Study on K-anonymity Models of Sharing Medical Information

Today's globally networked society places great demand on sharing of information. Chinese Medical industry is undergoing a drastic Informationization process while privacy concerns arise. This paper discusses the threatening due to information share in medical industry, especially in a well-informatinized society. We first thoroughly describe the present situation of China Medical informatization level and explain the necessity of cross-organizational information share. The specific problem called linking attack is illustrated. We also formulated a corresponding anonymity model and exemplified the Generalization and Suppression techniques it utilizes to preserve privacy. Then we give an overview of present research areas and classical algorithms. Next, more detailed attacking conditions and the characteristic of medical information are taking into consideration. We formulated a Modified Entropy 1-diversity model which was an extension of the basic k-anonymity. Finally, we look forward to possible future researches.