Hybrid Homomorphic Encryption System for Secure Data Processing
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Solution Overview
Problem
Current encryption methods, such as Homomorphic Encryption (HE), are inefficient for performing complex computations on large amounts of data due to slow processing speeds and high computational burdens, especially when non-linear operations are involved, making them impractical for real-world applications involving secret data sharing and collaboration.
Innovation Solution
A hybrid approach that splits computations into linear and non-linear subsets, where linear computations are performed using Homomorphic Encryption in an encrypted domain and non-linear computations are executed in a trusted hardware domain, with results merged to achieve equivalent outcomes without exposing the original data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Homomorphic Encryption is used to perform computations on encrypted data, then data security is improved, but processing speed deteriorates
Solution Approach 1:
The patent segments computations into two categories: linear computations performed using Homomorphic Encryption on encrypted data, and non-linear computations performed using trusted hardware. This segmentation allows the system to maintain security for linear operations while accelerating non-linear operations, thereby resolving the contradiction between security and speed.
2Reliability
If Homomorphic Encryption is used for complex computations on large amounts of data, then data privacy is improved, but computational burden increases
Solution Approach 1:
The patent divides the computational workload into linear computations handled by HE (maintaining privacy) and non-linear computations handled by trusted hardware (reducing computational burden). This segmentation resolves the contradiction by distributing complexity across two different computational paradigms.
Solution Approach 2:
The patent introduces trusted hardware as an intermediary component that handles non-linear computations. This intermediary relieves the computational burden from the HE system while maintaining an architecture where the untrusted server cannot access plaintext data, thus preserving privacy while reducing complexity.
3Speed
If all computations are performed in trusted hardware, then computation speed is improved, but security requirements and hardware limitations worsen
Solution Approach 1:
The patent segments the computational tasks so that only non-linear operations require trusted hardware execution, while linear operations can be performed in untrusted environments using HE. This reduces the security requirements for the overall system while maintaining speed where needed.
Solution Approach 2:
The patent extracts only the essential non-linear computations from the overall processing pipeline and assigns them to trusted hardware, while leaving linear computations to be handled by the untrusted server via HE. This extraction minimizes the role and security requirements of trusted hardware while preserving computation speed for critical operations.
Data Source
AI summary
A device, system and method for secure collaborations on encrypted data in a hybrid environment of a homomorphic encryption (HE) enabled device and trusted hardware. A set of computations may be divided into a subset of linear computations and a subset of non-linear computations. The linear computations on the encrypted data may be executed using homomorphic encryption (HE) in the homomorphic encryption (HE) enabled device. The non-linear computations on the unencrypted data may be executed in the trusted hardware in an unencrypted domain and encrypting the result. The results of the linear and non-linear computations may be decrypted and merged to generate a result equivalent to executing the set of linear and non-linear computations on the unencrypted data.