State-of-the-art in Distributed Privacy Preserving Data Mining

摘要：

Privacy preserving data mining has become an important research problem. The chief research is how to mine the potential knowledge and not to reveal the sensitive data. In reality, large amounts of data are stored in distributed sites, so the DPPDM (Distributed Privacy Preserving Data Mining) is very important This paper gave a survey on the DPPDM. Based on different underlying technologies, there are three kinds of techniques: perturbation, secure multi-party computation and restricted query. It provides a detailed description of the research in this area, compares the advantages and disadvantages of each method, foucs on the hot topic in this field, points out the future research directions.

关键词： data mining distributed data privacy preserving

作者: LIU Ying-hua YANG Bing-ru CAO Dan-yang MA Nan

作者单位: School of Information Engineering, University of Science and Technology Beijing, Beijing 100083,Chin School of Information Engineering, University of Science and Technology Beijing, Beijing 100083,Chin

会议类型: 国际会议

会议名称: 2011 2nd International Conference on Data Storage and Data Engineering(DSDE 2011)(2011年第二届数据存储与数据工程国际会议)

会议地点: 西安

会议语种:英文

页码: 545-549

在线出版日期: 2011-05-13（万方平台首次上网日期，不代表论文的发表时间）