Skip to main content
SpringerLink
Log in

PrivSem: Protecting location privacy using semantic and differential privacy

  • Published:
World Wide Web Aims and scope Submit manuscript

Abstract

In this paper, we address the problem of users’ location privacy preservation on road networks. Most existing privacy preservation techniques rely on structure-based spatial cloaking, but pay little attention to locations’ semantic information. Yet, the semantics may disclose sensitive information of mobile users. In addition, these studies ignore the location privacy requirements of other users, which is essential for location-based services (LBS). Thus, to tackle these problems, we propose PrivSem, a novel framework which integrates locationk-anonymity, segmentl-semantic diversity, and differential privacy to protect user location privacy from violation. In this framework, rather than using the original location data, we only access to the sanitized data according to differential privacy. Due to the nature of differential privacy which perturbs the real data with noise, it is particularly challenging to determine an effective cloaked area. Further, we investigate an error analysis model to ensure the effectiveness of the generated cloaked areas. Finally, through formal privacy analysis, we show that our proposed approach is effective in providing privacy guarantees. Extensive experimental evaluations on large real-world datasets are conducted to demonstrate the efficiency and effectiveness of PrivSem.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11

Similar content being viewed by others

Notes

  1. http://www.cs.utah.edu/~lifeifei/SpatialDataset.htm

  2. http://www.fh-oow.de/institute/iapg/personen/brinkhoff

References

  1. Bamba, B., Liu, L., Pesti, P., Wang, T.: Supporting anonymous location queries in mobile environments with privacygrid. In: Proceedings of WWW, pp. 237–246 (2008)

  2. Beresford, A.R., Stajano, F.: Location privacy in pervasive computing. Pervasive comput 2(1), 46–55 (2003)

    Article  Google Scholar 

  3. Bettini, C., Mascetti, S., Wang, X.S.: Privacy Threats in Location-Based Services. In: Encyclopedia of GIS, pp. 906–912 (2008)

    Chapter  Google Scholar 

  4. Chan, T.H.H., Shi, E., Song, D.: Private and continual release of statistics. Information and System Security Journal 14(3), 26 (2011)

    Google Scholar 

  5. Cheng, R., Zhang, Y., Bertino, E., Prabhakar, S.: Preserving user location privacy in mobile data management infrastructures. Lect. Notes Comput. Sci 4258, 393–412 (2006)

    Article  Google Scholar 

  6. Chor, B., Goldreich, O., Kushilevitz, E., Sudan, M.: Private information retrieval. In: Proceedings of Annual Foundations of Computer Science, pp. 41–50 (1995)

  7. Chow, C., Mokbel, M., Bao, J., Liu, X.: Query-aware location anonymization for road networks. GeoInformatica 15(3), 571–607 (2011)

    Article  Google Scholar 

  8. Cormode, G., Procopiuc, C., Srivastava, D., Shen, E., Yu, T.: Differentially private spatial decompositions. In: Proceedings of ICDE, pp. 20–31 (2012)

  9. Damiani, M.L., Bertino, E., Silvestri, C., et al.: The probe framework for the personalized cloaking of private locations. Trans. Data Privacy Journal 3(2), 123–148 (2010)

    Google Scholar 

  10. Damiani, M.L., Silvestri, C., Bertino, E.: Fine-grained cloaking of sensitive positions in location-sharing applications. Pervasive Computing Journal 10(4), 64–72 (2011)

    Article  Google Scholar 

  11. Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating noise to sensitivity in private data analysis. In: Proceedings of TCC, vol. 3876. pp. 265–284 (2006)

    Chapter  Google Scholar 

  12. Fan, L., Xiong, L.: An adaptive approach to real-time aggregate monitoring with differential privacy. TKDE J 26(9), 2094–2106 (2014)

    Google Scholar 

  13. Fogaras, D., Rácz, B.: A scalable randomized method to compute link-based similarity rank on the web graph. In: Proceedings of EDBT Workshops, pp. 557–567 (2004)

    Chapter  Google Scholar 

  14. Gedik, B., Liu, L.: Location privacy in mobile systems: a personalized anonymization model. In: Proceedings of ICDCS, pp. 620–629 (2005)

  15. Ghinita, G., Kalnis, P., Khoshgozaran, A., Shahabi, C., Tan, K.L.: Private queries in location based services: anonymizers are not necessary. In: Proceedings of SIGMOD, pp. 121–132 (2008)

  16. Gruteser, M., Grunwald, D.: Anonymous usage of location-based services through spatial and temporal cloaking. In: Proceedings of MobiSys, pp. 31–42 (2003)

  17. Hashem, T., Kulik, L., Ramamohanarao, K., Zhang, R., Soma, S.C.: Protecting privacy for distance and rank based group nearest neighbor queries. World Wide Web 22(1), 375–416 (2019)

    Article  Google Scholar 

  18. He, X., Cormode, G., Machanavajjhala, A., Procopiuc, C.M., Srivastava, D.: Dpt: differentially private trajectory synthesis using hierarchical reference systems. VLDB J. 8(11), 1154–1165 (2015)

    Google Scholar 

  19. Kalnis, P., Ghinita, G., Mouratidis, K., Papadias, D.: Preventing location-based identity inference in anonymous spatial queries. TKDE J. 19(12), 1719–1733 (2007)

    Google Scholar 

  20. Kellaris, G., Papadopoulos, S.: Practical differential privacy via grouping and smoothing. In: Proceedings of VLDB, vol. 6. pp. 301–312 (2013)

    Article  Google Scholar 

  21. Kellaris, G., Papadopoulos, S., Xiao, X., Papadias, D.: Differentially private event sequences over infinite streams. VLDB J. 7(12), 1155–1166 (2014)

    Google Scholar 

  22. Kido, H., Yanagisawa, Y., Satoh, T.: An anonymous communication technique using dummies for location-based services. In: Proceedings of ICPS, pp. 88–97 (2005)

  23. Kong, X., Song, X., Xia, F., Guo, H., Wang, J., Tolba, A.: Lotad: long-term traffic anomaly detection based on crowdsourced bus trajectory data. World Wide Web 21(3), 825–847 (2018)

    Article  Google Scholar 

  24. Ku, W.S., Zimmermann, R., Peng, W.C., Shroff, S.: Privacy protected query processing on spatial networks. In: Proceedings of ICDE Workshop, pp. 215–220. IEEE (2007)

  25. Lee, B., Oh, J., Yu, H., Kim, J.: Protecting location privacy using location semantics. In: Proceedings of SIGKDD, pp. 1289–1297 (2011)

  26. Li, C., Palanisamy, B.: Differentially private trajectory analysis for points-of-interest recommendation (2017)

  27. Li, M., Qin, Z., Wang, C.: Sensitive semantics-aware personality cloaking on road-network environment. International Journal of Security and Its Applications 8(1), 133–146 (2014)

    Article  Google Scholar 

  28. Li, P., Peng, W., Wang, T.: A cloaking algorithm based on spatial networks for location privacy. In: Proceedings of SUTC, pp. 90–97 (2008)

  29. Li, Y., Yuan, Y., Wang, G., Chen, L., Li, J.: Semantic-aware location privacy preservation on road networks. In: Proceedings of DASFAA, pp. 314–331 (2016)

    Chapter  Google Scholar 

  30. Li, Z., Pei, Q., Liu, Y.: Spoofing attacks and countermeasures in fm indoor localization system. World Wide Web 21(1), 219–240 (2018)

    Article  Google Scholar 

  31. Machanavajjhala, A., Gehrke, J., Kifer, D.: Venkitasubramaniam, M.: l-diversity: Privacy beyond k-anonymity. In: Proceedings of ICDE, pp. 24–24 (2006)

  32. Martínez-Hinarejos, C., Juan, A., Casacuberta, F.: Generalized k-medians clustering for strings. Pattern Recognition and Image Analysis pp .502–509 (2003)

  33. McSherry, F., Mironov, I.: Differentially private recommender systems: building privacy into the net. In: Proceedings of SIGKDD, pp. 627–636 (2009)

  34. Mokbel, M.F., Chow, C.Y., Aref, W.G.: The new casper: Query processing for location services without compromising privacy. In: Proceedings of VLDB, pp. 763–774 (2006)

  35. Palanisamy, B., Liu, L.: Mobimix: Protecting location privacy with mix-zones over road networks. In: Proceedings of ICDE, pp. 494–505 (2011)

  36. Papadopoulos, S., Bakiras, S., Papadias, D.: Nearest neighbor search with strong location privacy. VLDB J. 3(1-2), 619–629 (2010)

    Google Scholar 

  37. Qardaji, W., Yang, W., Li, N.: Differentially private grids for geospatial data. In: Proceedings of ICDE, pp. 757–768 (2013)

  38. Shin, K.G., Ju, X., Chen, Z., Hu, X.: Privacy protection for users of location-based services. Wirel. Commun. J. 19(1), 30–39 (2012)

    Article  Google Scholar 

  39. Sibson, R.: Slink: an optimally efficient algorithm for the single-link cluster method. Comput. J. 16(1), 30–34 (1973)

    Article  MathSciNet  Google Scholar 

  40. Soma, S.C., Hashem, T., Cheema, M.A., Samrose, S.: Trip planning queries with location privacy in spatial databases. World Wide Web J. 20(2), 205–236 (2017)

    Article  Google Scholar 

  41. Sweeney, L.: k-anonymity: A model for protecting privacy. Int. J. Uncertainty Fuzziness Knowledge Based Syst. 10(05), 557–570 (2002)

    Article  MathSciNet  Google Scholar 

  42. To, H., Ghinita, G., Fan, L., Shahabi, C.: Differentially private location protection for worker datasets in spatial crowdsourcing. TMC Journal 16(4), 934–949 (2017)

    Google Scholar 

  43. Vicente, C.R., Freni, D., Bettini, C., Jensen, C.S.: Location-related privacy in geo-social networks. Internet Computing Journal 15(3), 20–27 (2011)

    Article  Google Scholar 

  44. Wang, Q., Zhang, Y., Lu, X., Wang, Z., Qin, Z., Ren, K.: Rescuedp: Real-time spatio-temporal crowd-sourced data publishing with differential privacy. In: Proceedings of INFOCOM, pp. 1–9 (2016)

  45. Wang, T., Liu, L.: Privacy-aware mobile services over road networks. VLDB J. 2(1), 1042–1053 (2009)

    Google Scholar 

  46. Wu, W., Parampalli, U., Liu, J., Xian, M.: Privacy preserving k-nearest neighbor classification over encrypted database in outsourced cloud environments. World Wide Web pp. 1–23 (2018)

  47. Xiao, X., Wang, G., Gehrke, J.: Differential privacy via wavelet transforms. TKDE Journal 23(8), 1200–1214 (2011)

    Google Scholar 

  48. Xiao, Y., Xiong, L., Yuan, C.: Differentially private data release through multidimensional partitioning. Secure Data Management Journal 6358, 150–168 (2010)

    Article  Google Scholar 

  49. Xu, J., Zhang, Z., Xiao, X., Yang, Y., Yu, G., Winslett, M.: Differentially private histogram publication. VLDB J. 22(6), 797–822 (2013)

    Article  Google Scholar 

  50. Xu, T., Cai, Y.: Exploring historical location data for anonymity preservation in location-based services. In: Proceedings of INFOCOM, pp. 547–555 (2008)

  51. Xu, T., Cai, Y.: Feeling-based location privacy protection for location-based services, In: Proceedings of CCS, pp. 348–357 (2009)

  52. Xue, M., Kalnis, P., Pung, H.K.: Location diversity: Enhanced privacy protection in location based services. In: Proceedings of LoCA, pp. 70–87 (2009)

    Google Scholar 

  53. Yigitoglu, E., Damiani, M.L., Abul, O., Silvestri, C.: Privacy-preserving sharing of sensitive semantic locations under road-network constraints. In: Proceedings of MDM, pp. 186–195 (2012)

  54. Yiu, M.L., Jensen, C.S., Huang, X., Lu, H.: Spacetwist: Managing the trade-offs among location privacy, query performance, and query accuracy in mobile services. In: Proceedings of ICDE, pp. 366–375 (2008)

  55. Zhang, Y., Szabo, C., Sheng, Q.Z., Fang, X.S.: Snaf: Observation filtering and location inference for event monitoring on twitter. World Wide Web 21(2), 311–343 (2018)

    Article  Google Scholar 

Download references

Acknowledgments

This research was partially supported by the National Natural Science Foundation of China under Grant No. 61572119, 61622202, U1401256, 61732003 and 61729201; and the Fundamental Research Funds for the Central Universities under Grant No. N150402005.

Author information

Authors and Affiliations

  1. Northeastern University, Shenyang, China

    Yanhui Li, Ye Yuan & Guoren Wang

  2. The University of New South Wales, Sydney, Australia

    Yanhui Li & Xin Cao

Authors
  1. Yanhui Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xin Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ye Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guoren Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yanhui Li.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Y., Cao, X., Yuan, Y. et al. PrivSem: Protecting location privacy using semantic and differential privacy. World Wide Web 22, 2407–2436 (2019). https://doi.org/10.1007/s11280-019-00682-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11280-019-00682-0

Keywords

Search

Navigation