基于布隆过滤器属性基的多关键词可搜索方案

在云计算环境下，基于属性加密的多关键词可搜索加密能够同时实现对加密数据的访问控制和加密数据可搜索。为提高密文检索效率、降低关键词索引代价，本文提出一种基于布隆过滤器属性基的多关键词搜索方案。首先，对于文件关键词集合，利用布隆过滤器生成对应于关键词集合的固定长度索引向量，从而降低关键词索引的存储复杂度。然后，为防止敌手对索引的统计分析，利用置换将索引向量中元素随机化，同时利用属性加密技术将此置换进行共享，只有合法用户才能获取此置换并构建查询关键词的陷门。最后，通过安全性分析和实验分析，表明本文方案的安全性、高效性和实用性。

An Attribute-based Multi-keyword Searchable Scheme Based on Bloom Filters

Under the cloud computing environment, the attribute-based encryption multi-keyword searchable encryption can realize access control and searchability of encrypted data at the same time. For improving the retrieval efficiency of encrypted databases and reducing the cost of file keyword retrieval index storage, this article proposes an attribute-based multi-keyword search scheme based on Bloom filters. First, for the keywords set of a file, the Bloom filter is used to generate a fixed length index vector corresponding to the keyword set, so as to reduce the storage complexity of the keyword index. Besides, in order to prevent the adversary from obtaining the keywords information by means of statistical analysis of the index, this paper uses a permutation to randomize the elements of the index vector, and uses the attribute-based encryption to share the permutation. Thus, only legitimate users can obtain the permutation and construct a trapdoor for querying keywords with the permutation. Finally, through the security analysis and experimental analysis, the security, efficiency and practicability of this scheme are showed.