文献类型：期刊文献

英文题名：Experimental analysis for novel K-NN classification algorithm in cloud computing

作者：Wang, Jian[1]

第一作者：王健

通讯作者：Wang, J.|[1048412d09c322f]王健;

机构：[1] College of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou 450003, China

第一机构：河南财经政法大学计算机与信息工程学院

通讯机构：[1]College of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou 450003, China|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

年份：2012

卷号：8

期号：22

起止页码：9217-9224

外文期刊名：Journal of Computational Information Systems

收录：EI(收录号：20124815723753);Scopus(收录号：2-s2.0-84869816041)

语种：英文

外文关键词：Cloud computing - Computer systems - Data mining - Data privacy - Pattern recognition

摘要：Privacy Preserving Data Mining (PPDM) refers to that we can use technical method, such as data perturbation, data reconstruction, encryption, to do the mining job while the miner can't access the original private data under the premise of sufficient precision and accuracy. Nowadays there are many PPDM algorithms around the classification mining, clustering and association rules mining. However, in the cloud computing environment, there is no PPDM algorithm which can do data mining while protecting privacy. So this paper proposes a novel K-NN classification algorithm for privacy preserving in cloud computing. We also design a lot of experiments to observe the accuracy comparison between our proposed algorithm and traditional algorithm. The experimental results show the application and performance of the proposed algorithm. Copyright ? 2012 Binary Information Press.