利用概率的位置匿名算法

doi:10.3969/j.issn.1001-2400.2015.06.014

J4 ›› 2015, Vol. 42 ›› Issue (6): 75-80.doi: 10.3969/j.issn.1001-2400.2015.06.014

利用概率的位置匿名算法

闫玉双;谭示崇;赵大为

(西安电子科技大学综合业务网理论及关键技术国家重点实验室，陕西西安 710071)

收稿日期:2014-07-13 出版日期:2015-12-20 发布日期:2016-01-25
通讯作者: 谭示崇
作者简介:闫玉双(1987-), 女, 西安电子科技大学博士研究生，E-mail: yushuangy15@163.com．
基金资助:
中央高校基本科研业务费专项资金资助项目(K5051201027)；高等学校学科创新引智计划资助项目(B08038)

Probability-based location anonymity algorithm

YAN Yushuang;TAN Shichong;ZHAO Dawei

(State Key Lab. of Integrated Service Networks, Xidian Univ., Xi'an 710071, China)

Received:2014-07-13 Online:2015-12-20 Published:2016-01-25
Contact: TAN Shichong

摘要/Abstract

摘要：

k匿名模型是一种有效的位置隐私保护技术，通过构造包含需要保护的用户在内的k个正在发送请求的用户的匿名区域，达到保护用户位置的目的．但是现有的k匿名模型仅能利用当前正在发送请求的用户，当同时发送请求用户较少时，就会导致匿名区域过大．为此，提出一种利用概率的位置匿名算法来保护路网中的移动用户的位置，利用当前时刻的不活跃用户的历史位置轨迹，计算出进入匿名路段的概率，可明显减小匿名路段长度．实验结果证明，基于概率的位置匿名算法与一般的k匿名模型相比较，提高了匿名效率．

关键词: k匿名, 不活跃用户, 概率, 基于概率的位置匿名算法

Abstract:

As one of the most effective location privacy preservation technologies, the k-anonymity model provides safeguards for location privacy of the mobile client against vulnerabilities for abuse by constructing an anonymous area of k users including the protected one. However, most existing k-anonymity models only utilize the users who are sending requests at recent time. If there are not enough requesting users, the generated anonymous area of the k-anonymity model will be larger than expected. In this paper, a Probability-based Location Anonymity (PLA) algorithm is proposed for protecting location privacy of the mobile users in a road network. The PLA model takes advantage of the historical path track of the users who are not sending the request currently, and then computes the probability into the anonymous section so that it can greatly reduce the size of the anonymous area. Experimental results show that the PLA algorithm is superior to the k-anonymity and it increases its anonymous efficiency enormously.

Key words: k-anonymity, inactive users, probability, PLA algorithm

闫玉双;谭示崇;赵大为. 利用概率的位置匿名算法[J]. J4, 2015, 42(6): 75-80.

YAN Yushuang;TAN Shichong;ZHAO Dawei. Probability-based location anonymity algorithm[J]. J4, 2015, 42(6): 75-80.

参考文献

［1］ Duri S, Gruteser M, Liu X, et al. Framework for Security and Privacy in Automotive Telematics［C］//Proceedings of the 2nd International Workshop on Mobile Commerce. New York: ACM, 2002: 25-32.
［2］ Wang Y, Xu D, He X. L2P2: Location-aware Location Privacy Protection for Location-based Services［C］//Proceedings of IEEE INFOCOM. Piscataway: IEEE, 2012: 1996-2004.
［3］ Wang Q, Xu Z, Qu S. An Enhanced K-Anonymity Model Against Homogeneity Attack［J］. Journal of Software, 2011, 6(10): 1945-1952.
［4］ Gruteser M, Grunwald D. Anonymous Usage of Location-based Services through Spatial and Temporal Cloaking［C］//Proceedings of the 1st International Conference on Mobile Systems, Applications and Services. New York: ACM, 2003: 31-42.
［5］ Beresford A R, Stajano F. Location Privacy in Pervasive Computing［J］. IEEE Pervasive Computing, 2003, 2(1): 46-55.
［6］ Kim M, Fielding J J, Kotz D. Risks of Using AP Locations Discovered through War Driving in Pervasive Computing［M］. Berlin: Springer, 2006: 67-82.
［7］ Xu T, Cai Y. Exploring Historical Location Data for Anonymity Preservation in Location-based Services［C］//Proceedings of the 27th IEEE Communications Society Conference on Computer Communications. Piscataway: IEEE, 2008: 1220-1228.
［8］ Chow C Y, Mokbel M F. Trajectory Privacy in Location-based Services and Data Publication［J］. ACM SIGKDD Explorations Newsletter, 2011, 13(1): 19-29.
［9］ Suzuki A, Iwata M, Arase Y, et al. A User Location Anonymization Method for Location Based Services in a Real Environment［C］//Proceedings of the 18th ACM International Symposium on Advances in Geographic Information Systems. New York: ACM, 2010: 398-401.
［10］ Kato R, Iwata M, Hara T, et al. A Dummy-based Anonymization Method Based on User Trajectory with Pauses［C］//Proceedings of the 20th ACM International Symposium on Advances in Geographic Information Systems. New York: ACM, 2012: 249-258.
［11］ Yigitoglu E, Damiani M L, Abul O. Privacy-preserving Sharing of Sensitive Semantic Locations under Road-network Constraints［C］//Proceedings of the 13th IEEE International Conference on Mobile Data Management. Washington: IEEE Computer Society, 2012: 186-195.
［12］ Pan X, Xu J, Meng X. Protecting Location Privacy against Location-dependent Attacks in Mobile Services［J］. IEEE Transactions on Knowledge and Data Engineering, 2012, 24(8): 1506-1519.
［13］ Karimi H A, Liu X. A Predictive Location Model for Location-based Services［C］//Proceedings of the 11th ACM International Symposium on Advances in Geographic Information Systems. New York: ACM, 2003: 126-133.
［14］ Thomas Brinkhoff: Network-based Generator of Moving Objects［EB/OL］. ［2014-05-20］. http://iapg.jade-hs.de/personen/brinkhoff/generator/.

[1]	肖叶秋,祝幸辉,赵双睿,任保全,沈玉龙. 卫星通信系统的物理层安全性能分析[J]. 西安电子科技大学学报, 2021, 48(3): 163-169.
[2]	宋传旺,刘栋,李恩玉,赵瑞收,郝思媛,申天琪. NOMA系统的被动中继选择策略[J]. 西安电子科技大学学报, 2021, 48(3): 56-62.
[3]	张逸宸,水鹏朗. 一种改进的泊松点过程概率多假设跟踪方法[J]. 西安电子科技大学学报, 2021, 48(2): 27-34.
[4]	李杉,张坤,水鹏朗. 近海船长分布建模与雷达舰船分类能力评估[J]. 西安电子科技大学学报, 2021, 48(2): 84-91.
[5]	NGUYEN Van-Truong,蔡觉平,魏琳育,褚洁. Sigmoid函数的低复杂度概率分段线性拟合法[J]. 西安电子科技大学学报, 2020, 47(3): 58-65.
[6]	孙翠珍,丁君,郭陈江. 一种改进的引力搜索算法及其波束赋形[J]. 西安电子科技大学学报, 2020, 47(2): 83-90.
[7]	刘雷,贾仁需. 微机电系统麦克风灵敏度不确定性分析[J]. 西安电子科技大学学报, 2019, 46(6): 23-29.
[8]	王明杰,姬红兵,刘龙. 噪声野值下的学生t分布混合CPHD滤波[J]. 西安电子科技大学学报, 2019, 46(5): 134-141.
[9]	刘向丽,刘冬妮,李海娇,李赞. 能量协作下中继系统性能推导及仿真分析[J]. 西安电子科技大学学报, 2019, 46(5): 91-97.
[10]	张书博,任淑霞,吴涛. 结合概率矩阵的改进谱聚类社区发现算法[J]. 西安电子科技大学学报, 2019, 46(3): 167-172.
[11]	李中捷,陈燚雷,曹世明,朱翠涛. 一种蜂窝移动用户小区切换的宏分集方案[J]. 西安电子科技大学学报, 2019, 46(2): 114-118.
[12]	孙林海, 田斌, 黄俊桦, 张月婷. 一种寄生转发系统的ADP干扰抑制技术[J]. 西安电子科技大学学报, 2018, 45(6): 38-43.
[13]	李静威;刘广凯;王川川. 复杂干扰条件对跳频系统中断概率的影响[J]. 西安电子科技大学学报, 2018, 45(4): 137-142.
[14]	李兴旺;李静静;靳进;李立华. Nakagami-m衰落下中继系统性能分析[J]. 西安电子科技大学学报, 2018, 45(3): 117-122.
[15]	李冬霞;李春鸣;赵文强;刘海涛. 无人机中继广播通信系统航迹优化方法[J]. 西安电子科技大学学报, 2018, 45(3): 143-148+180.

利用概率的位置匿名算法

Probability-based location anonymity algorithm

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 10