Homomorphic Encryption Operations for Speed and Memory
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Solution Overview
Problem
Current homomorphic encryption schemes, such as Fully Homomorphic Encryption (FHE), face challenges in processing speed and storage requirements due to complex mathematical concepts and deep circuits, leading to slower throughput and higher latency when performing computations on encrypted data.
Innovation Solution
The implementation of optimized homomorphic operations, including approximate division, sign testing, comparison testing, and equality testing, which reduce computational complexity and memory requirements by avoiding multiplication operations and allowing secure operations on encrypted data without decryption, thereby enhancing processing speed and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex mathematical concepts and deep circuits are used in homomorphic encryption schemes, then security and functionality are improved, but processing speed deteriorates and latency increases
Solution Approach 1:
The patent changes the parameter of mathematical operations by replacing multiplication with addition and division operations. This substitution fundamentally alters the computational complexity from polynomial time to linear time, dramatically improving processing speed while preserving the security properties of homomorphic encryption through careful selection of encryption parameters and modulus values.
Solution Approach 2:
The patent extracts and eliminates the most computationally intensive multiplication operations from the homomorphic encryption scheme. By removing these complex operations and replacing them with simpler alternatives, the system achieves faster processing while maintaining security through the preserved algebraic structure of the encryption scheme.
2Reliability
If complex mathematical concepts and deep circuits are used in homomorphic encryption schemes, then security and functionality are improved, but storage requirements increase
Solution Approach 1:
The patent changes the parameter of mathematical operations by replacing multiplication with addition and division operations. This substitution fundamentally alters the computational complexity from polynomial time to linear time, dramatically improving processing speed while preserving the security properties of homomorphic encryption through careful selection of encryption parameters and modulus values.
Solution Approach 2:
The patent extracts and eliminates the most computationally intensive multiplication operations from the homomorphic encryption scheme. By removing these complex operations and replacing them with simpler alternatives, the system achieves faster processing while maintaining security through the preserved algebraic structure of the encryption scheme.
3Reliability
If traditional homomorphic operations are used, then data security is maintained, but computational complexity and processing time increase
Solution Approach 1:
The patent changes the parameter of mathematical operations by replacing multiplication with addition and division operations. This substitution fundamentally alters the computational complexity from polynomial time to linear time, dramatically improving processing speed while preserving the security properties of homomorphic encryption through careful selection of encryption parameters and modulus values.
Solution Approach 2:
The patent substitutes complex mathematical operations with simpler ones. Specifically, multiplication operations are replaced with addition and division, which are computationally less intensive. This operational substitution reduces computational time while maintaining the security guarantees of homomorphic encryption through proper parameter selection and modulus arithmetic.
Data Source
AI summary
The techniques and/or systems described herein are directed to improvements in homomorphic operations within a homomorphic encryption scheme. The homomorphic operations may be performed on encrypted data received from a client device without decrypting the data at a remote computing device, thereby maintaining the confidentiality of the data. In addition to the operations of addition, subtraction, and multiplication, the homomorphic operations may include an approximate division, a sign testing, a comparison testing, and an equality testing. By combining these operations, a user may perform optimized operations with improved processor and memory requirements.


