Utility Enhancement for Privacy Preserving Health Data Publishing

In the medical field, we are amassing phenomenal amounts of data. This data is imperative in discovering patterns and trends to help improve healthcare. Yet the researchers cannot rejoice as the data cannot be easily shared, because health data custodians have the understandable ethical and legal responsibility to maintain the privacy of individuals. Many techniques of anonymization have been proposed to provide means of publishing data for research purposes without jeopardizing privacy. However, as flaws are discovered in these techniques, other more stringent methods are proposed. The strictness of the techniques is putting in question the utility of the data after severe anonymization. In this paper, we investigate several rigorous anonymization techniques with classification to evaluate the utility loss, and propose a framework to enhance the utility of anonymized data.