Method for processing big data based on MLDM algorithm meeting secondary aggregation

Abstract

The invention belongs to the technical field of database privacy protection, and discloses a method for processing big data based on an MLDM algorithm meeting secondary aggregation. The method comprises the steps of introducing a k-means algorithm based on a (1,d,e)-MDAV algorithm; and when a big data set is processed, dividing the big data set into a plurality of small data sets firstly, then processing each small data set by using the (1,d,e)-MDAV algorithm, and finally combining the processed data, thereby enabling the whole data set to meet a (1,d,e)-diversity rule, and obtaining relatively low algorithm time complexity and relatively short algorithm time through improvement. According to the method, a k-means algorithm is introduced based on the (1,d,e)-MDAV algorithm; a new MLDM algorithm is proposed; and when the big data set is processed, the big data set is divided into the small data sets firstly, then each small data set is processed by using the (1,d,e)-MDAV algorithm, and finally the processed data are combined, so that the whole data set can meet the (1,d,e)-diversity rule, and the relatively low algorithm time complexity and the relatively short algorithm time can be obtained through the improvement.

Description

technical field [0001] The invention belongs to the technical field of privacy protection of databases, and in particular relates to a method for processing large data based on an MLDM algorithm satisfying secondary aggregation. Background technique [0002] The issue of privacy protection in data publishing was first raised in the field of statistical leakage control, and then gradually penetrated into the entire information technology field. In the field of statistical leak control, methods such as micro-aggregation, randomization, sampling, and adding white noise are mainly used to protect information. While trying to ensure the statistics and availability of processed data and the security of private information, more information is retained. Useful information, balance the relationship between data confidentiality and availability. After years of development, the privacy protection technology released in the data mainly focuses on two aspects of research, one is the us...

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Problems solved by technology

[0007] In summary, the technical problem solved by the present invention is: solve (l, d, e)-MDAV algorithm algorithm complexity is high and the problem of long computing time when processing large data sets

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