1.Computer Center,Beijing Information Science and Technology University,Beijing 100192
2.Information Engineering School,University of Science and Technology Beijing,Beijing 100083
How to realize privacy-preserving data mining becomes a research hotspot in a distributed environment. A model is proposed to realize privacy-preserving decision-tree classifying when data are vertically partitioned. In this model, a privacy-preserving decision-tree is proposed, which is composed of Global-Table stored by an obvious semi-honest partner and several local decision-trees stored by different sites. By using indexed array and private data comparison protocol, decision-tree generation and classification can be realized without uncovering the original information. Theoretical analysis and experimental results demonstrate the proposed model provides good capabilities of privacies preserving, accuracy and efficiency.
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