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In this paper we studied privacy preserving distributed data mining. The existing methods focus on a universal approach that exerts preservation in the same degree for all persons, without catering for their concrete needs. In view of this we innovatively proposed a new framework combining the secure multiparty computation (SMC) with K-anonymity technology, and achieved personalized privacy preserving...
This paper studied how two parties collaboratively built a decision tree on the union of their dataset without revealing privacy when dataset is vertically and horizontally distributed. We gave an algorithm of privacy preserving C4.5 which is applicable to vertically and horizontally partitioned dataset, and also gave the detailed computation method of the information gain ratio in the case of without...
It has been a significant research subject that how to extract valuable knowledge in data and to preserve private or sensitive information in data mining process from leaking. By comparing and analyzing privacy-preserving data mining algorithm, the paper has established the classification frame of privacy-preserving algorithm, found the opening of present privacy-preserving technology study and meanwhile...
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