Private data distributed storage system and method of marginalized architecture

Abstract

The invention provides a private data distributed storage system of a marginalized architecture. User information is acquired through an acquisition terminal, the privacy normal form edge node provides a normal form template for the privacy protection terminal, the privacy protection terminal executes privacy protection calculation on the user information according to the normal form template so as to obtain normal form features of the user, therefore, the normal form features of the user can be uploaded to the information storage edge node to be stored so as to be called by the big data application end, and the big data application end can execute user-oriented big data analysis. The invention further provides a method of the system. On the basis of meeting a big data analysis function, user privacy can be protected to the maximum extent, and the diffusion degree of user information is reduced; the communication load and delay in the user information application process cannot be increased, and the requirements for high concurrency and massive calling of user information in big data analysis can be met; and the accuracy of the user information in the aspect of big data analysis isnot influenced.

Description

technical field [0001] The invention relates to the technical field of privacy protection, in particular to a distributed storage system and method for private data with a marginalized architecture. Background technique [0002] With the development of intelligent Internet of Things and big data technology, the collection of user information has gradually shifted from online to offline. For example, the collection of user face information can be realized through various face recognition camera devices. The collected user information can be used for big data analysis, thereby improving the operating efficiency of the intelligent Internet of Things and providing users with more personalized services. [0003] As users pay more and more attention to data rights and personal privacy rights, how to protect user privacy to the greatest extent and reduce The degree of diffusion of user information has become an urgent problem to be solved. At present, the main methods of privacy ...

AI Technical Summary

Problems solved by technology

However, centralizing user information and increasing timeliness restrictions will increase the communication load and delay in the application process of user information, which cannot meet the needs of high concurrency and massive invocation of user information in big data analysis

Fuzzifying user information may affect the accuracy of user information in big data analysis, and the impact of fuzzification on big data analysis cannot be verified in time

[0004] To sum up, the existing technology provides a distributed storage system and method for private data with a marginalized architecture, which can solve the problem: in the existing user information collection process, in order to protect user privacy to the greatest extent, user information is centralized and increased Timeliness limits the increased communication load and delay in the application of user information, which cannot meet the needs of high concurrency and massive invocation of user information in big data analysis; fuzzing user information may affect the accuracy of user information in big data analysis The impact of fuzzification on big data analysis cannot be verified in time

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