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Homomorphic encryption matrix continuous multiplication safety outsourcing method based on cloud computing

A technology of homomorphic encryption and security outsourcing, which is applied in the fields of homomorphic encryption communication, secure communication device, complex mathematical operation, etc., can solve the problem of low computing efficiency of matrix connection and multiplication security outsourcing, and reduce the number of ciphertext operations and circuit Deep, Efficient Effects

Active Publication Date: 2020-04-24
ZHEJIANG SCI-TECH UNIV
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AI Technical Summary

Problems solved by technology

The present invention proposes an improvement method for the problem of low efficiency of matrix multiplication security outsourcing calculation under fully homomorphic encryption technology

Method used

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  • Homomorphic encryption matrix continuous multiplication safety outsourcing method based on cloud computing
  • Homomorphic encryption matrix continuous multiplication safety outsourcing method based on cloud computing
  • Homomorphic encryption matrix continuous multiplication safety outsourcing method based on cloud computing

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Embodiment Construction

[0026] In order to make the features and advantages of the present invention more obvious, the present invention will be described in detail and completely below in conjunction with the accompanying drawings.

[0027] figure 1 It is a flowchart of the security outsourcing method of the present invention, and the method specifically includes the following steps:

[0028] (1) With the increasing popularity of cloud computing, people outsource a large number of computing tasks to cloud service providers. The client collects the matrix data A that needs to be kept confidential in the industry i , such as medical data, traffic flow data, private picture data, financial data, etc., and the collected m matrix data A 1 ,A 2 ...A m A matrix set is formed, where matrix A is a square matrix of order n, and n is a positive integer; i∈{1,2,...,m} indicates the position of the matrix set where the matrix is ​​located.

[0029] (2) Each matrix data A in step (1) i Encode and encrypt re...

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Abstract

The invention discloses a homomorphic encryption matrix continuous multiplication safety outsourcing method based on cloud computing, and belongs to the technical field of homomorphic encryption. Themethod comprises the following steps that: encryption is performed at a client, encoding and encrypting is carried out on a matrix and the matrix is uploaded to a cloud server; the cloud server executes homomorphic calculation, carries out ciphertext matrix continuous multiplication operation under the condition that decryption is not carried out, and returns a calculation result to the client side in a ciphertext form; and finally, the client executes a decryption module to obtain a value of matrix continuous multiplication. The matrix continuous multiplication calculation task can be outsourced to the cloud server under the condition that matrix elements, namely client private data, are not leaked, so that the security of client data is protected, and the calculation amount of the clientis reduced. The matrix is encoded into a ciphertext for operation, so that the space complexity is remarkably reduced, the ciphertext operation frequency is reduced, and the purpose of improving theefficiency is achieved.

Description

technical field [0001] The invention belongs to the technical field of homomorphic encryption, and in particular relates to a cloud computing-based safe outsourcing method for matrix multiplication of homomorphic encryption. Background technique [0002] Matrix calculation is a basic scientific computing problem, which has a wide range of applications in many fields, such as data analysis and decision-making, scientific computing, machine learning and image processing. Therefore, improving the efficiency of matrix secure outsourcing computing is of great significance to the performance optimization of secure outsourcing computing for many high-level problems. For example, the training and prediction process of convolutional neural network, the most classic model in deep learning, can be expressed as a series of matrix operations. Improving the efficiency of matrix security outsourcing computing will greatly improve the efficiency of deep learning security outsourcing computi...

Claims

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Application Information

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IPC IPC(8): H04L9/00H04L29/08G06F17/16
CPCH04L9/008H04L67/10G06F17/16
Inventor 黄海王淑芳
Owner ZHEJIANG SCI-TECH UNIV
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