云外包个人健康档案的安全存储与隐私诊断机制研究

According to the privacy requirement of storage and diagnosis for outsourced personal health record (PHR) in the cloud, the project makes a comprehensive study on the problems of secure storage with generalized features, self-adaptive privacy diagnosis as well as the resource consumption, and constructs its corresponding three key techniques. Firstly, we construct a secure fine-grained hierarchical PHR storage scheme to support secure computation, reusability and expansibility. It can assure the owner of PHR to define the security level of PHR by himself and guarantee the PHR can be accessed across different domains. Secondly, we design a general framework for privacy decision system to achieve the self-adaptive between privacy and high-accuracy diagnosis. Thirdly, we consider the optimized methods to reduce the resource consumption to realize the privacy，high-efficiency, real-time and reliability of PHR during the secure storage and diagnosis. The research achievement of the project provides an important theoretical basis and technology support for the secure storage and privacy-preserving diagnosis mechanism，which can advance the development of outsourced PHR from theoretical research to real application.

本项目针对云外包个人健康档案存储与诊断的隐私需求，全面系统地分析了广义特性、自适应诊断与资源消耗之间的内在联系，重点研究云外包个人健康档案的广义特性安全存储，自适应隐私诊断和隐私保护中资源消耗优化三个科学问题，并突破其所需的三个关键技术：一是，研究支持隐私计算的细粒度外包档案分级安全存储方案与其复用扩展方法，确保个人健康档案的拥有者可自定义档案安全级别并实现档案多服务域可访问；二是，设计隐私诊断决策模型的通用框架，构造隐私保护的多级预测模型与多服务域的协同隐私诊断方法，实现隐私诊断与高正确诊断之间的自适应；三是，考虑系统资源的消耗优化方法，实现存储与诊断过程中的隐私性、高效性、实时性与可靠性。本项目的研究成果将为云环境下个人健康档案安全存储与隐私保护诊断机制的构建提供重要的理论基础与技术支撑，促进云外包个人健康档案从理论研究快速走向实际应用。

本项目针对云外包个人健康档案存储与诊断的隐私需求，全面系统地分析了广义特性、自适应诊断与资源消耗之间的内在联系，重点研究云外包个人健康档案的广义特性安全存储，自适应隐私诊断和隐私保护中资源消耗优化三个科学问题，并突破其所需的三个关键技术：一是，研究支持隐私计算的细粒度外包档案分级安全存储方案与其复用扩展方法，确保个人健康档案的拥有者可自定义档案安全级别并实现档案多服务域可访问；二是，设计隐私诊断决策模型的通用框架，构造隐私保护的多级预测模型与多服务域的协同隐私诊断方法，实现隐私诊断与高正确诊断之间的自适应；三是，考虑系统资源的消耗优化方法，实现存储与诊断过程中的隐私性、高效性、实时性与可靠性。本项目的研究成果将为云环境下个人健康档案安全存储与隐私保护诊断机制的构建提供重要的理论基础与技术支撑，促进云外包个人健康档案从理论研究快速走向实际应用。

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