Abstract
With the development of positioning technology and location-aware devices, moving objects’ location and trajectory information have been collected and published, resulting in serious personal privacy leakage. Existing dummy trajectory privacy preserving method does not consider user’s exposure locations, which causes the adversary can easily exclude the dummy trajectories, resulting in a significant reduction in privacy protection. To solve this problem, we propose a dummy-based trajectory privacy protection scheme, which hides the real trajectory by constructing dummy trajectories, considering the spatio-temporal constraints of geographical environment of the user, the exposure locations in trajectory and the distance between dummy trajectories and real trajectory. We design a number of techniques to improve the performance of the scheme. We have conducted an empirical study to evaluate our algorithms and the results show that our method can effectively protect the user’s trajectory privacy with high data utility.
The work is partially supported by Key Projects of Natural Science Foundation of Liaoning Province (No. 20170520321) and the National Natural Science Foundation of China (Nos. 61502316, 61702344).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gao, S., Ma, J., Sun, C., Li, X.: Balancing trajectory privacy and data utility using a personalized anonymization model. Netw. Comput. Appl. 38, 125–134 (2013)
Fechner, T., Kray, C.: Attacking location privacy: exploring human strategies. In: ACM Conference on Ubiquitous Computing, pp. 95–98 (2012)
Liu, X., Li, M., Xia, X., Li, J., Zong, C., Zhu, R.: Spatio-temporal features based sensitive relationship protection in social networks. In: Meng, X., Li, R., Wang, K., Niu, B., Wang, X., Zhao, G. (eds.) WISA 2018. LNCS, vol. 11242, pp. 330–343. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-02934-0_31
Wu, Q., Liu, H.X., Zhang, C., Fan, Q., Li, Z.Q., Wang, K.: Trajectory protection schemes based on a gravity mobility model in IoT. Electronics 8(2), 148–166 (2019)
Li, F.H., Zhang, C., Niu, B., Li, H., Hua, J.F., Shi, G.Z.: Efficient scheme for user’s trajectory privacy. J. Commun. 36(12), 114–123 (2015)
Yarovoy, R., Bonchi, F., Lakshmanan, S., Wang, W.H.: Anonymizing moving objects: how to hide a MOB in a crowd? In: Kersten, M.L., Novikov, J. (eds.) EDBT 2009, pp. 72–83. ACM Press, New York (2009)
Abul, O., Bonchi, F., Nanni, M.: Never walk alone: uncertainty for anonymity in moving objects databases. In: 24th IEEE International Conference on Data Engineering, pp. 215–226. IEEE Press, Washington (2008)
Huo, Z., Meng, X., Hu, H., Huang, Y.: You Can Walk Alone: trajectory privacy-preserving through significant stays protection. In: Lee, S.-g., Peng, Z., Zhou, X., Moon, Y.-S., Unland, R., Yoo, J. (eds.) DASFAA 2012. LNCS, vol. 7238, pp. 351–366. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29038-1_26
Terrovitis, M., Mamoulis, N.: Privacy preservation in the publication of trajectories. In: 9th International Conference on Mobile Data Management (MDM), pp. 65–72. IEEE (2008)
Zhao, J., Zhang, Y., Li, X.H., Ma, J.F.: A trajectory privacy protection approach via trajectory frequency suppression. J. Comput. 37(10), 2096–2106 (2014)
Kido, H., Yanagisawa, Y., Satoh, T.: An anonymous communication technique using dummies for location-based services. In: International Conference on Pervasive Services (ICPS), pp. 88–97. IEEE (2005)
Lei, P.R., Peng, W.C., Su, I.J., et al.: Dummy-based schemes for protecting movement trajectories. J. Inf. Sci. Eng. 28(2), 335–350 (2012)
Lei, K.Y., Li, X.H., Liu, H., Pei, Z.X., Ma, J.F., Li, H.: Dummy trajectory privacy protection scheme for trajectory publishing based on the spatiotemporal correlation. J. Commun. 37(12), 156–164 (2016)
Moreale, A., et al.: Movement data anonymity through generalization. IEEE Trans. Data Privacy 3, 91–121 (2010)
Kido, H., Yanagisawa, Y., Satoh, T.: Protection of location privacy using dummies for location-based services. In: 21st International Conference on Data Engineering Workshops, p. 1248. IEEE (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Liu, X., Chen, J., Xia, X., Zong, C., Zhu, R., Li, J. (2019). Dummy-Based Trajectory Privacy Protection Against Exposure Location Attacks. In: Ni, W., Wang, X., Song, W., Li, Y. (eds) Web Information Systems and Applications. WISA 2019. Lecture Notes in Computer Science(), vol 11817. Springer, Cham. https://doi.org/10.1007/978-3-030-30952-7_37
Download citation
DOI: https://doi.org/10.1007/978-3-030-30952-7_37
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30951-0
Online ISBN: 978-3-030-30952-7
eBook Packages: Computer ScienceComputer Science (R0)
