云计算环境中数据的对称可搜索加密关键技术研究

With the rapid development of cloud computing, users are beginning to move their data to the cloud server. To preserve users' privacy, data are usually stored in encrypted form in the cloud server, which raises a new challenge for performing search over the encrypted data efficiently. Symmetrical Searchable Encryption (SSE) has the important scientific significance and application value because it can support keyword based search over encrypted data efficiently. However, the existing research results cannot be applied into practical industry due to their limitations in terms of functionality, security and efficiency. In this project, first, based on some core technologies, we start from the severe known background model, thereby the research problem is abstracted to the model space. Then, we deeply study four characteristics of SSE, including vector space based multi-keyword complex logic operations, file updating, quantized search users' preferences, as well as efficient and various big data search. We will prove the security of proposed SSE schemes with the above characteristics. Finally, we evaluate the efficiency of the proposed SSE schemes in the real cloud platform. The project will be able to enrich the theory of SSE, and lay the foundation for the industrial application of SSE.

随着云计算的迅速发展，用户开始将数据迁移到云端服务器。为了保护用户隐私，数据一般以密文形式存储在云端服务器,这使得对密文的高效搜索成为一个挑战性的研究课题。对称可搜索加密（Symmetric Searchable Encryption，SSE）由于支持在密文上进行关键字搜索且效率较高，因而具有重要的科学意义和应用价值。但是，现有的研究成果在功能性、安全性及效率上尚有不足，对于指导实际的产业应用还有很大的局限性。本项目拟在多项核心技术的基础上，从严格的已知背景模型入手，将问题抽象到模型空间，然后深入研究SSE的四种特性，包括基于向量空间的多关键字复杂逻辑运算、文件的动态更新、搜索用户偏好的量化以及高效的多类型的大数据搜索，并分别证明具备以上特性的SSE方案的安全性，最后在真实的云平台上验证所提出的SSE方案的效率。本项目的研究内容将能丰富SSE的理论，为SSE的产业应用奠定基础。

随着云计算的迅速发展，用户开始将数据迁移到云端服务器。为了保护用户隐私，数据一般以密文形式存储在云端服务器,这使得对密文的高效搜索成为一个挑战性的研究课题。对称可搜索加密（Symmetric Searchable Encryption，SSE）由于支持在密文上进行关键字搜索且效率较高，因而具有重要的科学意义和应用价值。在本项目中，我们首先研究了SSE的多种特性，包括基于向量空间的多关键字复杂逻辑运算、文件的动态更新、搜索用户偏好的量化等，之后我们在具体的场景如医疗云、移动云中探索了其应用。