Relevant time series publishing method and system based on differential privacy

Abstract

The invention provides a correlation time series issuing method and system based on differential privacy. The correlation time series issuing method comprises segmenting an original sequence to be issued through an observation window with a preset length, and processing a subsequence section in the observation window as a short-time stationary process; calculating the autocorrelation function of the subsequence in the window first, then generating a correlation Laplacian noise sequence being consistent with the autocorrelation function of the subsequence, overlay noise onto the subsequence, and issuing a sequence containing noise after the original sequence is processed. According to the invention, a sliding window mechanism and a correlation Laplacian noise mechanism are employed, and the problem that in an existing correlation time series issuing method by means of a differential privacy mechanism, the actual effective privacy protection intensity cannot reach the preset value and the data availability is low is solved.

Description

technical field [0001] The present invention relates to the fields of data mining and privacy protection, and more specifically, to a method and system for publishing correlation time series based on differential privacy, which is used to solve the problems faced by existing methods for publishing correlation time series using differential privacy mechanisms The actual and effective privacy protection strength cannot reach the preset value and the data availability is low. Background technique [0002] With the development of social informatization and the increasing popularity of mobile terminal equipment, a large amount of time series data (such as medical, financial, traffic data, etc.) Sequence analysis and mining to obtain valuable information requires data collectors (individuals, enterprises, governments, etc.) to publish and share the collected time series data. However, time series data may contain sensitive information of users, and data collectors are reluctant t...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the defects and insufficiencies of the existing methods, the present invention proposes a differential privacy publishing technical scheme of correlation time series, which can prevent attackers from exploiting The attack initiated by the correlation background knowledge ensures that the set privacy protection strength is effective in practice, and at the same time does not increase the noise size, so as to solve the actual and effective privacy when using the differential privacy protection mechanism to publish the correlation time series. The problem that the protection strength cannot reach the preset value and the data availability is low

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