Big data privacy retrieval method based on edge computing

Abstract

A big data privacy retrieval method based on edge computing comprises the steps that (1) enabling a user side to calculate information entropy of a to-be-uploaded data file, and carrying out core dataextraction and storage; 2) uploading the non-core data to an edge end and constructing an implicit retrieval index; 3) presetting system parameters at the edge end, and performing structure hiding and re-division on the non-core data to obtain public part data and private part data; 4) encrypting the public part of data and uploading the encrypted public part of data to a cloud, wherein the cloudstores the encrypted public part of data; and 5) enabling the user side to initiate a retrieval application according to the keyword, enabling the edge side to generate a retrieval token according tothe keyword and the implicit retrieval index, enabling the cloud side to perform keyword matching retrieval after acquiring the retrieval token, returning a retrieval result to the edge side, and enabling the edge side to return the retrieval result to the user side. According to the method, the effectiveness, reliability and flexibility of the system in the storage and retrieval process can be ensured, and efficient and private data retrieval is achieved.

Description

technical field [0001] The invention relates to the field of data privacy protection in a big data network, in particular to a big data privacy retrieval method based on edge computing. Background technique [0002] Intelligent network infrastructure and high-capacity storage have been widely deployed in various types of environments, regardless of time and place, which has brought great benefits for users to collect and publish information through multiple platforms (such as smart devices, mobile terminals). convenient. Statistics and forecasts from the International Telecommunication Union Telecommunication Standards Body (ITU-T) show that by 2020, each person will generate 1.7 million pieces of data per second. There is no doubt that this new industrial wave, cloud computing, will help shape a new era of technological development and economic growth. The global expanded network market is expected to reach USD 9,336.2 million by 2050, with approximately 80% of enterprise...

AI Technical Summary

Problems solved by technology

However, some necessary improvements and innovations have not been proposed for future-oriented computation and storage of data-intensive services based on edge and cloud interactions.

The main reason is the following factors: the solution used for cloud computing security may not be directly applicable after the introduction of edge computing. If the characteristics of the edge device close to the underlying network cannot be fully understood, the traditional management model cannot be applied to the new solution.

Secondly, whether it is security testing or information authentication, it is difficult to ensure its security performance if the main environment (that is, the cloud server) is not sure enough to be trusted.

In addition, the above methods still lack the consideration of the security of the data itself for the design of matching edge computing with the traditional sensor cloud network

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