Efficient(K,L)-anonymous Privacy Protection Based on Clustering
Chai Ruimi · Jisuanji gongcheng · 2015
In order to prevent sensitive information leakage in the release data,this paper puts forward a kind of anonymous protection algorithm based on clustering. It takes the overlooked influnces of identifier to sensitive attributes into account,clusters the sensitive attribute of data,and makes the modified k-means clustering algorithm apply to this step,to make the data more similar in class. It uses(K,L)-anonymous method for tables which being published,considering of sensitive attribute in the equivalence class,and puts forward the effective methods for privacy protection.Experimental results show that the proposed model has good effect of privacy protection,compared with the traditional Kanonymous methods,it can achieve privacy protection,at the same time,reduce the loss of data information,make the data have a higher accuracy,and the executive time is shorter.