Data privacy protection method in classification data mining system

Abstract

The invention relates to a data privacy protection method in a classification data mining system. All attributes of processing data in the system are allocated to all parties according to a distributed vertical partitioning mode. The method includes that firstly, each party deploys privacy data thereof in random data in a ciphertext form and acquires information entropy of each attribute by cooperative computing; secondly, each party acquires information gain of each attribute by adopting an encrypted transfer mode for computation results in the computation process; thirdly, the information gains of all the attributes are compared to acquire the attribute corresponding to the maximum information gain, and division is performed by taking the attribute as a node; finally, whether or not conditions for ending division are satisfied is judged, and if yes, the division is ended, otherwise the scheme is circulated. On the basis of a privacy protection ID3 classification model, a fully homomorphic encryption algorithm is adopted, and private data protection in the network classification data mining process is realized effectively.

Description

technical field [0001] The invention relates to a data privacy protection method in a classified data mining system. Background technique [0002] Data Mining (DM) is the process of extracting hidden, unknown but potentially useful information and knowledge from a large amount of incomplete, noisy, fuzzy, random data. . With the development of data mining and knowledge discovery technology, the research of data mining and knowledge discovery has covered the content of the three major disciplines of database, artificial intelligence and mathematical statistics. It upgrades people's application of data from low-level simple query to mining knowledge from data and providing decision-making and support. [0003] Due to the many advantages of data mining, it has good application prospects in commercial retail, medical and insurance, big data analysis, etc. The research on data mining technology is becoming one of the hot spots in academia, business and industry. However, while...

AI Technical Summary

Problems solved by technology

At present, there have been many achievements in the research on the first two aspects, but few people have been involved in the research on privacy protection of classification mining. The multi-party participation and quasi-integrity environment in the distributed environment obviously bring certain advantages to the solution of the problem. Difficulty, the general strategy is to use cryptography methods, but only cryptography methods are not enough, still need to combine new technologies and methods to ensure that the private data of all parties in the classification mining is not leaked; for distribution For the traditional environment, the distributed environment includes two types of data split horizontally and vertically split data. In a vertically split data set, different attributes of the same data are stored in different participants; Attributes are stored in the same participant, and different participants store different data information

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