Due to increasing volume of stored data in organizations, data owners upload their data to cloud servers. Sensitive data has to be encrypted prior to uploading to the cloud server because of security requirements. Therefore, capable of searching over the encrypted cloud data is a very important issue. One of the most important challenges that must be addressed is to search whole documents to find related documents to a query. In this paper, a scheme is suggested to eliminate the need of searching for whole documents. A secure multi-keyword ranked search method over the encrypted cloud data is introduced that provides dynamic operation on the document collection. Also, access control mechanism is considered in the proposed scheme. The vector space model is employed to B+tree index and query creating. Due to generation of a B+tree-based index structure, search time is getting sub-linear. First, the cloud server is assumed to be “Honest-but-Curious”. Second, it is considered that the data are stored on an untrusted cloud server. The Merkle B-tree (MB-tree) is utilized to verify search results in the presence of access control rules when the cloud server is untrusted. Experiments are conducted using the real world dataset to confirm efficiency and precision of the offered scheme.

由于组织中存储的数据量不断增加，数据所有者将他们的数据上传到云服务器。由于安全要求，敏感数据必须在上传到云服务器之前进行加密。因此，能够搜索加密的云数据是一个非常重要的问题。必须解决的最重要挑战之一是搜索整个文档以查找与查询相关的文档。在本文中，提出了一种方案来消除搜索整个文档的需要。介绍了一种对加密云数据的安全多关键字排序搜索方法，该方法提供了对文档集合的动态操作。此外，在所提出的方案中考虑了访问控制机制。B+树索引和查询创建采用向量空间模型。由于生成了基于 B+树的索引结构，搜索时间变得次线性。首先，假设云服务器是“诚实但好奇的”。其次，认为数据存储在不受信任的云服务器上。Merkle B-tree (MB-tree) 用于在云服务器不受信任时验证存在访问控制规则的搜索结果。使用真实世界数据集进行实验以确认所提供方案的效率和精度。