Big data security fusion method without revealing privacy

Abstract

A method for safe integration of big data, comprising: a first party and a second party negotiating about associated fields, data items required by the first party and the second party and a sorting rule; screening out, on the basis of the data items required by the first party and the second party, a first to-be-integrated data set and a second to-be-integrated data set respectively from a first data set and a second data set; sorting, according to the sorting rule, respectively the first to-be-integrated data set and the second to-be-integrated data set, and removing, respectively from the first to-be-integrated data set and the second to-be-integrated data set, the data that the associated fields correspond to; submitting the first to-be-integrated data set and the second to-be-integrated data set to a third party computing platform, so as to form an integrated data set; and the third party computing platform generating, by means of analysis and calculation of the integrated data set, a result data set. This invention effectively prevents the private data from being leaked while accomplishing the integration of big data, facilitating share of information on the premise of ensuring the data security.

Description

Technical field [0001] The invention relates to a big data safety fusion method. Background technique [0002] With the introduction of the national "Internet +" strategy, the need for big data integration among various industries has become increasingly urgent. However, on the one hand, different institutions welcome big data sharing. The introduction of the fusion of different types of data can produce new analysis results, and the value of the data will therefore have a multiplier effect; on the other hand, the two parties are more concerned about the process of data fusion. There are concerns about the leakage of private data in China, because the final analysis result is often only a statistical conclusion, and in the process of big data fusion calculation, all the details of the data have to be exposed to the other party. This problem has become a major obstacle to big data collaboration and sharing between industries. [0003] Therefore, those skilled in the art expect to ...

AI Technical Summary

Problems solved by technology

However, on the one hand, different organizations welcome the sharing of big data. The introduction of fusion of different types of data can produce new analysis results, and the value of data will thus have a multiplier effect; There are concerns about the leakage of private data in the Internet, because the final analysis result is often only a statistical conclusion, but in the process of big data fusion calculation, all the entry details of the data have to be exposed to the other party

This problem has become a major obstacle to big data collaboration and sharing among industries

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