【摘要】 随着云计算的日益普及,越来越多的用户通过云来存储数据,从而降低本地数据存储和管理的成本。为了保护隐私性,敏感数据在上传到云之前需要进行加密处理,这势必降低数据的利用率,使得数据搜索变得困难。执行搜索操作时,还要根据查询关键词与文件之间的相关度,返回相关度较高的文件。此外,为了防止云服务器返回错误的搜索结果,需要支持对搜索结果的可验证。针对以上问题,文章提出一种支持可验证的关键词排序搜索方案。该方案基于向量空间模型和TF×IDF模型构造索引向量和查询向量。采用基于树的索引结构,利用深度优先搜索算法和剪枝策略实现关键词排序搜索。文章设计了基于MAC的可验证机制来验证返回文件的正确性。安全性分析和性能分析表明提出的方案是安全高效的。更多还原

【Abstract】 With the increasing popularity of cloud computing, more and more users upload their data into the cloud server, thus reducing the cost of local data storage and management. In order to protect privacy, sensitive data need to be encrypted before uploaded to the cloud server, which will inevitably reduce the utilization of data and make data search difficult. When performing the search operation, the files with high relevance scores are returned according to the relevance score between the query keyword and the file. In addition, the data user should be able to check the correctness of search results to prevent cloud server from returning the invalid results. In view of the above problems, this paper proposes a verifiable keywords ranked search scheme. This scheme constructs the index vector and query vector based on vector space model and TF×IDF model. Using tree-based index structure, this paper uses depth first search algorithm and pruning strategy to achieve keywords ranked search. This scheme verifies whether the search result is valid based on MAC mechanism. Security analysis and performance analysis show that this scheme is secure and efficient.更多还原