Publishing Health Information without Distortion While Balancing Desired Privacy-Preserving and Utility

Subject Areas : Renewable energy

Abbas Karimi Rizi ¹ , Mohammad Naderi Dehkordi ² , Naser Nematbakhsh ³

1 - Faculty of Computer Engineering- Najafabad Branch, Islamic Azad University, Najafabad, Iran
2 - Big Data Research Center- Najafabad Branch, Islamic Azad University, Najafabad, Iran
3 - Department of Engineering- Shahid Ashrafi Esfahani University, Esfahan, Iran

Received: 2020-12-18 Accepted : 2021-03-02 Published : 2021-04-18

Keywords: Taxonomy, disease diagnostic code, membership analysis,

Abstract :

In the age of health information analysis, the disease diagnostic code is considered as the patient's privacy. Achieving this code is the most important need for the analysts while anonymizing the code is necessary for people when publishing health information. Disease diagnostic codes, usually presented based on international classifications, are displayed in the form of a taxonomy. In real life, patients only allow the category of the disease diagnostic code to be disclosed, not the original disease diagnostic code. Conventional privacy-preserving models often distort the category of the disease diagnostic code. Preserving privacy accompanying the data utility has always been a critical issue in the dissemination of health information. In this study, a new anonymization method is presented in a way that all attributes of health information can be published without distortion to maintain the utility of the data. So, the published information protects the privacy of patients, so that the experts' expectations and the utility of analysts are desired as expected. The innovative method disseminates health information in a way that the maximum probability of disclosing the disease diagnostic code is always less than or equal to the threat threshold defined by the expert, and on the other hand, the membership analysis error is reduced. The new method is scalable under certain conditions. The results of the practical evaluation of patient data obtained from one of the hospitals in Isfahan are evidence of the effectiveness of the proposed method.

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