模式识别与人工智能
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  2010, Vol. 23 Issue (6): 776-780    DOI:
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Decision-Tree Model Research Based on Privacy-Preserving
FANG Wei-Wei1,2,YANG Bing-Ru2,YANG Jun2,ZHOU Chang-Sheng1
1.Computer Center,Beijing Information Science and Technology University,Beijing 100192
2.Information Engineering School,University of Science and Technology Beijing,Beijing 100083

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Abstract  

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.

Key wordsPrivacy-Preserving Data Mining (PPDM)      Decision-Tree      Vertical Distribution     
Received: 27 July 2009     
ZTFLH: TP181  
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Articles by authors
FANG Wei-Wei
YANG Bing-Ru
YANG Jun
ZHOU Chang-Sheng
Cite this article:   
FANG Wei-Wei,YANG Bing-Ru,YANG Jun等. Decision-Tree Model Research Based on Privacy-Preserving[J]. , 2010, 23(6): 776-780.
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http://manu46.magtech.com.cn/Jweb_prai/EN/      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2010/V23/I6/776
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