Abstract:Since the problem of trajectory privacy violation and homogeneous semantic location attack of moving objects in road network environment is very serious, a Privacy-aware Trajectory Data Collection (PTDC) algorithm was proposed. Firstly, through visits' entropy of Points Of Interests (POI), the sensitivity of each POI was computed; secondly, based on the mixture distance of sensitivity and Euclidean distance, θ-weight was defined and a weighted model of vertices and edges in the network environment was established to reach a k-θ-D anonymity, which can resist the semantic location homogeneity attack; finally, based on the bread-first traversal algorithm of undirected graph, an anonymous algorithm was proposed to satisfy the semantic difference of POIs, so that user's sensitive sampling location was replaced by an anonymous region. Data utility caused by PTDC algorithm was theoretically evaluated. A set of experiments were implemented to test PTDC algorithm, and compare it with the privacy-preserving algorithm named YCWA (You Can Walk Alone) in free space. In theory, the privacy level of YCWA algorithm was lower than PTDC algorithm. The experimental results show that the PTDC algorithm has an average information loss of about 15%, and average range count query error rate of about 12%, which performs slightly worse than YCWA algorithm, while the running time of PTDC algorithm is less than 5 seconds, which is much better than YCWA algorithm. PTDC algorithm meets the needs of real-time online data collection.
霍峥, 王卫红, 曹玉辉. PTDC:路网环境中感知隐私的轨迹数据采集技术[J]. 计算机应用, 2017, 37(9): 2567-2571.
HUO Zheng, WANG Weihong, CAO Yuhui. PTDC:privacy-aware trajectory data collection technology under road network constraint. Journal of Computer Applications, 2017, 37(9): 2567-2571.
[1] ZHENG Y. Trajectory data mining:an overview[J]. ACM Transactions on Intelligent Systems and Technology, 2015, 6(3):Article No. 29. [2] 霍峥,孟小峰.轨迹隐私保护技术研究[J].计算机学报,2011,34(10):1820-1830.(HUO Z, MENG X F. A survey of trajectory privacy-preserving techniques[J]. Chinese Journal of Computers, 2011, 34(10):1820-1830.) [3] DAI J, HUA L. A method for the trajectory privacy protection based on the segmented fake trajectory under road networks[C]//Proceedings of the 20152nd International Conference on Information Science and Control Engineering. Washington, DC:IEEE Computer Society, 2015:13-17. [4] CHEN R, LI H, QIN A K, et al. Private spatial data aggregation in the local setting[C]//Proceedings of the 2016 IEEE 32nd International Conference on Data Engineering. Washington, DC:IEEE Computer Society, 2016:289-300. [5] 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 J, ZHANG Y, LI X H, et al. A trajectory privacy protection approach via trajectory frequency suppression[J]. Chinese Journal of Computers, 2014, 37(10):2096-2106.) [6] CAI Z F, YANG H X, SHUANG W, et al. A clustering-based privacy-preserving method for uncertain trajectory data[C]//Proceedings of the 2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications. Washington, DC:IEEE Computer Society, 2014:1-8. [7] HAN P I, TSAI H P. SST:privacy preserving for semantic trajectories[C]//Proceedings of the 201516th IEEE International Conference on Mobile Data Management. Washington, DC:IEEE Computer Society, 2015:80-85. [8] HUO Z, MENG X, HU H, et al. You can walk alone:trajectory privacy-preserving through significant stays protection[C]//International Conference on Database Systems for Advanced Applications, LNCS 7238. Berlin:Springer, 2012:351-366. [9] HUO Z, MENG X, ZHANG R. Feel free to check in:privacy alert against hidden location inference attacks in GeoSNs[C]//International Conference on Database Systems for Advanced Applications, LNCS 7825. Berlin:Springer, 2013:377-391. [10] 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 Z, MENG X F, HUANG Y. PrivateCheckIn:trajectory privacy-preserving for check-in services in MSNS[J]. Chinese Journal of Computers. 2013, 36(4):716-726.) [11] 数据堂.数据产品[DB/OL].[2017-01-06]. http://www.datatang.com/product/product.html. [12] TRAJCEVSKI G, WOLFSON O, HINRICHS K, et al. Managing uncertainty in moving objects databases[J]. ACM Transactions on Database Systems, 2004, 29(3):463-507. [13] AI-HUSSAENI K, FUNG B C M, CHEUNG W K. Privacy-preserving trajectory stream publishing[J]. Data and Knowledge Engineering, 2014, 94(Part A):89-109. [14] GUO M, JIN X, PISSINOU N, et al. In-network trajectory privacy preservation[J]. ACM Computing Surveys, 2015, 48(2):Article No. 23.