Clustering-based algorithm for data sensitive attributes anonymous protection
Geng Chen · Jisuanji yingyong yanjiu · 2012
In order to prevent the disclosure of data sensitive attributes,it requires preserving the anonymity of data sensitive attributes.The current algorithm that has proposed to meet l-diversity is mostly based on the hierarchy,which can lead to unnecessary information loss.For this reason,this paper proposed a clustering-based algorithm for data sensitive attributes anonymous protection,it adopted an improved distance measure method which was from achieving k-anonymity by clustering in attribute hierarchical structures and combined clustering together,the algorithm in accordance with the requirements of l-diversity model clustering of data sets.Experimental results show that the algorithm can not only protect anonymity of sensitive attri-butes in data set,but also reduce the extent of information losses.