A Multi Sensitive Attribute Data Inverse Clustering Privacy Preserving Algorithm for Sensitivity Attack
Bin Zhang · Dianzi xuebao · 2014
In allusion to l-diversity model not considering sensitivity differences between the sensitive attributes,a new attack pattern w hich named sensitivity attack w as proposed. Secondly,a new sensitive groups constructing method w hich based on sensitive attributes decomposition w as proposed,and a keyw ord w eight evaluation method called IDF w as used to measure the sensitivity of the sensitive values. At the same time,a multi sensitive attributes( l1,l2,…,ld)-diversity privacy preserving method for sensitivity attack w hich called MICD w as proposed,w hich guaranteed the sensitivity difference betw een sensitive values in sensitive groups by sensitivity inverse clustering. Experiment results demonstrated that the MICD algorithm could better protect sensitive attributes against sensitivity attack,and more effective on information loss.