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Multi-source data fusion platform based on privacy computing

A multi-source data and privacy technology, applied in the information field, can solve problems such as the lack of efficient privacy computing technology, and achieve the effect of convenient execution and high execution efficiency

Pending Publication Date: 2022-02-15
浙江数秦科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is: the current lack of high-efficiency privacy computing technology

Method used

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  • Multi-source data fusion platform based on privacy computing
  • Multi-source data fusion platform based on privacy computing
  • Multi-source data fusion platform based on privacy computing

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Embodiment Construction

[0024] The specific embodiments of the present invention will be further specifically described below through specific embodiments in conjunction with the accompanying drawings.

[0025] A multi-source data fusion platform based on privacy computing, used for statistics of industry business data, please refer to the attached figure 1 , the platform includes service nodes 10 and fusion nodes 30, there are multiple fusion nodes 30, and multiple fusion nodes 30 have sequential numbers. Please refer to the attached figure 2, the method for performing privacy calculation on this platform includes: step A01) the data source 20 connects to the service node 10, the service node 10 assigns a source identifier, and any data source 20 initiates a privacy calculation task and submits the objective function; step A02) the service The node 10 displays the privacy calculation task, and registers the source identification of the data source 20 to be added to the privacy calculation; Step A0...

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Abstract

The invention relates to the technical field of information, in particular to a multi-source data fusion platform based on privacy computing. The platform comprises a service node and a fusion node, wherein the service node displays a privacy computing task, registers source identifiers of data source parties to be added into privacy computing, and distributes formal variables for privacy numbers of the data source parties related to a target function; the service node establishes a polynomial fitting function of the target function, and expands the polynomial fitting function into the sum of a plurality of product terms; the data source parties split the privacy numbers into a plurality of multipliers and distribute the multipliers to a plurality of data source parties; the data source parties take values of the multipliers as values of the formal variables, calculate a value of each product term as an intermediate value, and send the intermediate values to the fusion node; and the fusion node multiplies the intermediate values of the same subtask number, corrects coefficients of the product terms by using a correction value to obtain values of the product terms, and adds the values of all the product terms to obtain a value of the polynomial fitting function. The invention has the substantive effects that wide privacy computing requirements can be met, and higher execution efficiency is achieved.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a privacy computing-based multi-source data fusion platform. Background technique [0002] The subdivision of industries can improve the utilization rate of resources, improve the quality of final products, and have significant economic and social benefits. With the development of the economy, a large number of industrial structures with fine division of labor and cooperation have emerged in the market. Subdivided industrial structure, there are a large number of market participants. In the process of its production and operation, a large amount of data is generated, mainly production data, operation data and transportation data. Since a large number of collaborative productions are involved, the relevant upstream and downstream data of the participating entities have an important impact on the production and operation of the participating entities themselves. Moreover, t...

Claims

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Application Information

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IPC IPC(8): G06F21/71G06F7/523
CPCG06F21/71G06F7/523
Inventor 张金琳高航俞学劢
Owner 浙江数秦科技有限公司
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