ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2019, Vol. 56 ›› Issue (10): 2193-2206.doi: 10.7544/issn1000-1239.2019.20190378

所属专题: 2019密码学与智能安全研究专题

• 信息安全 • 上一篇    下一篇



  1. (东华大学计算机科学与技术学院 上海 201620) (
  • 出版日期: 2019-10-16
  • 基金资助: 

Multi-Keyword Searchable Encryption Algorithm Based on Semantic Extension

Xu Guangwei, Shi Chunhong, Wang Wentao, Pan Qiao, Li Feng   

  1. (College of Computer Science and Technology, Donghua University, Shanghai 201620)
  • Online: 2019-10-16

摘要: 云存储中为保护数据所有者的数据安全性和隐私性,采用数据加密后再提供按需数据服务的方式,可搜索加密技术是解决加密数据接入的关键方法.但搜索时的多关键词不加区别和忽视索引之间的关联性会造成搜索时间长和准确率低等问题,提出一种基于语义扩展的多关键词可搜索加密算法.首先,基于依存句法区分多关键词的重要性进行语义扩展,并生成多关键词陷门;其次,基于凝聚层次聚类和关键词平衡二叉树,构建索引关联性的索引树结构;最后,引入剪枝参数和相关性得分阈值对索引树进行剪枝,在索引树中过滤掉索引无关的子树.基于真实数据集的理论和实验分析表明:所提算法能够抵抗规模分析攻击,并能提高搜索时间效率和搜索准确率.

关键词: 云存储, 可搜索加密, 语义扩展, 依存句法, 凝聚层次聚类

Abstract: In cloud storage, to protect the data security and privacy of data owners, data encryption is used to provide on-demand data services. Searchable encryption technology is the key method to solve encrypted data access. However, the multi-keywords in search do not distinguish and ignore the correlation between indexes, which will cause long search time and low accuracy. To this end, this paper proposes a multi-keyword searchable encryption algorithm based on semantic extension. Firstly, the dependency syntax is based on to distinguish the importance of multiple keywords for semantic expansion, and generate multiple keyword trapdoors. Secondly, the condensed hierarchical clustering and the keyword balanced binary tree are based on, and the index tree structure of index relevance is constructed. Finally, the pruning parameter and the correlation score threshold are introduced to prune the index tree, and the index-independent subtree is filtered out in the index tree. Theoretical and experimental analysis based on real data sets shows that the proposed algorithm can resist scale analysis attacks and improve search time efficiency and search accuracy.

Key words: cloud storage, searchable encryption, semantic extension, dependency grammar, condensed hierarchical clustering