Attribute-centric anonymization scheme for improving user privacy and utility of publishing e-health data

Abstract

The adoption of advanced technologies in the healthcare sector has brought about many improvements in the industry, including better communication between healthcare providers, improved quality of treatment, and reduced cost. For the most part, these improvements have come about due to collaboration between healthcare providers and the sharing of healthcare data. However, this introduces various security and privacy concerns pertaining to the data in question. Preserving the privacy of the patients while simultaneously sharing data that would facilitate medical research is absolutely essential, for it is not just an ethical requirement but is also dictated by the regulations. In this paper, we propose a new anonymization scheme of data privacy for e-health records which differs from existing approaches in its ability to prevent from identity disclosure even faced with adversaries having pertinent background knowledge. The proposed scheme is based on transforming data into fixed intervals and then replacing original values with averages. As a result, the proposed scheme offers improved data privacy and utility in privacy preserving data publishing. The simulation results show the effectiveness of the scheme and verify the aforementioned claims.