A Privacy Protection Method in Sensitive Data Publishing

Abstract

The invention discloses a privacy protecting method in sensitive data publishing. The method comprises the following steps: receiving a data set from a user and a plurality of corresponding generalized input trees, traversing each group of data in the data set and successively judging whether each row of data in the group of data has a corresponding generalized input tree or not; if so, searching for a corresponding node from the corresponding generalized input tree according to an attribute value of the data and inputting information of the node to a coordinate array; if not, directly inputting the attribute value of the data into the coordinate array so as to obtain m rows of coordinate arrays; adding a zone bit with an initial value of 0 for each of the coordinate arrays; establishing p clusters; and selecting p rows of coordinate arrays from the m rows of coordinate arrays randomly to be used as the central points of p clusters separately. According to the invention, a method of clustering first and then generalizing is adopted, so that the computing efficiency is increased and a foundation is laid for scaled computing.

Description

technical field [0001] The invention belongs to the field of computer security, and more specifically relates to a method for protecting privacy in publishing sensitive data. Background technique [0002] With the rapid development of Internet technology, various Internet applications have sprung up like mushrooms after rain. It is undeniable that these Internet applications have greatly facilitated our lives. But while using these applications, our various behavioral data will also be stored by major application manufacturers. Due to research needs or other purposes, data holders need to release these data, which leads to the leakage of users' private information. The problem of privacy leakage in the big data environment is becoming more and more prominent. Encrypting and hiding sensitive data in the process of data release has become very important. . Sensitive data requires privacy protection, and its main goal is to eliminate the correspondence between user sensitive...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above defects or improvement needs of the prior art, the present invention provides a privacy protection method in publishing sensitive data, the purpose of which is to calculate the distance between data and The generalized output of data solves the technical problem of unreasonable allocation of k-anonymous groups due to inaccurate similarity calculation in the above existing methods

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