Differential privacy histogram publishing method and system giving priority to keg availability

Abstract

The invention provides a differential privacy histogram publishing method and system giving priority to keg availability, and the method comprises the steps: carrying out the preliminary disturbance: carrying out the preliminary disturbance of an original histogram through the combination of a part of privacy budget and a Laplacian differential privacy mechanism, and obtaining an intermediate histogram after the preliminary disturbance; threshold function processing: performing threshold processing on the intermediate histogram after preliminary disturbance; sequencing: sequencing the updated middle histograms to obtain histograms which are sequenced from small to large; grouping and clustering, namely sequentially grouping the histograms sorted from small to large by utilizing the residual privacy budget to obtain a grouping set; and publishing, namely generating final noise by combining each group in the group set with the residual privacy budget, and obtaining a disturbance histogram after disturbance implementation and publishing the disturbance histogram. According to the method and system, strict epsilon-differential privacy protection is met, and meanwhile, the balance between a reconstruction error and a noise error is also realized.

Description

technical field [0001] The invention belongs to the field of information security, and in particular relates to a differential privacy histogram publishing method and system that give priority to keg availability. Background technique [0002] With the rapid development of the mobile Internet and the widespread popularity of mobile devices, a large amount of data is generated every day based on various App applications. Although the collection, extraction, and release of data can help users obtain the required information efficiently, quickly, and accurately from the complicated data, the issue of privacy security is also becoming more and more serious. The potential or direct harm brought to users by the disclosure of these private information makes the personal privacy security of users a hot topic. [0003] The issue of data privacy protection was first raised by the statistician Dalenius in the late 1970s. He believes that protecting the private information in the data...

AI Technical Summary

Problems solved by technology

[0013] The problem to be solved by the present invention is to provide a relatively balanced unit noise amount for both small buckets and large buckets under the background of uneven data distribution for traditional histogram publishing that satisfies ε-differential privacy

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