东北大学学报:自然科学版 ›› 2019, Vol. 40 ›› Issue (7): 913-919.DOI: 10.12068/j.issn.1005-3026.2019.07.001

• 信息与控制 •    下一篇

一种面向密文大型数据集的可搜索加密方案

贾强, 张帅, 周福才   

  1. (东北大学 软件学院, 辽宁 沈阳110169)
  • 收稿日期:2018-06-04 修回日期:2018-06-04 出版日期:2019-07-15 发布日期:2019-07-16
  • 通讯作者: 贾强
  • 作者简介:贾强(1989-),男,江苏徐州人,东北大学博士研究生; 周福才(1964-),男,辽宁沈阳人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(61772127,61472184); 国家科技重大专项(2013ZX03002006); 辽宁省科技攻关项目(2013217004); 中央高校基本科研业务费专项资金资助项目(N151704002).

A Searchable Encryption Scheme for Encrypted Large Data Sets

JIA Qiang, ZHANG Shuai, ZHOU Fu-cai   

  1. School of Software, Northeastern University, Shenyang 110169, China.
  • Received:2018-06-04 Revised:2018-06-04 Online:2019-07-15 Published:2019-07-16
  • Contact: ZHOU Fu-cai
  • About author:-
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摘要: 为解决可搜索加密方案中由于安全索引过大而导致的关键词搜索时间复杂度过高这一问题,结合云存储应用环境,提出了一种面向密文大型数据集的可搜索加密方案.针对云存储环境中数据集过大的用户,使用块状存储结构优化安全索引的数据结构,将安全索引按照分块参数分为Small,Medium,Large三类.在关键词搜索过程中采用间接寻址的方式,使得在安全索引过大的情况下,仍然能保持良好的搜索时间复杂度,达到用户可接受的范围.实验结果表明,随着安全索引的增大,关键词搜索时间达到了亚线性.

关键词: 可搜索加密, 倒排索引, 云存储, 文件加密, 大型数据集

Abstract: In order to solve the problem of high keywords-search time-complexity caused by excessive security indexes in symmetric searchable encryption scheme, combined with the cloud storage application environment, a new searchable encryption (SE) scheme for encrypted large data sets in distributed environments was presented. The scheme was aimed at data owners who have large sizes of files in the cloud storage application environment. By using block storage structure to optimize the structure of security index, the security indexes were divided into three categories: Small, Medium, and Large, according to the block parameters. And with the method of register indirect addressing, the scheme can maintain good search time complexity in the case of large security index, and be acceptable for users. The experimental result shows that the keyword search time reaches sublinearity as the security index increases.

Key words: searchable encryption, inverted index, cloud storage, file encryption, large data sets

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