基于马尔可夫模型的同态加密位置隐私保护方案

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

Chinese Journal of Network and Information Security ›› 2017, Vol. 3 ›› Issue (1): 54-60.doi: 10.11959/j.issn.2096-109x.2017.00137

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Homomorphic encryption location privacy-preserving scheme based on Markov model

Kai ZHOU^1,^2,³,Chang-gen PENG^2,³(),Yi-jie ZHU^3,⁴,Jian-qiong HE^1,^2,³

¹ College of Computer Science and Technology, Guizhou University, Guiyang 550025, China
² Guizhou Provincial Key Laboratory of Public Big Data, GuiZhou University, Guiyang 550025, China
³ Institute of Cryptography＆Data Security, Guizhou University, Guiyang 550025, China
⁴ Guizhou Provincial Engineering and Technology Research Center of Cyber Data Security, Guiyang 550025, China

Revised:2016-12-27 Online:2017-01-15 Published:2020-03-20
Supported by:
The National Natural Science Foundation of China(61262073);The National Natural Science Foundation of China(61662009);The Philosophy and SocialSciences Planning Project of Guizhou Province(16GZQN06);The Science and Technology Foundation of GuizhouProvince(黔科合基础[2016]1023);The Graduate Innovation Foundation of Guizhou University(2016050)

Abstract

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.

Key words: location-based services, Markov chain, homomorphic encryption, anonymity, inquiry privacy

CLC Number:

TP302

Kai ZHOU,Chang-gen PENG,Yi-jie ZHU,Jian-qiong HE. Homomorphic encryption location privacy-preserving scheme based on Markov model[J]. Chinese Journal of Network and Information Security, 2017, 3(1): 54-60.

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References 17

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Homomorphic encryption location privacy-preserving scheme based on Markov model

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