Overview of Privacy Protection Technology of Big Data in Healthcare

With the popularization of smart mobile devices, the digitalization of medical devices and the structuring of electronic medical records, medical data have shown the characteristics of explosive growth. It has attracted wide attention to improve the understanding of the real value of big data in healthcare, by doing in-depth research and discussion on its development regulation. However, the issue how to protect the privacy security effectively in the process deserves attentions as well. Due to the characteristics of big data in healthcare and the storage environment, privacy protection faces severe challenges. First, the related concepts and characteristics of big data in healthcare are introduced. Then, focusing on the four stages of the life cycle model of big data in healthcare, which includes data collection, storage, share and analysis, this paper respectively introduces the risks and challenges it faces and the corresponding privacy protection technologies, analyzing the merits, drawbacks and their applicable scope. When collecting, anonymous technology and differential privacy can resist attacks based on background knowledge brought by data integration and fusion. During the storage stage, big data in healthcare are mostly stored on the cloud platform. Encryption and audit are often used for the confidentiality and integrity of data. During the data share stage, the access control plays an important part in controling the object to obtain data. During the analysis stage, privacy protection of big data in healthcare is achieved based on the framework of machine learning. Last but not least, regarding to the universal privacy protection challenges throughout the life cycle of big data in healthcare, reasonable suggestions are proposed in the management level