@article{7e4e93ff671e42cfa92646e7d5f84423,
title = "Medical big data access control model based on UPHFPR and evolutionary game",
abstract = "This paper discusses how to improve the accuracy of doctors' diagnosis and how to protect the security of patients' information. First, UPHFPR (Uncertain Probability Hesitant Fuzzy Preference Relationship) is applied to select more accurate target for doctors. The framework involved an information entropy to quantify the access request risks and privacy risks when doctors access clinical data. Based on the bounded rationality hypothesis, we build a multi-player evolutionary game model of risk access control, and analyze the participants' dynamic selection strategy and evolutionary stability. The simulation experiments suggest that UPPHFPR can help doctors choose the correct work objectives by integrating doctors' diagnostic opinions; we also incorporate the risk of doctor's access behavior into the evolutionary game's profit function, which can realize risk-adaptive access control. This model avoids the disclosure of clinical data and effectively protects the patients{\textquoteright} privacy.",
keywords = "Access control, Evolutionary game theory, Medical big data, UPHFPR",
author = "Rong Jiang and Shanshan Han and Ying Zhang and Taowei Chen and Junrong Song",
note = "Funding Information: This work was supported by National Natural Science Foundation of China (Nos. 71972165, 61763048 ), Science and Technology Foundation of Yunnan Province (No. 202001AS070031). Funding Information: The research on the access control model in this article is based on the National Natural Science Foundation of China, which is a joint project between Yunnan University of Finance and Economics and a third-class hospital in Kunming, China. A third-class hospital in Kunming, China, provided real data for the experiment in this paper. The data occupied 1,200G of storage space and is divided into 5 databases and 1360 data tables, including 2,139,373 records. The data types include text data, image data, and etc. According to the requirements of the model experiment in this paper, it is not necessary to use all the medical data, so only part of the data is extracted from the medical data for the experiment. The purpose of the experiment in this paper is to verify the validity of the UPHFPR-EGBAC (access control based on UPHFPR and evolutionary game) model and analyze the factors that affect doctors' access behavior selection strategies. Publisher Copyright: {\textcopyright} 2022 THE AUTHORS",
year = "2022",
month = dec,
doi = "10.1016/j.aej.2022.03.075",
language = "English",
volume = "61",
pages = "10659--10675",
journal = "Alexandria Engineering Journal",
issn = "1110-0168",
publisher = "Alexandria University",
number = "12",
}