关键词: 云存储, 多关键字搜索, 词频-逆向文件频率, 向量空间模型, 聚类, 隐私保护

Abstract: Aiming at the problem of low efficiency and lack of adaptive ability for the existing multi-keyword ciphertext search methods in cloud storage environment, a Multi-keyword Ranked Search over Encrypted cloud data based on Improved Quality Hierarchical Clustering (MRSE-IQHC) method was proposed. Firstly, the document vectors were constructed by Term Frequency-Inverse Document Frequency (TF-IDF) method and Vector Space Model (VSM). Secondly, the Improved Quality Hierarchical Clustering (IQHC) algorithm was proposed to cluster the document vectors, the document index and cluster index were constructed. Thirdly, the K-Nearest Neighbor (KNN) query algorithm was used to encrypt the indexes. Finally, the user-defined keyword weight was used to construct the search request and search for the top k relevant documents in ciphertext state. The experimental results show that compared with the Multi-keyword Ranked Search over Encrypted cloud data (MRSE) method and the Multi-keyword Ranked Search over Encrypted data based on Hierarchical Clustering Index (MRSE-HCI) method, the search time was shortened by 44.3% and 34.2%, 32.4% and 13.2%, 36.9% and 19.4% in the same number of search documents, retrieved documents and search keywords conditions, and the accuracy rate was increased by 10.8% and 8.6%. The proposed method MRSE-IQHC has high search efficiency and accuracy for multi-keyword ciphertext search in cloud storage environment.

Key words: cloud storage, multi-keyword search, Term Frequency-Inverse Document Frequency (TF-IDF), Vector Space Model (VSM), clustering, privacy protection