Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (24): 90-96.

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Fuzzy keyword search over encrypted cloud data

WU Yang, LIN Bogang, YANG Yang, CHEN Hefeng   

  1. 1.College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
    2.Key Lab of Information Security of Network System, Fuzhou University, Fuzhou 350108, China
  • Online:2015-12-15 Published:2015-12-30

加密云数据下的关键词模糊搜索方案

吴  阳,林柏钢,杨  旸,陈何峰   

  1. 1.福州大学 数学与计算机科学学院,福州 350108
    2.网络系统信息安全福建省高校重点实验室,福州 350108

Abstract: Traditional fuzzy keyword search over encrypted cloud data can search the related documents, however, the search results are not satisfactory. When the user enters correctly, it can not complete similarity search; when the user spelling errors occur, the returned result contains a large number of unrelated documents, seriously wasting bandwidth resources. According to the drawback of the current fuzzy keyword over encrypted cloud data, this paper proposes a novel fuzzy keyword search scheme. Keyword relevance score is calculated and sorted according to the document relevance score, and the top-k documents are returned to the user, reducing unnecessary waste of bandwidth and user time consuming to find effective documentation, providing more effective search results. By introducing dummy trapdoors, increasing the cloud server for document analysis keyword difficulty, the system increases the privacy protection.

Key words: encrypted cloud data, cloud computing secure, searchable encryption, fuzzy keyword search

摘要: 对于加密云数据的搜索,传统的关键词模糊搜索方案虽然能搜索到相关文档,但是搜索的结果并不令人满意。在用户输入正确的情况下,无法完成近似搜索,当用户出现拼写错误时,返回的结果中包含大量无关关键词文档,严重浪费了带宽资源。针对目前在加密云数据下关键词模糊搜索的缺陷,提出了一种新型的关键词模糊搜索方案,通过对关键词计算相关度分数并对文档根据相关度分数进行排序,将top-k(即相关度最高的k个文档)个文档返回给搜索用户,减少了不必要的带宽浪费和用户寻找有效文档的时间消耗,提供了更加有效的搜索结果,并且通过引入虚假陷门集,增大了云服务器对文档关键词的分析难度,增加了系统的隐私性保护。

关键词: 加密云数据, 云计算安全, 可搜索加密, 模糊搜索