[1]杨清琳,黄治国,钱文标,等.云计算下支持语义的可搜索加密方法研究[J].计算机技术与发展,2020,30(03):111-116.[doi:10. 3969 / j. issn. 1673-629X. 2020. 03. 021]
　YANG Qing-lin,HUANG Zhi-guo,QIAN Wen-biao,et al.Research on Searchable Encryption Method with Supporting Semantics in Cloud Computing[J].Computer Technology and Development,2020,30(03):111-116.[doi:10. 3969 / j. issn. 1673-629X. 2020. 03. 021]
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云计算下支持语义的可搜索加密方法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年03期
页码:
111-116
栏目:
安全与防范
出版日期:
2020-03-10

文章信息/Info

Title:
Research on Searchable Encryption Method with Supporting Semantics in Cloud Computing
文章编号:
1673-629X(2020)03-0111-06
作者:
杨清琳1; 黄治国2; 钱文标1; 杨晓雷1
1. 广西财经学院 现代教育技术部,广西 南宁 530003; 2. 河南工程学院 计算机学院,河南 郑州 451191
Author(s):
YANG Qing-lin1; HUANG Zhi-guo2; QIAN Wen-biao1; YANG Xiao-lei1
1.Department of Modern Education Technology,Guangxi University of Finance and Economics, Nanning 530003,China; 2.School of Computer Science,Henan University of Engineering,Zhengzhou 451191,China
关键词:
云计算; 可搜索加密; 语义扩展; 本体知识库; 语义相似度; 标记向量
Keywords:
cloud computing; searchable encryption; semantic expansion; ontology knowledge base; semantic similarity mark vector
分类号:
TP391
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 03. 021
摘要:
传统的云计算下的可搜索加密算法没有对查询关键词进行语义扩展,导致了用户查询意图与返回结果存在语义 偏差,并且对检索结果的相关度排序不够合理,无法满足用户对智能搜索的需求。 对此,提出了一种支持语义的可搜索加 密方法。 该方法利用本体知识库实现了用户查询的语义拓展,并通过语义相似度来控制扩展词的个数,防止因拓展词过 多影响检索的精确度。 同时,该方法利用文档向量、查询向量分块技术构造出对应的标记向量,以过滤无关文档,并在查 询-文档的相似度得分中引入了语义相似度、关键词位置加权评分及关键词-文档相关度等影响因子,实现了检索结果的 有效排序。 实验结果表明,该方法在提高检索效率的基础上显著改善了检索结果的排序效果,提高了用户满意度。
Abstract:
The traditional searchable encryption(SE) algorithm in cloud computing doesn’t extend the query keywords semantically, which leads to the semanticdeviation between the query intention and thereturned result,and the inordinate relevance of the search results is not reasonable enough? ? to meet the needs of users for intelligent search. In this study,a SE method of supporting semantics is proposed. The ontology knowledge base is used to realize the semantic extension of user query,and the number of extended words by semantic similarity is seriously controlled to improve the retrieval accuracy without overextending words. Furthermore,by using document vector and query vector block technology,the corresponding marker vector is constructed to filter irrelevant documents,and semantic similarity, keyword location weighted score and keyword-document relevancy are introduced into query-document similarity score,so as to effectively sort the retrieval results. The experiment shows that the proposed method can significantly increase the retrieval efficiency and improve the user’s satisfaction.

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更新日期/Last Update: 2020-03-10