Research And Implementation Of Healthy Big Data Protention Technology In Cloud Environment

The research of healthy big data in cloud environment is of great value in analyzing the distribution,spread trend,and prevention of diseases.In order to enable the researchers to research the healthy big data,it is necessary to store and distribute the healthy big data.And healthy big data related to the user’s privacy information,the leakage of these information will cause great harm to the user.Therefore,in order to enable researchers to obtain measurable healthy big data,while protecting user privacy,we need to research healthy big data protection technology in cloud environment,and publish healthy big data to researchers after protection processing.Information publishers typically delete or generalize attributes that involved user privacy in healthy big data,and retain the data attributes with research value.This thesis deeply researched the safety of healthy big data storage,the safety of healthy data publish,the privacy protection technology and related laws in cloud environment,and researched the core products of the domestic mainstream safety vendors and applies them to the healthy big Data privacy protection security solution,which Comprehensively protect healthy big data and achieve maximum protection of healthy big data.This thesis makes the following research:（1）Proposed a privacy protection solution for healthy big data in cloud environment.In this thesis,the requirement of privacy protection for healthy big data is strict,need to take full account of the security and practicability of the solution.After in-depth research of data security protection method,a security solution is proposed in this thesis,which fused physical security equipment,anonymous processing and encryption storage,and realized the comprehensive protection of healthy big data.（2）Proposed（α₁, α₂, α₃）-Sensitive K-anonymous model for healthy big data anonymous publish.In this thesis,through the research of privacy protection technology,especially the implementation principles and defects of the classic K-anonymous model and P-sensitive model,（α₁, α₂, α₃）-Sensitive K-anonymous model is proposed,in which the value of α₁, α₂, α₃,and K are set by experts.The model is safer and more flexible,and can solve the consistent attack problem that the traditional K-anonymous model and the P-Sensitive model can’t solved.（3）Proposed a storage encryption strategy for the characteristics of healthy big data.Based on the premise of not affecting the performance of the system,t this thesis designed a supplementary encryption strategy for healthy big data,which prevents developers and data managers from viewing user privacy information,but can also be used to provides protection for the healthy big data when the database is attacked.