An Algorithm of Decision Tree for k-Anonymity Data
Mei Wang · Journal of Wuhan University · 2011
Data mining is one of problems for the utility of anonymized data under the k-anonymity privacy protection model.Through analysis,we find that both the quasi-identifier attribute values in the k-anonymity table and the node except leaf of the decision tree in the private table are needed to generalize.According to this correspondence,we propose a decision tree algorithm based on k-anonymity.The algorithm accepts the k-anonymity table as input to avoid the ID3algorithm data preparation work before running.Experimental results show that the algorithm saves the time which is used to build generalize tree and it is efficient for k-anonymity data table.