Homomorphic Encryption Optimized Encoding
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Solution Overview
Problem
Existing homomorphic encryption schemes face challenges in processing speed and storage requirements, particularly in fully homomorphic encryption, which can be several orders of magnitude slower than non-homomorphic evaluations and require substantial storage and computational resources, making them impractical for widespread use.
Innovation Solution
The implementation of optimized encoding techniques and parameter selection using an error growth simulator to improve processing speed and reduce memory requirements, allowing for secure computations on encrypted data without the need for decryption, by encoding fractional parts of real numbers and using balanced odd bases and slot encoding, thereby reducing computational overhead and storage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fully homomorphic encryption is implemented to perform computations on encrypted data, then data confidentiality is improved, but processing speed deteriorates (several orders of magnitude slower than non-homomorphic evaluations)
Solution Approach 1:
The patent applies parameter changes by optimizing encoding parameters (such as base representation, polynomial degree, and noise distribution parameters) to reduce computational overhead. By carefully selecting and tuning these parameters, the system achieves faster homomorphic operations while maintaining security guarantees, directly addressing the speed deterioration issue.
Solution Approach 2:
The patent implements local quality by using different encoding strategies for different parts of the computation. Specifically, it applies optimized encoding for specific operation types (addition vs. multiplication) and uses localized noise management techniques. This allows the system to achieve high performance for specific operations without compromising overall security or requiring full optimization of all computational paths.
2Reliability
If fully homomorphic encryption is implemented to perform computations on encrypted data, then data confidentiality is improved, but storage requirements worsen (substantial storage resources required)
Solution Approach 1:
The patent reduces storage requirements by optimizing encoding parameters such as the degree of polynomials and the base representation. By carefully selecting these parameters, the system minimizes the size of ciphertexts and intermediate computations while maintaining security, directly addressing the substantial storage resource issue.
Solution Approach 2:
The patent extracts and optimizes specific components of the homomorphic encryption system, such as using compact encoding schemes that represent large amounts of information in smaller data structures. This extraction of essential functions with reduced resource requirements directly addresses the storage burden.
3Reliability
If fully homomorphic encryption is implemented to perform computations on encrypted data, then data confidentiality is improved, but computational resources worsen (make them impractical for widespread use)
Solution Approach 1:
The patent applies parameter changes by optimizing encoding parameters (such as base representation, polynomial degree, and noise distribution parameters) to reduce computational overhead. By carefully selecting and tuning these parameters, the system achieves faster homomorphic operations while maintaining security guarantees, directly addressing the speed deterioration issue.
Solution Approach 2:
The patent segments the computational process into distinct phases (encoding, encryption, homomorphic operations, decryption, decoding) and optimizes each phase independently. This segmentation allows for targeted optimizations in each stage, reducing overall computational complexity and making the system more practical for widespread use.
Data Source
AI summary
The techniques and/or systems described herein are directed to improvements in homomorphic encryption to improve processing speed and storage requirements. For example, the techniques and/or systems can be used on a client device to encode data to be sent to a remote server, to be operated on while maintaining confidentiality of data. For example, data including a real number can be encoded as a polynomial, with the fractional part of the real number encoded as high-order coefficients in the polynomial. Further, real numbers can be approximated and encoded in a polynomial using a fractional base, and/or the encoding can include slot encoding. Thus, the optimized encodings disclosed herein provide an optimized homomorphic encryption scheme.