Individuation privacy preservation based on lossy join
Geng Chen · Jisuanji gongcheng yu sheji · 2011
k-anonymization of tables is an important approach to protect data privacy in data publishing scenario.(a,k)-anonymity model is an effective individuation privacy preservation method.These anonymization is achieved traditionally via generalization/suppression techniques.However,these methods have some defects on efficiency and data distortion.To solve the problem,a(a,k)-anonymity clustering algorithm based on greedy strategy is proposed recur to the idea of lossy join,which is an effective method to protect the privacy data.Experimental results show that the clustering algorithm is better than previous approaches.