Abstract:

It is important to keep balance between the usefulness and the degree of privacy protection when the techniques of generalization and suppression are applied to the 
K-anonymization of data. A novel K-anonymity method implemented by grey relational analysis based on difference information theory is proposed. The similarity  between any two data sequences is described by their balanced closeness degrees. The generalization and suppression operations are carried out accordingly. The 
K-anonymized data are then applied in cluster analysis. The experimental results on the real data sets prove the effectiveness of the proposed method.