基于马尔可夫模型的同态加密位置隐私保护方案

周凯; 彭长根; 朱义杰; 何建琼

doi:10.11959/j.issn.2096-109x.2017.00137

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基于马尔可夫模型的同态加密位置隐私保护方案

学术论文 | 更新时间：2024-06-03

- 基于马尔可夫模型的同态加密位置隐私保护方案
- Homomorphic encryption location privacy-preserving scheme based on Markov model
- 网络与信息安全学报 2017年3卷第1期页码：54-60
- 作者机构：
  
  1. 贵州大学计算机科学与技术学院，贵州贵阳 550025
  2. 贵州大学贵州省公共大数据重点实验室，贵州贵阳 550025
  3. 贵州大学密码学与数据安全研究所，贵州贵阳 550025
  4. 贵州省网络数据保密工程技术研究中心，贵州贵阳 550025
- 作者简介：
  
  [ "周凯（1991-），男，浙江衢州人，贵州大学硕士生，主要研究方向为密码学与可信计算。" ]
  [ "彭长根（1963-），男，贵州锦屏人，博士，贵州大学教授、博士生导师，主要研究方向为密码学、信息安全。" ]
  [ "朱义杰（1989-），男，山东临沂人，贵州大学硕士生，主要研究方向为密码学与可信计算。" ]
  [ "何建琼（1991-），贵州遵义人，贵州大学硕士生，主要研究方向为密码学与安全协议。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61262073);国家自然科学基金资助项目;The National Natural Science Foundation of China(61662009);贵州省哲学社会科学规划青年课题基金资助项目;The Philosophy and SocialSciences Planning Project of Guizhou Province(16GZQN06);贵州省科技基金计划基金资助项目;The Science and Technology Foundation of GuizhouProvince(黔科合基础[2016]1023);贵州大学研究生创新基金资助项目;Graduate Innovation Foundation of Guizhou University(2016050)
- DOI：10.11959/j.issn.2096-109x.2017.00137
  中图分类号： TP302
- 网络首发：2017-01，
  
  纸质出版：2017-01-15
- 稿件说明：
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周凯, 彭长根, 朱义杰, 等. 基于马尔可夫模型的同态加密位置隐私保护方案[J]. 网络与信息安全学报, 2017,3(1):54-60.

Kai ZHOU, Chang-gen PENG, Yi-jie ZHU, et al. Homomorphic encryption location privacy-preserving scheme based on Markov model[J]. Journal of network and information security, 2017, 3(1): 54-60.
周凯, 彭长根, 朱义杰, 等. 基于马尔可夫模型的同态加密位置隐私保护方案[J]. 网络与信息安全学报, 2017,3(1):54-60. DOI： 10.11959/j.issn.2096-109x.2017.00137.

Kai ZHOU, Chang-gen PENG, Yi-jie ZHU, et al. Homomorphic encryption location privacy-preserving scheme based on Markov model[J]. Journal of network and information security, 2017, 3(1): 54-60. DOI： 10.11959/j.issn.2096-109x.2017.00137.

摘要

针对基于位置服务的位置隐私与查询隐私保护问题，提出一种基于马尔可夫模型的同态加密位置隐私保护方案。首先，随机置换匿名用户真实身份，结合用户的历史查询内容，构建马尔可夫状态转移矩阵；其次，预查询用户的历史高频率内容及马尔可夫链下的预测内容，并且存储相应结果集；最后，对该方案双预测系统的安全性进行了分析。该方案使服务器满足k+1个查询内容，并使恶意服务器或攻击者无法判定查询用户的真实身份与查询内容之间的对应关系，实现了用户位置隐私与查询隐私的保护。同时，利用同态加密密文的可计算性和保密性，实现了面向密文数据的统计分析和隐私数据的安全存储。

Abstract

Homomorphic encryption location privacy-preserving scheme based on Markov mode was proposed to solve the problem of location privacy and query privacy protection in location-based service systems. Firstly

the anonymous user's identity were permuted randomly and the Markov state transition matrix combining with the user's historical query content was constructed. Secondly

system previously queries the user's high frequency con-tent and the prediction content under Markov chain

then store the corresponding result sets. Finally

the security of the scheme's double prediction system was analyzed. The scheme makes the LBS receives k+1 query contents which let malicious server or attacker can't determine the corresponding relation between queried user's real identity and queried content. So the user's location privacy and query privacy can be protected. Meanwhile

the computability and confidentiality of homomorphic encryption ciphertext were used to realize the statistical analysis of cipher-text-oriented data and the secure storage of private data.

关键词

Keywords

references

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