decryption-encryption cycles from the computation workflow. By leveraging the homomorphic properties of polynomial rings and using pre-computed lookup tables, the system performs all necessary operations directly on encrypted polynomials, eliminating unnecessary time-consuming steps while preserving encryption functionality
Solution Approach 2:
The patent uses copying by creating and storing lookup tables that contain pre-computed transformation data. These lookup tables serve as reference copies that can be repeatedly used during homomorphic computations without requiring re-computation, significantly reducing time consumption while maintaining encryption integrity
3Reliability
If traditional fully homomorphic encryption methods are used, then security is maintained, but computing resources consumption increases
Solution Approach 1:
The patent extracts and eliminates resource-intensive decryption-encryption operations from the computation process. By using pre-computed lookup tables and direct polynomial homomorphic operations, the system performs computations with minimal resource consumption while maintaining security through encrypted data processing
Solution Approach 2:
The patent applies preliminary action by pre-computing and caching lookup tables during an initial setup phase. This pre-computation shifts the resource consumption to a one-time setup rather than repeated during actual computations, significantly reducing ongoing computing resource requirements while maintaining security
Data Source
AI summary
A processing system and method related to encryption are provided. The processing system includes multiple computing circuits. A memory stores data. The computing circuit performs a number theoretic transform (NTT) calculation on a polynomial. A matrix multiplication calculation is performed on the polynomial through the NTT calculation. Therefore, the computing efficiency of encryption or decryption can be improved.