期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：6
DOI：10.15680/ijircce.2015.0306103
出版社：S&S Publications
摘要：Data mining concerns with extracting the required important data from the database and ignoring therest. With the success of data mining, privacy preservation has also acquired the great importance. The new conceptprivacy preserving data mining PPDM, concerns with preserving the privacy of sensitive individuals data. In this paper,privacy of sensitive attribute data concerned with individual user or data miner is preserved. For preserving the privacyadditive perturbation method is used, in which random noise are added to the sensitive attribute values from the requiredata set and perturb copies are generated. A new concept multilevel trust MLT-PPDM approach is used, in which wegenerate multiple perturb copies of same data for the data miners at different trust level. For perturb copies generation,group generation algorithm is used, in which for a given original data, multiple perturbed copies of same data will begenerated. We are using relational streaming database which means records in the database are updated continuouslyand at the same time for each updated records perturb copies will be generated successfully, which is the newcontribution to the proposed work
关键词：Data mining; Privacy preservation data mining (PPDM); Additive perturbation; Group generation;algorithm; Relational Streaming data.
