Homomorphic encryption location privacy-preserving scheme based on Markov model

Kai ZHOU; Chang-gen PENG; Yi-jie ZHU; Jian-qiong HE

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

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Homomorphic encryption location privacy-preserving scheme based on Markov model

Academic paper | 更新时间：2024-06-03

- Homomorphic encryption location privacy-preserving scheme based on Markov model
- Journal of network and information security Vol. 3, Issue 1, Pages: 54-60(2017)
- 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：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2017.00137
  CLC： TP302
- Online First：2017-01，
  
  Published：15 January 2017
- 稿件说明：
移动端阅览
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：

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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