加密云数据下基于Simhash的模糊排序搜索方案

发布时间：2018-05-30 15:00

本文选题：云计算 + 加密云数据　；参考：《计算机学报》2017年02期

【摘要】：为了保护数据隐私,数据拥有者会将敏感数据的密文外包到云服务器,这使得传统明文搜索技术难以使用.因此可搜索加密技术被用于对密文数据进行搜索,实现高效的数据利用.然而目前在加密云数据中,关键词模糊搜索方案主要是通过构造关键词模糊集合来实现,其需要大量的计算和存储开销.本文提出的搜索方案,无需构造关键词模糊集合,而是基于Simhash的降维思想,将文档关键词做n-gram处理并得到Simhash指纹来实现模糊搜索.该文结合汉明距离和关键词相关度分数,设计了双因子排序算法对查询结果进行排序.使用树索引结构和新型遍历方法进一步提高了搜索效率.通过新型遍历方法,即使树的节点值与期望值不相等,也能够对树进行遍历.理论分析和实验结果表明:该方案实现了加密云数据下的关键词模糊搜索,同时极大地节约了时间和空间成本.
[Abstract]:In order to protect data privacy, data owners outsource ciphertext of sensitive data to cloud servers, which makes it difficult for traditional plaintext search technology to use. Therefore searchable encryption technology is used to search ciphertext data to achieve efficient data utilization. However, in encrypted cloud data, keyword fuzzy search scheme is mainly implemented by constructing fuzzy set of keywords, which requires a large amount of computation and storage overhead. The search scheme proposed in this paper does not need to construct the fuzzy set of keywords, but based on the dimensionality reduction idea of Simhash, the document keywords are processed by n-gram and the Simhash fingerprint is obtained to realize the fuzzy search. Combining hamming distance and keyword correlation score, a two-factor sorting algorithm is designed to sort the query results. The search efficiency is further improved by using tree index structure and new traversal method. Through the new traversal method, the tree can be traversed even if the node value is not equal to the expected value. The theoretical analysis and experimental results show that the proposed scheme realizes the keyword fuzzy search under encrypted cloud data and saves the cost of time and space greatly at the same time.
【作者单位】：福州大学数学与计算机科学学院;网络系统信息安全福建省高校重点实验室;福州大学物理与信息工程学院;
【基金】：国家自然科学基金(61402112,61472307,61472309,61303198) 福建省教育厅科技项目(JA12028) 福建省重大科技项目(2015H6013) 福州大学科技发展基金项目(2012-XY-17)资助~~
【分类号】：TP309

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