Data release privacy protection algorithm and system based on big data

Abstract

The invention relates to the technical field of data privacy protection, and discloses a big data-based data release privacy protection algorithm, which comprises the steps of obtaining a to-be-released data table, and obtaining a statistical histogram of to-be-released data according to an attribute value division result of the to-be-released data; converting the statistical histogram of the to-be-published data into a k-fork interval tree, adding noise to the k-fork interval tree to disturb the k-fork interval tree to obtain a noise-added interval tree, and approximately converting the noise-added interval tree into an average histogram; constructing an integrated classification function based on feature selection; solving the integrated classification function by using an L-BFGS optimization algorithm to obtain a classification result of the to-be-published data; and clustering the to-be-published data according to the classification result of the to-be-published data, performing data privacy protection by utilizing a clustering-based personalized anonymous algorithm, and publishing the private data at the same time. The invention further provides a data release privacy protection system based on the big data. According to the invention, the protection of private data is realized.

Description

technical field [0001] The present invention relates to the technical field of data protection, in particular to a big data-based data release privacy protection algorithm and system. Background technique [0002] With the popularization of the Internet and the rise of the mobile Internet, the commercial value of big data has been applied to all aspects of society, which has brought a profound impact on the development of human society. At the same time, it also makes the collection, analysis or mining of information data more convenient and accurate. However, in the process of sharing, mining and knowledge discovery of data information as the research purpose, it is also accompanied by the leakage of sensitive private information. How to protect private data has become a hot topic in current research. [0003] At present, the privacy protection technology in data release can be divided into restricted release technology, data encryption technology and data distortion techn...

AI Technical Summary

Problems solved by technology

The traditional method for making an anonymous model generate an equivalence class does not consider the problem of sensitive attribute values, and similar sensitive attribute values ​​of the same sensitive attribute are very likely to exist in the equivalence class. It is very easy to cause probabilistic attacks or similarity attacks to cause privacy leaks, and secondly cause greater information loss in constraining sensitive attribute values

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