A Framework for Preserving Location Privacy for Continuous Queries

  • Raed Saeed Al-DhubhaniEmail author
  • Jonathan Cazalas
  • Rashid Mehmood
  • Iyad Katib
  • Faisal Saeed
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1073)


The growth of the location-based services (LBSs) market in recent years was motivated by the widespread use of mobile devices equipped with positioning capability and Internet accessibility. To preserve the location privacy of LBS users, many mechanisms have been proposed to provide a partial disclosure by decreasing or blurring or the accuracy of the shared location. While these Location Privacy Preserving Mechanisms (LPPMs) have demonstrated effective performance with snapshot queries, this work shows that preserving location privacy for continuous queries should be addressed differently. In this paper, MOPROPLS framework is proposed with the aim to preserve location privacy in the specific case of continuous queries. As part of the proposed framework, a novel set of six requirements that any LPPM should meet in order to provide location privacy for continuous queries is proposed. In addition, a novel location privacy leakage metric and a novel two-phased probabilistic candidate selection algorithm are proposed. Comparing the performance of MOPROPLS framework with the geo-indistinguishability LPPM in terms of privacy (adversary estimation error) shows that the average of MOPROPLS framework improvement is 34%.


MOPROPLS framework Location privacy Continuous queries Location-based services and LBS 


  1. 1.
    Primault, V., Boutet, A., Mokhtar, S.B., Brunie, L.: The long road to computational location privacy: a survey. IEEE Commun. Surv. Tutorials. 1 (2018).
  2. 2.
    Gupta, R., Rao, U.P.: An exploration to location based service and its privacy preserving techniques: a survey. Wirel. Pers. Commun. 96, 1973–2007 (2017). Scholar
  3. 3.
    Talat, H., Nomani, T., Mohsin, M., Sattar, S.: A survey on location privacy techniques deployed in vehicular networks. In: 2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST), pp. 604–613. IEEE (2019).
  4. 4.
    Gruteser, M., Grunwald, D.: Anonymous usage of location-based services through spatial and temporal cloaking. In: Proceedings of the 1st International Conference on Mobile Systems, Applications and Services - MobiSys 2003, pp. 31–42. ACM Press, New York (2003).
  5. 5.
    Mokbel, M.F., Chow, C.-Y., Aref, W.G.: The new Casper: query processing for location services without compromising privacy (2006).
  6. 6.
    Gedik, B., Liu, L.: Protecting location privacy with personalized k-anonymity: architecture and algorithms. IEEE Trans. Mob. Comput. 7, 1–18 (2008). Scholar
  7. 7.
    Nguyen, N., Han, S., Shin, M.: URALP: unreachable region aware location privacy against maximum movement boundary attack. Int. J. Distrib. Sens. Netw. 11, 246216 (2015). Scholar
  8. 8.
    Lu, Q., Wang, C., Xiong, Y., Xia, H., Huang, W., Gong, X.: Personalized privacy-preserving trajectory data publishing. Chin. J. Electron. 26, 285–291 (2017)CrossRefGoogle Scholar
  9. 9.
    Ma, C., Zhou, C., Yang, S.: A voronoi-based location privacy-preserving method for continuous query in LBS. Int. J. Distrib. Sens. Netw. 11, 326953 (2015). Scholar
  10. 10.
    Wang, Y., Xia, Y., Hou, J., Gao, S., Nie, X., Wang, Q.: A fast privacy-preserving framework for continuous location-based queries in road networks. J. Netw. Comput. Appl. 53, 57–73 (2015). Scholar
  11. 11.
    Kido, H., Yanagisawa, Y., Satoh, T.: An anonymous communication technique using dummies for location-based services. In: Proceedings of International Conference on Pervasive Services, ICPS 2005, pp. 88–97. IEEE (2005).
  12. 12.
    Shankar, P., Ganapathy, V., Iftode, L.: Privately querying location-based services with SybilQuery. In: Proceedings of the 11th international conference on Ubiquitous computing - Ubicomp 2009, p. 31. ACM Press, New York (2009).
  13. 13.
    Gao, S., Ma, J., Shi, W., Zhan, G.: LTPPM: a location and trajectory privacy protection mechanism in participatory sensing. Wirel. Commun. Mob. Comput. 15, 155–169 (2015). Scholar
  14. 14.
    Wei, W., Xu, F., Li, Q.: MobiShare: flexible privacy-preserving location sharing in mobile online social networks. In: 2012 Proceedings IEEE INFOCOM, pp. 2616–2620. IEEE (2012).
  15. 15.
    Beresford, A.R., Stajano, F.: Location privacy in pervasive computing. IEEE Pervasive Comput. 2, 46–55 (2003). Scholar
  16. 16.
    Palanisamy, B., Liu, L.: MobiMix: protecting location privacy with mix-zones over road networks. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 494–505. IEEE (2011).
  17. 17.
    Eckhoff, D., German, R., Sommer, C., Dressler, F., Gansen, T.: SlotSwap: strong and affordable location privacy in intelligent transportation systems. IEEE Commun. Mag. 49, 126–133 (2011). Scholar
  18. 18.
    Chen, Y.-S., Lo, T.-T., Lee, C.-H., Pang, A.-C.: Efficient pseudonym changing schemes for location privacy protection in VANETs. In: 2013 International Conference on Connected Vehicles and Expo (ICCVE), pp. 937–938. IEEE (2013).
  19. 19.
    Domenic, M.K., Wang, Y., Zhang, F., Memon, I., Gustav, Y.H.: Preserving users’ privacy for continuous query services in road networks. In: 2013 6th International Conference on Information Management, Innovation Management and Industrial Engineering, pp. 352–355. IEEE (2013).
  20. 20.
    Sun, Y., Zhang, B., Zhao, B., Su, X., Su, J.: Mix-zones optimal deployment for protecting location privacy in VANET. Peer-to-Peer Netw. Appl. 8, 1108–1121 (2015). Scholar
  21. 21.
    Boualouache, A., Moussaoui, S.: Urban pseudonym changing strategy for location privacy in VANETs. Int. J. Ad Hoc Ubiquitous Comput. 24, 49 (2017). Scholar
  22. 22.
    Ullah, I., Wahid, A., Shah, M.A., Waheed, A.: VBPC: Velocity based pseudonym changing strategy to protect location privacy of vehicles in VANET. In: 2017 International Conference on Communication Technologies (ComTech), pp. 132–137. IEEE (2017).
  23. 23.
    Palanisamy, B., Liu, L.: Attack-resilient mix-zones over road networks: architecture and algorithms. IEEE Trans. Mob. Comput. 14, 495–508 (2015). Scholar
  24. 24.
    Mascetti, S., Freni, D., Bettini, C., Wang, X.S., Jajodia, S.: Privacy in geo-social networks: proximity notification with untrusted service providers and curious buddies. VLDB J. 20, 541–566 (2011). Scholar
  25. 25.
    Shen, N., Yang, J., Yuan, K., Fu, C., Jia, C.: An efficient and privacy-preserving location sharing mechanism. Comput. Stand. Interfaces 44, 102–109 (2016). Scholar
  26. 26.
    Ghinita, G., Kalnis, P., Khoshgozaran, A., Shahabi, C., Tan, K.-L.: Private queries in location based services: anonymizers are not necessary. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data - SIGMOD 2008, p. 121. ACM Press, New York (2008).
  27. 27.
    Paulet, R., Kaosar, M.G., Yi, X., Bertino, E.: Privacy-preserving and content-protecting location based queries. IEEE Trans. Knowl. Data Eng. 26, 1200–1210 (2014).
  28. 28.
    Gutscher, A.: Coordinate transformation - a solution for the privacy problem of location based services? In: Proceedings 20th IEEE International Parallel & Distributed Processing Symposium, p. 7. IEEE (2006).
  29. 29.
    Yiu, M.L., Jensen, C.S., Møller, J., Lu, H.: Design and analysis of a ranking approach to private location-based services. ACM Trans. Database Syst. 36, 1–42 (2011). Scholar
  30. 30.
    Perazzo, P., Dini, G.: A uniformity-based approach to location privacy. Comput. Commun. 64, 21–32 (2015). Scholar
  31. 31.
    Kachore, V.A., Lakshmi, J., Nandy, S.K.: Location obfuscation for location data privacy. In: 2015 IEEE World Congress on Services, pp. 213–220. IEEE (2015).
  32. 32.
    Zurbaran, M.A., Avila, K., Wightman, P., Fernandez, M.: Near-rand: noise-based location obfuscation based on random neighboring points. IEEE Lat. Am. Trans. 13, 3661–3667 (2015). Scholar
  33. 33.
    Shahid, A.R., Jeukeng, L., Zeng, W., Pissinou, N., Iyengar, S.S., Sahni, S., Varela-Conover, M.: PPVC: privacy preserving voronoi cell for location-based services. In: 2017 International Conference on Computing, Networking and Communications (ICNC), pp. 351–355. IEEE (2017).
  34. 34.
    Schlegel, R., Chow, C.-Y., Huang, Q., Wong, D.S.: User-defined privacy grid system for continuous location-based services. IEEE Trans. Mob. Comput. 14, 2158–2172 (2015). Scholar
  35. 35.
    Shokri, R., Theodorakopoulos, G., Troncoso, C., Hubaux, J.-P., Le Boudec, J.-Y.: Protecting location privacy: optimal strategy against localization attacks. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security - CCS 2012, p. 617. ACM Press, New York (2012).
  36. 36.
    Xiong, P., Zhu, T., Niu, W., Li, G.: A differentially private algorithm for location data release. Knowl. Inf. Syst. 47, 647–669 (2016). Scholar
  37. 37.
    Andrés, M.E., Bordenabe, N.E., Chatzikokolakis, K., Palamidessi, C., Andrés, M.E., Bordenabe, N.E., Chatzikokolakis, K., Palamidessi, C.: Geo-indistinguishability: differential privacy for location-based systems. In: Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security - CCS 2013, pp. 901–914. ACM Press, New York (2013).
  38. 38.
    Chatzikokolakis, K., Palamidessi, C., Stronati, M.: Constructing elastic distinguishability metrics for location privacy. Proc. Priv. Enhancing Technol. 2015, 156–170 (2015). Scholar
  39. 39.
    Al-Dhubhani, R., Cazalas, J.M.: An adaptive geo-indistinguishability mechanism for continuous LBS queries. Wirel. Netw. 1–19 (2017).
  40. 40.
    Shokri, R., Theodorakopoulos, G., Le Boudec, J.-Y., Hubaux, J.-P.: Quantifying location privacy. In: 2011 IEEE Symposium on Security and Privacy, pp. 247–262. IEEE (2011).
  41. 41.
    Piorkowski, M., Sarafijanovic-Djukic, N., Grossglauser, M.: A parsimonious model of mobile partitioned networks with clustering. In: 2009 First International Communication Systems and Networks and Workshops, pp. 1–10. IEEE (2009).

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Raed Saeed Al-Dhubhani
    • 1
    Email author
  • Jonathan Cazalas
    • 2
  • Rashid Mehmood
    • 3
  • Iyad Katib
    • 3
  • Faisal Saeed
    • 4
  1. 1.University of Hafr AlbatinHafar Al BatinKingdom of Saudi Arabia
  2. 2.Rollins CollegeWinter ParkUSA
  3. 3.King Abdul-Aziz UniversityJeddahKingdom of Saudi Arabia
  4. 4.Taibah UniversityMedinaKingdom of Saudi Arabia

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