Privacy Protection Technology and Access Control Mechanism for Medical Big Data
Narn-Yih Lee, Binghan Wu · 2017
The age of big data is coming. Many data processing and statistical analysis technologies of big data are developing now. They widely impact our live, for examples: society, science, medical industry, military, education, government and business, etc. By using statistical analysis technologies of big data, many valuable information are produced and those results can be used to predict the trend of the future. However, it also brings huge challenges for personal privacy. For protecting the privacy of personal medical data, how to use cryptographic technologies de-identify medical privacy data becomes very important. On the other hand, how to control the access privileges of privacy data for authorized persons are also needed to be solved. This paper bases on Diffie-Hellman protocol to design a privacy protection system for medical big data. It can protect patient privacy information and avoid revealing the medical data. Besides, it can assign access right to authorized doctors, such that the authorized doctors can access and share the patient privacy information. Finally, it can achieve the destination of protecting the privacy and confidentiality of medical big data.