Privacy preserving technology for multiple sensitive attributes in data publishing
Shiguang Ju · Jisuanji yingyong yanjiu · 2011
In view of the privacy leak problem of secure data publishing when sensitive data contains multi attributes,based on the multi-dimension bucket grouping approach,this paper proposed a(g,l)-grouping approach on the idea of lossy join.It divided sensitive attributes into groups according to the sensitivity,and set the size of each group as the dimension number of each dimension of the multi-dimension bucket.And proposed two specific line time based(g,l)-grouping algorithms,which were general(g,l)-grouping algorithm(GGLG) and maximal sensitivity first algorithm(MSF).Experimental results on the real world datasets show that the new model is able to reduce privacy disclosure apparently and enforce security of data publishing.