Homomorphic Encryption Cloud Device Prediction
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Solution Overview
Problem
Existing encryption technologies, such as RSA, face limitations in performing operations on encrypted data, including statistical analysis, due to large key sizes and slow operation speeds, especially when multiple multiplications are involved, leading to noise accumulation and unreliable decryption values.
Innovation Solution
A method and system for providing a computing device in a cloud environment that processes homomorphic encryption operations, recommending suitable devices based on operation type, number of operations, encryption scheme, and parameters like multiplication depth, speed, accuracy, and rebooting availability, and providing virtual images with installed homomorphic encryption libraries to manage and execute these operations efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If homomorphic encryption is used to perform operations on encrypted data, then data security is improved, but operation speed deteriorates (dozens of times slower than plaintext operations)
Solution Approach 1:
The system performs preliminary actions by predicting computing power requirements before actual homomorphic encryption operations are executed. The computing power prediction module estimates the computational resources needed in advance, allowing the cloud environment to pre-allocate and prepare appropriate computing devices, thereby reducing the actual operation time and mitigating the speed deterioration inherent in homomorphic encryption
Solution Approach 2:
The patent introduces an intermediary management system between the user and the homomorphic encryption operations. This management tool includes a computing power prediction module that acts as a mediator, translating user requirements into appropriate computing device selections. The intermediary optimizes resource allocation and manages the complexity of homomorphic encryption operations, improving overall system efficiency without compromising data security
2Productivity
If the number of multiplications is increased to perform deeper operations, then computational capability is improved, but ciphertext size and key size increase
Solution Approach 1:
The system dynamically adjusts computing device allocation based on the depth of multiplications required. The computing power prediction module evaluates the computational depth needed for specific operations and dynamically selects or configures computing devices with appropriate resources. This dynamic approach allows the system to handle deeper computational operations while optimizing resource usage and managing ciphertext and key size growth effectively
Solution Approach 2:
The patent applies parameter changes by adjusting computing device configurations based on operation requirements. The management tool modifies parameters such as computing power allocation, device selection, and resource distribution according to the specific depth and complexity of homomorphic encryption operations. This allows the system to adapt to varying computational demands while managing the trade-off between computational capability and resource consumption
3Productivity
If cloud resources are allocated for homomorphic encryption operations, then processing capability is improved, but resource and cost efficiency deteriorate due to unpredictable computing power requirements
Solution Approach 1:
The system implements feedback mechanisms through the computing power prediction module, which continuously monitors and predicts the computing power requirements for homomorphic encryption operations. Based on this feedback, the management tool optimizes cloud resource allocation, adjusting resource distribution to match actual需求的. This feedback-driven approach improves processing capability while enhancing resource and cost efficiency by avoiding both over-provisioning and under-provisioning of cloud resources
Data Source
AI summary
A method and a system provide a computing device for each computing power based on prediction of computing power required for fully homomorphic encryption in a cloud environment. A computing device providing method may be performed by a computer device including at least one processor. The computer device may implement at least one node included in the cloud environment. The computing device providing method may include providing, to a client device, a management tool including an application function of a computing device that processes a homomorphic encryption operation, and recommending the computing device for processing of the homomorphic encryption operation requested through the management tool.