Research on Location Privacy Protection Scheme Based on Similar Trajectory Replacement

doi:10.13190/j.jbupt.2019-031

Journal of Beijing University of Posts and Telecommunications ›› 2020, Vol. 43 ›› Issue (1): 135-142.doi: 10.13190/j.jbupt.2019-031

• Reports • Previous Articles

Research on Location Privacy Protection Scheme Based on Similar Trajectory Replacement

SONG Cheng, ZHANG Ya-dong, PENG Wei-ping, WANG Lei, LIU Zhi-zhong

School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, China

Received:2019-02-28 Online:2020-02-28 Published:2020-03-27
Supported by:

Abstract

Abstract: Aiming at the problem of privacy leakage of mobile terminal users in location based service, a location privacy protection scheme is proposed based on similar trajectory replacement query. In this scheme, identities of the requesting user and all the candidates are annonymized. By adopting the similar trajectory function to calculate the trajectory similarities between all the candidates and the requesting user at certain time intervals, the optimal candidate with highest similarity is selected to represent requesting user in requesting LBS. So the identities of the requesting user. The privacy of queries and the trajectories is protected. Security analyses prove that the scheme satisfies such security features as anonymity, unforgeability, and resisting continuous query service tracking attack. Simulation shows that the proposed scheme effectively improves the trajectory similarity of the optimal candidate and the efficiency of the best candidate selection.

Key words: location based services, similar trajectory, privacy protection, query-replace

CLC Number:

TP309

SONG Cheng, ZHANG Ya-dong, PENG Wei-ping, WANG Lei, LIU Zhi-zhong. Research on Location Privacy Protection Scheme Based on Similar Trajectory Replacement[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(1): 135-142.

References

[1] Huang Haosheng. Progress in location-based services 2014[J]. Lecture Notes in Geoinformation and Cartography, 2016, 46(6):0463.
[2] Sun Yanming, Chen Min, Hu Long, et al. ASA:against statistical attacks for privacy-aware users in location based service[J]. Future Generation Computer Systems, 2017(70):48-58.
[3] He Wen. Research on LBS privacy protection technology in mobile social networks[C]//IEEE, Advanced Information Technology, Electronic and Automation Control Conference. New York:IEEE Press, 2017:73-76.
[4] Huo Zheng, Meng Xiaofeng. A Survey of trajectory privacy-preserving techniques[J]. Chinese Journal of Computers, 2011, 34(10):1820-1830.
[5] Naghizade E, Bailey J, Kulik L, et al. How private can i be among public users[C]//UbiComp2015, the 2015 ACM International Joint Conference. Osaka, ACM, 2015:1137-1141.
[6] Zhang Yuan, Chen Qingjun, Zhong Sheng. Privacy-preserving data aggregation in mobile phone sensing[J]. IEEE Transactions on Information Forensics & Security, 2016, 11(5):980-992.
[7] 万盛, 李凤华, 牛犇, 等. 位置隐私保护技术研究进展[J]. 通信学报, 2016, 37(12):124-141. Wansheng, Li Fenghua, Niu Ben, et al. Research progress on location privacy-preserving techniques[J]. Journal on Communications, 2016, 37(12):124-141.
[8] Lee Ken C K, Zheng Baihua, Chen C, et al. Efficient index-based approaches for skyline queries in location-based applications[J]. IEEE Transactions on Knowledge and Data Engineering, 2013, 25(11):2507-2520.
[9] Pan Xiao, Meng Xiaofeng, Xu Jianliang. Distortion-based anonymity for continuous queries in location-based mobile services[C]//ACM Sigspatial International Symposium on Advances in Geographic Information Systems. Washington:DBLP, 2009:256-265.
[10] Freudiger J, Shokri R, Hubaux J P. On the optimal placement of mix zones[C]//International Symposium on Privacy Enhancing Technologies. Springer, Berlin:Springer-Verlag, 2009:216-234.
[11] Kato R, Iwata M, Hara T, et al. A dummy-based anonymization method based on user trajectory with pauses[C]//International Conference on Advances in Geographic Information Systems. New York:ACM, 2012:249-258.
[12] 霍峥, 孟小峰, 黄毅. PrivateCheckIn:一种移动社交网络中的轨迹隐私保护方法[J]. 计算机学报, 2013, 36(4):716-726. Huo Zhen, Meng Xiaofeng, Huang Yi. PrivateCheckIn:a trajectory privacy preserving method in mobile social networks[J]. Journal of Computer Science, 2013, 36(4):716-726.
[13] Niu Ben, Zhu Xiaoyan, Chi Haotian, et al. 3PLUS:Privacy-preserving pseudo-location updating system in location-based services[C]//2013 IEEE Wireless Communications and Networking Conference. New York:IEEE, 2013:1-8.
[14] Chen Rui, Benjamin C. M. Fung, Noman Mohammed, et al. Privacy-preserving trajectory data publishing by local suppression[J]. Information Sciences, 2013, 231(1):83-97.
[15] 赵婧, 张渊, 李兴华, 等. 基于轨迹频率抑制的轨迹隐私保护方法[J]. 计算机学报, 2014, 37(10):2096-2106. Zhao Jing, Zhang Yuan, Li Xinghua, et al. Trajectory privacy preserving method based on trajectory frequency suppression[J]. Acta Computer Science, 2014, 37(10):2096-2106.
[16] 李凤华, 张翠, 牛犇, 等. 高效的轨迹隐私保护方案[J]. 通信学报, 2015, 36(12):114-123. Li Fenghua, Zhang Cui, Niu Ben, et al. Efficient trajectory privacy protection scheme[J]. Journal on Communications, 2015, 36(12):114-123.
[17] Ye A, Li Yacheng, Li Xu. A novel location privacy-preserving scheme based on l-queries for continuous LBS[J]. Computer Communications, 2016:1-10.
[18] Sun Gang, Liao Dan, Li Hui, et al. L2P2:A location-label based approach for privacy preserving in LBS[J]. Future Generation Computer Systems, 2017, 74:375-384.
[19] Li Xinghua, Miao MeiXia, Liu Hai, et al. An incentive mechanism for K-anonymity in LBS privacy protection based on credit mechanism[J]. Soft Computing, 2017, 21(14):3907-3917.
[20] Lam T, Rietsch K. Total positivity, Schubert positivity, and geometric Satake[J]. Journal of Algebra, 2016, 460:284-319.

Research on Location Privacy Protection Scheme Based on Similar Trajectory Replacement

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 11

Recommended Articles

Metrics

Comments

[1]	SONG Cheng, CHENG Daochen, NI Shuiping. k Anonymous Trajectory Privacy Protection Scheme of Personalized Differential Privacy [J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(3): 109-114.
[2]	. Trusted predictive cache architecture for Internet of vehicles privacy protection combined with blockchain [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(6): 145-150.
[3]	SONG Cheng, XU Biao, HE Junyi. Differential Privacy Trajectory Data Protection Scheme [J]. Journal of Beijing University of Posts and Telecommunications, 2022, 45(1): 13-18.
[4]	MEI Ya-xin, SHEN Xue-wei, ZHAO Dan, WANG Tian. An Edge-Based Differential Method for Data Protection in Sensor-Cloud [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(4): 48-53,75.
[5]	LI Tao, ZHANG Jing, YANG Hao. Analysis and Improvement of Privacy Protection Scheme in VANET [J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(1): 104-110.
[6]	DUAN Yu-cong, ZHANG You-liang, BAI Yong, CAO Chun-jie. Privacy Protection Strategy for Implicit Typed Resources [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(4): 121-125.
[7]	SONG Cheng, ZHANG Ya-dong, WANG Lei, LIU Zhi-zhong, CHAO Hao. Trajectory Privacy Protection Scheme Based on DTW Exchange Query [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2018, 41(6): 97-102.
[8]	DU Hui-ying, DU Wu-gong. Optimization Strategy of Efficient Periodic Mobile Location [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(6): 80-85.
[9]	SONG Cheng, ZHANG Ming-yue, PENG Wei-ping, JIA Zong-pu, LIU Zhi-zhong. Privacy Protection Mechanism Based on Secure Multi-party Computation in VANET [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(3): 67-71.
[10]	LI Meng-xing, FENG Quan, YANG Mei, ZHAO Jian, HE Kang. Garbled Circuits Based Alignment-Free Fingerprint Matching [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2014, 37(6): 81-85.
[11]	ZHU Zhen-rong, LI Hui, YANG Yi-xian . An Improved Secure Electronic Payment Protocol Based on Account [J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2006, 29(s2): 155-159.