期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：5
页码：5594-5599
出版社：IJECS
摘要：In collaborative data mining, data sets from various parties are submitted to a third party where they arecombined, privacy of each data sets’ sensitive attributes are protected and data mining is carried out. Inprivacy preserving data mining, there is a need to extract knowledge from databases without disclosinginformation about individuals. Each participant will have sensitive and non-sensitive data in their localdatabase. Therefore the most important challenge in privacy preserving multi party collaborative datamining is how these multiple parties conduct data mining without disclosing each participant’s sensitivedata. In this paper we propose a two-level encryption algorithm for protecting sensitive attributes fromdisclosure and a generalization algorithm. This approach guarantees high level privacy with less amount ofcomplexity as compared to the existing methods and also proves to be fast and efficient over dynamicqueries.
