(k, g)-anonymity Model Based on Grey Relational Analysis

摘要

k-anonymity is an effective method of privacy preserving. However, some traditional k-anonymity models do not capture diversity and dispersibility of sensitive values in each equivalence class, which makes the privacy disclosure of anonymity table occur easily. In this paper, an advanced (k, g)-anonymity model for numerical data is proposed, and a (k, g)-MDAV algorithm is designed to achieve (k, g)-algorithm. Experimental results show that the algorithm can lower the risk of privacy disclosure while maintaining the data availability.