The Method of Trajectory Privacy Preserving Based on Agent Forwarding Mechanism in Mobile Social Networks
ZHANG Shaobo①④ Md Zakirul Alam Bhuiyan② LIU Qin③ WANG Guojun①⑤
①(School of Information Science and Engineering, Central South University, Changsha 410083, China) ②(Department of Computer and Information Sciences, Temple University, Philadelphia, PA19122, USA) ③(College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China) ④(School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China) ⑤(School of Computer Science and Educational Software, Guangzhou University, Guangzhou 510006, China)
The trajectory K-anonymous is the mainstream of the current trajectory privacy protection, but the method has some defects such as privacy leakage. In this paper, a method of trajectory privacy preserving is proposed Based on Agent Forwarding Mechanism (BAFM) in mobile social networks, which uses secure multi-party computation and inner product secure computation to find the best matching user by the trusted server as the agent. The agent forwards the user’s request to the server to query, which hides the correlation between user’s real trajectory and the server in order to achieve user’s trajectory privacy. Security analysis shows that the propose method can effectively protect the user's trajectory privacy. Experiments show that the proposed method is more effective, it reduces the overhead of server’s query and communication.
张少波, Md Zakirul Alam Bhuiyan,刘琴,孟大程,王国军. 移动社交网络中基于代理转发机制的轨迹隐私保护方法[J]. 电子与信息学报, 2016, 38(9): 2158-2164.
ZHANG Shaobo, Md Zakirul Alam Bhuiyan, LIU Qin, WANG Guojun. The Method of Trajectory Privacy Preserving Based on Agent Forwarding Mechanism in Mobile Social Networks. JEIT, 2016, 38(9): 2158-2164.
LU Rongxing, LIN Xiaodong, LIANG Xiaohui, et al. A dynamic privacy preserving key management scheme for location-based services in vanets[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 13(1): 127-139. doi: 10.1109/TITS.2011.2164068.
HUO Zheng, MENG Xiaofeng, and HUANG Yi. PrivateCheckIn: Trajectory privacy-preserving for check-in services in MSNS[J]. Chinese Journal of Computers, 2013, 36(4): 716-726. doi: 10.3724/SP.J.1016.2013.00716.
[3]
LEI P R, PENG W C, SU I J, et al. Dummy-based schemes for protecting movement trajectories[J]. Journal of Information Science and Engineering, 2012, 28(2): 335-350.
[4]
YOU T H, PENG W C, and LEE W C. Protecting moving trajectories with dummies[C]. Proceedings of the 8th International Conference on Mobile Data Management, Mannheim, Germany, 2007: 278-282. doi: 10.1109/MDM. 2007.58.
[5]
TERROVITIS M and MAMOULIS N. Privacy preservation in the publication of trajectories[C]. Proceedings of the 9th International Conference on Mobile Data Management, Beijing, 2008: 65-72. doi: 10.1109/MDM. 2008.29.
ZHAO Jing, ZHANG Yuan, LI Xinghua, et al. A trajectory privacy protection approach via trajectory frequency suppression[J]. Chinese Journal of Computers, 2014, 37(10): 2096-2106. doi: 10.3724/SP.J.1016.2014.02096.
[7]
HWANG R H, HSUEH Y L, and CHUNG H W. A novel time-obfuscated algorithm for trajectory privacy protection[J]. IEEE Transactions on Services Computing, 2014, 7(2): 126-139. doi: 10.1109/TSC.2013.55.
ZHU Huaijie, WANG Jiaying, WANG Bin, et al. Location privacy preserving obstructed nearest neighbor queries[J]. Journal of Computer Research and Development, 2014, 51(1): 115-125. doi: 10.7544/issn1000-1239.2014.20130694.
YANG Jing, ZHANG Bing, ZHANG Jianpei, et al. Personalized trajectory privacy preserving method based on graph partition[J]. Journal on Communications, 2015, 36(3): 1-11. doi: 10.11959/j.issn.1000-436x.2015053.
WANG Chao, YANG Jing, and ZHANG Jianpei. Privacy preserving algorithm based on trajectory location and shape similarity[J]. Journal on Communications, 2015, 36(2): 144-157. doi: 10.11959/j.issn.1000-436x.2015043.
[11]
XU T and CAI Y. Exploring historical location data for anonymity preservation in location-based services[C]. Proceedings of the 27th International Conference on Computer Communications(INFOCOM 2008), Toronto, Canada, 2008: 547-555. doi: 10.1109/INFOCOM.2008.103.
[12]
GAO Sheng, MA Jianfeng, SHI Weisong, et al. TrPF: a trajectory privacy-preserving framework for participatory sensing[J]. IEEE Transactions on Information Forensics and Security, 2013, 8(6): 874-887. doi: 10.1109/TIFS.2013. 2252618.
[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, Shanghai, China, 2013: 4564-4569. doi: 10.1109/WCNC.2013.6555314.
[14]
GENKIN D, ISHAI Y, and POLYCHRONIADOU A. Efficient multi-party computation: from passive to active security via secure SIMD circuits[C]. Proceedings of the 35th Annual Cryptology Conference, Santa Barbara, USA, 2015: 721-741. doi: 10.1007/978-3-662-48000-7-35.
[15]
ZHU Xiaoyan, LIU Jie, JIANG Shunrong, et al. Efficient weight-based private matching for proximity-based mobile social networks[C]. 2014 IEEE International Conference on Communications, Sydney, Australia, 2014: 4114-4119. doi: 10.1109/ICC.2014.6883965.
[16]
BRINKHOFF T. Generating traffic data[J]. Bulletin of the Technical Committee Data Engineering, 2003, 26(2): 19-25.
[17]
PAN Xiao, XU Jianliang, and MENG Xiaofeng. Protecting location privacy against location-dependent attacks in mobile services[J]. IEEE Transactions on Knowledge and Data Engineering, 2012, 24(8): 1506-1519. doi: 10.1109/TKDE. 2011.105.
[18]
WANG Yu, XU Dingbang, HE Xiao, et al. L2p2: Location-aware location privacy protection for location-based services[C]. Proceedings IEEE INFOCOM, Orlando, Florida USA, 2012: 1996-2004. doi: 10.1109/INFOCOM.2012. 6195577.