A novel privacy preserving approach for database security

A lot of information of individuals is published by hospitals, insurance companies, medical administrations and governments, which may cause a major risk of sensitive information leakage in recent years. Thus, privacy preserving in data publishing has become an important research topics in database security field. In this paper, we propose a novel privacy preserving approach based on k-anonymity model and multidimensional model, which combines global recoding and local recoding technology and provides privacy preserving in data publishing. The novel anonymity strategy can efficiently and dynamically designate sensitive information according to the requirements of users. Then we develop an anonymous strategy algorithm which adapts to the anonymity strategy and achieves the purpose of preventing homogeneity attack and background knowledge attack. Finally, we conclude the paper and introduce the research directions for future work.