A privacy protection method for health care big data management based on risk access control.

With the rapid development of modern information technology, the health care industry is entering a critical stage of intelligence. Faced with the growing health care big data, information security issues are becoming more and more prominent in the management of smart health care, especially the problem of patient privacy leakage is the most serious. Therefore, strengthening the information management of intelligent health care in the era of big data is an important part of the long-term sustainable development of hospitals. This paper first identified the key indicators affecting the privacy disclosure of big data in health management, and then established the risk access control model based on the fuzzy theory, which was used for the management of big data in intelligent medical treatment, and solves the problem of inaccurate experimental results due to the lack of real data when dealing with actual problems. Finally, the model is compared with the results calculated by the fuzzy tool set in Matlab. The results verify that the model is effective in assessing the current safety risks and predicting the range of different risk factors, and the prediction accuracy can reach more than 90%.