%0 Journal Article
%T State-of-the-art in distributed privacy preserving data mining<br>分布式隐私保护数据挖掘研究*
%A LIU Ying-hu
%A YANG Bing-ru
%A MA Nan
%A CAO Dan-yang
%A <br>刘英华
%A 杨炳儒
%A 马楠
%A 曹丹阳
%J 计算机应用研究
%D 2011
%I 
%X In recent years, privacy preserving data mining is one of the hot point problems in data mining. The chief research is how to mine the potential knowledge and not to reveal the sensitive data. In reality, large amounts of data stored in multiple sites, so the DPPDM (distributed privacy preserving data mining) is more important. This paper summarized the features of DPPDM, detailed described the research in this area, compared the advantages and disadvantages of each method, surveyed the state-of-the-art in DPPDM. Furthermore, it pointed out the future research directions.
%K data mining
%K privacy preserving
%K distributed data<br>数据挖掘
%K 隐私保护
%K 分布式
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=1F8EB868F38CE072F353FB8F40BBC67B&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=F3090AE9B60B7ED1&sid=D2F5521E765373D9&eid=6451941DD72CEE30&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=42