General data release privacy protection method based on random response technology

Abstract

The invention belongs to the technical field of privacy protection, and particularly relates to a general data release privacy protection method based on a random response technology. The method is based on the random response technology, and is characterized in that the calculation complexity of the reconstructed unbiased estimation result is reduced from exponential growth to linear growth by utilizing a matrix decomposition method and the Kronecker property, the error minimization of the unbiased estimation result is realized, the privacy protection parameters are allowed to be independently set for each attribute, and the calculation efficiency, the data availability and the application flexibility are effectively improved. The method supports the data release of a single sensitive attribute and multiple sensitive attributes, wherein the sensitive attributes comprise a Boolean attribute, a classified attribute and a numerical attribute; an efficient and flexible data publishing privacy protection mechanism can be provided for the scientific research and management in the fields of medical treatment, finance, biological information, transportation and the like, the data privacyis protected in the data publishing process, the useful information of published data is reserved, and the sharing of the data is promoted.

Description

technical field [0001] The invention belongs to the technical field of privacy protection, and in particular relates to a privacy protection method for data publishing. Background technique [0002] In data publishing applications, data publishers have two main concerns: one is to protect the privacy of individual sensitive data from being leaked, and the other is to preserve the statistical laws existing in the original data to ensure the availability of the published data. Privacy-preserving technology is a key guarantee to simultaneously realize these two main concerns. For example, a hospital has a large number of medical records of patients, and these data need to be provided to doctors, scientific researchers, and social managers to find out the regular characteristics in the data and provide services for researching disease treatment or prevention methods. However, publishing these data directly will lead to the disclosure of private information such as patients' dis...

AI Technical Summary

Problems solved by technology

Compared with the generalization technology, the data release form of the random response technology is relatively uniform, which can provide better privacy protection strength, but the existing methods based on the random response technology still have problems such as inflexible privacy parameter settings and high computational complexity.

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