Location based service location privacy protection method based on location security in augmented reality
YANG Yang1, WANG Ruchuan2,3
1.Institute of Engineering and Information, Nanjing Radio and TV University / Nanjing City Vocational College, NanjingJiangsu 211200, China
2.College of Computer, Nanjing University of Posts and Telecommunications, NanjingJiangsu 210003, China
3.Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, NanjingJiangsu 210003, China
Rapid development of Location Based Service (LBS) and Augmented Reality (AR) technology lead to the hidden danger of user location privacy leakage. After analyzing the advantages and disadvantages of existing location privacy protection methods, a location privacy protection method was proposed based on location security. The zone security degree and the camouflage region were introduced into the method, and the zone security was defined as a metric that indicates whether a zone needs protection. The zone security degree of insecure zones (zones need to be protected) was set to 1 while that of secure zones (zones not need to be protected) was set to 0. And the location security degree was calculated by expanding zone security degree and recognition levels. Experimental results show that, compared with the method without introducing location security, this method can reduce average location error and enhance average security, therefore effectively protecting the user location privacy and increasing the service quality of LBS.
杨洋, 王汝传. 增强现实中基于位置安全性的LBS位置隐私保护方法[J]. 计算机应用, 2020, 40(5): 1364-1368.
YANG Yang, WANG Ruchuan. Location based service location privacy protection method based on location security in augmented reality. Journal of Computer Applications, 2020, 40(5): 1364-1368.
1 HÖLLERER T H , FEINER S K . Mobile augmented reality[M]// KARIMI H A.Telegeoinformatics: Location-Based Computing and Services. Boca Raton: CRC Press, 2004：392.
2 张啸剑,孟小峰 . 面向数据发布和分析的差分隐私保护[J]. 计算机学报, 2014, 37(4):927-949. (ZHANG X J, MENG X F. Differential privacy in data publication and analysis[J]. Chinese Journal of Computers, 2014, 37(4):927-949.)
3 KIDO H , YANAGISAWA Y , SATOH T . Protection of location privacy using dummies for location-based services[C]// Proceedings of the 25th International Conference on Data Engineering Workshops. Piscataway: IEEE, 2005:1248-1248.
4 YIU M L, JENSEN C S , HUANG X , et al . SpaceTwist: managing the trade-offs among location privacy, query performance, and query accuracy in mobile services[C]// Proceedings of the IEEE 24th International Conference on Data Engineering. Piscataway: IEEE, 2008:366-375.
5 潘晓,郝兴,孟小峰 . 基于位置服务中的连续查询隐私保护研究[J]. 计算机研究与发展, 2011, 47(1):121-129. (PAN X, HAO X, MENG X F. Privacy preserving towards continuous query in location-based services[J]. Journal of Computer Research and Development, 2011, 47(1):121-129.)
6 GEDIK B , LIU L . Protecting location privacy with personalized k-anonymity: architecture and algorithms[J]. IEEE Transactions on Mobile Computing, 2008, 7(1):1-18.
7 张建明,赵玉娟,江浩斌,等 . 车辆自组网的位置隐私保护技术[J]. 通信学报, 2012, 33(8):180-189. ZHANG J M , ZHAO Y J , JIANG H B , et al . Research on protection technology for location privacy in VANET[J]. Journal on Communications, 2012, 33(8):180-189.
8 RAYA M , HUBAUX J P . The security of vehicular ad hoc networks[C]// Proceedings of the 3rd ACM Workshop on Security of Ad Hoc and Sensor Networks. New York: ACM, 2005:11-21.
9 胡兆玮,杨静 . 轨迹隐私保护技术研究进展分析[J]. 计算机科学, 2016, 43(4):16-23. (HU Z W, YANG J. Survey of trajectory privacy preserving techniques[J]. Computer Science, 2016, 43(4):16-23.)
10 WASEF A , SHEN X . REP: location privacy for VANET using random encryption periods[J]. Mobile Networks and Applications, 2010, 15(1): 172-185.
11 REEM D . The geometric stability of Voronoi diagrams with respect to small changes of the sites[C]// Proceedings of the 27th Annual Symposium on Computational Geometry. New York: ACM, 2011: 254-263.
12 CHOW C Y , MOKBEL M F , LIU X . Spatial cloaking for anonymous location-based services in mobile peer-to-peer environments[J]. GeoInformatica, 2011,15(2):351-380.
13 NERGIZ M E , GÖK M Z . Hybrid k-anonymity[J]. Computers and Security, 2014, 44:51-63.
14 DWORK C . The promise of differential privacy: a tutorial on algorithmic techniques[C]// Proceedings of the 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science. Piscataway: IEEE, 2011:1-2．
15 KALNIS P , GHINITA G , MOURATIDIS K , et al . Preventing location-based identity inference in anonymous spatial queries[J]. IEEE Transactions on Knowledge and Data Engineering, 2008, 19(12) :1719-1733.
16 BRINKHOFF T . A framework for generating network-based moving objects[J]. An International Journal on Advances of Computer Science for Geographic Information Systems(Geo Informatica) ,2002,6(2): 153-180.
2020, Vol. 40 
