基于计数布隆过滤器的属性基多关键词可搜索加密方案

李志单; 陈勇群; 王巍

doi:10.11959/j.issn.1000-0801.2023237

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基于计数布隆过滤器的属性基多关键词可搜索加密方案

研究与开发 | 更新时间：2024-06-05

- 基于计数布隆过滤器的属性基多关键词可搜索加密方案
- Attribute-based multi-keyword searchable encryption scheme based on counting Bloom filters
- 电信科学 2023年39卷第11期页码：116-127
- 作者机构：
  
  1. 中国电子科技集团公司第三十六研究所，浙江嘉兴 314033
  2. 电磁空间安全全国重点实验室，浙江嘉兴 314033
- 作者简介：
  
  [ "李志单（1989- ），男，博士，中国电子科技集团公司第三十六研究所工程师，主要研究方向为网络安全、信息安全、公钥密码等" ]
  [ "陈勇群（1987- ），男，博士，中国电子科技集团公司第三十六研究所高级工程师，主要研究方向为网络安全、无线网络安全、网络协议分析" ]
  [ "王巍（1980- ），男，博士，中国电子科技集团公司第三十六研究所研究员、技术创新部主任、电磁空间安全全国重点实验室常务副主任，主要研究方向为无线网络安全、网络协议分析、电子对抗网络安全等" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(U20B2050)
- DOI：10.11959/j.issn.1000-0801.2023237
  中图分类号： TP393
- 网络出版日期：2023-11，
  
  纸质出版日期：2023-11-20
- 稿件说明：
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李志单, 陈勇群, 王巍. 基于计数布隆过滤器的属性基多关键词可搜索加密方案[J]. 电信科学, 2023,39(11):116-127.

Zhidan LI, Yongqun CHEN, Wei WANG. Attribute-based multi-keyword searchable encryption scheme based on counting Bloom filters[J]. Telecommunications science, 2023, 39(11): 116-127.
李志单, 陈勇群, 王巍. 基于计数布隆过滤器的属性基多关键词可搜索加密方案[J]. 电信科学, 2023,39(11):116-127. DOI： 10.11959/j.issn.1000-0801.2023237.

Zhidan LI, Yongqun CHEN, Wei WANG. Attribute-based multi-keyword searchable encryption scheme based on counting Bloom filters[J]. Telecommunications science, 2023, 39(11): 116-127. DOI： 10.11959/j.issn.1000-0801.2023237.

摘要

为解决传统公钥密码体制下的可搜索加密方案检索效率低、关键词索引存储开销大、索引不支持动态更新等问题，基于计数布隆过滤器良好的空间和时间效率判断元素是否属于某个集合的特性，将此特性应用于可搜索加密建立关键词索引，即将关键词集合映射到一个二进制向量中，从而降低关键词存储开销；同时，利用计数布隆过滤器可删除的特性实现关键词索引的动态更新。此外，为防止敌手通过统计分析手段从二进制向量中推断出关键词明文信息，将二进制向量利用置换进行盲化，然后将置换利用属性加密进行秘密共享，合法用户正确生成关键词陷门后，服务商基于用户的关键词陷门帮助用户完成关键词匹配查询。最后，安全性分析和仿真实验证明了方案的安全性和高效性。

Abstract

To address the problems of low retrieval efficiency of searchable encryption scheme under traditional public key cryptosystem

high storage overhead of keyword index

and index does not support dynamic update

based on the good space and time efficiency of counting Bloom filter to determine whether an element belongs to a certain set

the feature into searchable encryption was applied to establish keyword index

thus

the keyword set was mapped into a binary vector

thereby reducing the keyword storage cost.Simultaneously

the feature of counting Bloom filter can be deleted was used to realize the dynamic update of keyword index.In addition

to prevent adversaries from inferring keyword plaintext information from binary vectors through statistical analysis

the binary vector was blinded by permutation

and then the permutation was encrypted by attribute-based encryption for secret sharing.After legitimate users generated keyword traps correctly

the service provider helped users complete keyword matching queries based on the user’s keyword trapdoor.Finally

the security and efficiency of the scheme were proved through security analysis and simulation experiments.

关键词

Keywords

references

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