Abstract: Focusing on the shortages of existing ciphertext retrieval schemes in cloud computing, such as not supporting semantic extension of retrieval keyword, low accuracy and not ranking search results, a ranked ciphertext retrieval scheme supporting semantic extension of retrieval keyword was proposed. Firstly, Term Frequency-Inverse Document Frequency (TF-IDF) method was used to calculate the relevance scores between keywords and documents, and different weights were set for keywords in different document domains. The position weight scores of keywords in different document domains were calculated based on domain-weighted scoring method. The value of keyword corresponding position on document index vector was set as the product of position weight score and relevance score. Secondly, according to WordNet semantic Web, semantic extension was performed on retrieval keywords that input by the authorized users, and edit distance formula was used to calculate the similarity among semantic extension keywords, and the value of retrieval keyword corresponding position on document retrieval vector was set as similarity value. Finally, security index and document retrieval trapdoors were generated by encryption, and the inner product operation was performed based on Vector Space Model (VSM), and the result of ciphertext retrieval documents was sorted by the value of inner product operation. The theoretical analysis and experimental simulations show that the proposed scheme is safe under the known ciphertext model and the known background knowledge model, and has the ability to sort the search results. Compared with Multi-keyword Ranked Search over Encrypted cloud data (MRSE) scheme, the proposed scheme supports keyword semantic extension, and is more accurate and reliable than MRSE, while the retrieval time is not much different from MRSE scheme.

Key words: cloud computing, semantic extension, position weight, relevance, similarity, ciphertext retrieval

摘要： 针对云计算环境下已有的密文检索方案不支持检索关键词语义扩展、精确度不够、检索结果不支持排序的问题，提出一种支持检索关键词语义扩展的可排序密文检索方案。首先，使用词频逆文档频率（TF-IDF）方法计算文档中关键词与文档之间的相关度评分，并对文档不同域中的关键词设置不同的位置权重，使用域加权评分方法计算位置权重评分，将相关度评分与位置权重评分的乘积设置为关键词在文档索引向量上相应位置的取值；其次，根据WordNet语义网对授权用户输入的检索关键词进行语义扩展，得到语义扩展检索关键词集合，使用编辑距离公式计算语义扩展检索关键词集合中关键词之间的相似度，并将相似度值设置为检索关键词在文档检索向量上相应位置的取值；最后，加密产生安全索引和文档检索陷门，在向量空间模型（VSM）下进行内积运算，以内积运算的结果为密文检索文档的排序依据。理论分析和实验仿真表明，所提方案在已知密文模型和已知背景知识模型下是安全的，且具备对检索结果的排序能力；与多关键字密文检索结果排序（MRSE）方案相比，所提方案支持关键词语义扩展，查询准确率比MRSE方案更加准确可靠，而检索时间则与MRSE方案相差不大。

关键词: 云计算, 语义扩展, 位置权重, 相关度, 相似度, 密文检索