Hybrid Cryptographic Based Approach for Privacy Preservation in Location-Based Services

  • Ajaysinh Rathod
  • Vivaksha Jariwala
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 27)


Location-based services (LBSs) are one of the dominant technology of current era in the fields of mobile, information communication and networking. User requires many important information based on their location to perform their task like location-based navigation, location-based information, and many more. The user has to give their important information like user identity and location information to the provider that are personalized. Location privacy and communication is the major problem in LBSs. LBSs are categorized as TTP based and TTP free schema. TTP free schema is one of the best schemas which uses cryptographic technique and peer-to-peer communication model. In peer-to-peer model, various authors already proposed various approaches to provide location privacy. But still many open challenges needed to be solved like to improve scalability and reduce communication cost and computational cost. In this paper, we propose an approach that provides location privacy to the LBS users.


Location-based services Privacy preserving Cryptography Privacy homomorphism Density based clustering 


  1. 1.
    R. Padmanaban, Location privacy in location based services: unsolved problem and challenge. Int. J. Adv. Remote Sens. GIS 2(1), 398–404 (2013)Google Scholar
  2. 2.
    Y. Liu, W. Wei, A. Sun, C. Miao, Exploiting geographical neighborhood characteristics for location recommendation, in Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM’14) (ACM, 2014), pp. 739–748Google Scholar
  3. 3.
    E. Magkos, Cryptographic approaches for privacy preservation in location-based services: a survey. Int. J. Inf. Technol. Syst. Approach 4(2), 48–69 (2011)CrossRefGoogle Scholar
  4. 4.
    M. Wernke, P. Skvortsov, F. Durr, K. Rothermel, A classification of location privacy attacks and approaches. Pers. Ubiquit. Comput. 18(1), 163–175 (2014)CrossRefGoogle Scholar
  5. 5.
    Y. Wang, F. Li, B. Xu, L2P2: Location-aware location privacy protection for location-based services, in Proceedings - IEEE INFOCOM, 2012, pp. 1996–2004Google Scholar
  6. 6.
    G. Yang, J. Li, S. Zhang, H. Zhou, A survey of location-based privacy preserving. J. Convergence Inf. Technol. 8(11), 27–33 (2013)CrossRefGoogle Scholar
  7. 7.
    A. Solanas, J. Domingo-Ferrer, A. Martinez-Ballest, Location privacy in location-based services: beyond TTP-based schemes, in Proceedings of the 1st International Workshop on Privacy in Location-Based Applications, October 2008Google Scholar
  8. 8.
    G. Ghinita, P. Kalnis, A. Khoshgozaran, C. Shahabi, K.-L. Tan, Private queries in location based services: anonymizers are not necessary, in ACM SIGMOD International Conference on Management of Data, 2008, pp. 121–132. ISBN: 978-1-60558-102-6Google Scholar
  9. 9.
    G. Ghinita, P. Kalnis, M. Kantarcioglu, E. Bertino, A hybrid technique for private location-based queries with database protection, in Advances in Spatial and Temporal Databases Volume 5644 of the Series Lecture Notes in Computer Science (Springer, Berlin, 2009), pp. 98–116. ISBN: 978-3-642-02982-0Google Scholar
  10. 10.
    A. Solanas, A. Martinez-Balleste, Privacy protection in location-based services through a public-key privacy homomorphism, in Proceedings of the 4th European Conference on Public Key Infrastructure: Theory and Practice (Springer, 2007). ISBN: 3-540-73407-4 978-3-540-73407-9Google Scholar
  11. 11.
    Y. Huang, R. Vishwanathan, Privacy preserving group nearest neighbor queries in location-based services using cryptographic techniques, in IEEE Global Telecommunications Conference GLOBECOM, 2010Google Scholar
  12. 12.
    R. Gupta, U.P. Rao, An exploration to location based service and its privacy preserving techniques: a survey. J. Wireless Pers. Commun. 96(2), 1973–2007 (2017)CrossRefGoogle Scholar
  13. 13.
    B. Amro, Y. Saygin, A. Levi, Enhancing privacy in collaborative traffic-monitoring systems using autonomous location update. IET Intell. Transp. Syst. 7(4), 388–395 (2013)CrossRefGoogle Scholar
  14. 14.
    M. Ashouri-Talouki, A. Baraani-Dastjerdi, Homomorphic encryption to preserve location privacy. Int. J. Secur. Appl. 6(4), 183–189 (2012)Google Scholar
  15. 15.
    A.K. Tyagi, D.N. Sreenath, Preserving location privacy in location based services against Sybil attacks. Int. J. Secur. Appl. 9(12), 175–196 (2015)Google Scholar
  16. 16.
    S. Patil, S. Ramayane, M. Jadhav, P. Pachorkar, Hiding user privacy in location base services through mobile collaboration: a review, in International Conference on Computational Intelligence and Communication Networks IEEE, 2015Google Scholar
  17. 17.
    T. Peng, Q. Liu, G. Wang, Enhanced location privacy preserving scheme in location-based services. IEEE Syst. J. 11(99), 1–12 (2014)Google Scholar
  18. 18.
    R. Shokri, G. Theodorakopoulos, P. Papadimitratos, E. Kazemi, J.-P. Hubaux, Hiding in the mobile crowd: location privacy through collaboration, in IEEE Transactions on Dependable and Secure Computing, Special Issue on “Security and Privacy in Mobile Platforms”, 2014Google Scholar
  19. 19.
    A.K. Tyagi, N. Sreenath, Future challenging issues in location based services. Int. J. Comput. Appl. 114(5), 51–56 (2015)Google Scholar
  20. 20.
    N. Yang, Y. Cao, Q. Liu, J. Zheng, A novel personalized TTP-free location privacy preserving method. Int. J. Secur. Appl. 8(2), 388 (2014)Google Scholar
  21. 21.
    A. Solanas, A. Martinez-Balleste, A TTP-free protocol for location privacy in location-based services. Trans. Comput. Commun. 31(6), 1181–1191 (2008)CrossRefGoogle Scholar
  22. 22.
    C. Bettini, X. Sean Wang, S. Jajodia, Protecting privacy against location-based personal identification, in Workshop on Secure Data Management SDM 2005: Secure Data Management, 2006, pp. 185–199Google Scholar
  23. 23.
    G. Yang, J. Li, S. Zhang, H. Zhou, A survey of location-based privacy preserving. J. Convergence Inf. Technol. 8(11), 27 (2013)CrossRefGoogle Scholar
  24. 24.
    M. Wernke, P. Skvortsov, F. Durr, K. Rothermel, A classification of location privacy attacks and approaches. Pers. Ubiquit. Comput. 18(1), 163–175 (2014)CrossRefGoogle Scholar
  25. 25.
    S.R. Shastry, P.K. Deshmukh, A.B. Bagwan, Generating: random regions in Spatial cloaking algorithm for location privacy preservation. IOSR J. Comput. Eng. 9(4), 46–49 (2013)CrossRefGoogle Scholar
  26. 26.
    A. Rathod, V. Jariwala, Investigation of privacy issues in location-based services, in Recent Findings in Intelligent Computing Techniques. Advances in Intelligent Systems and Computing, vol. 707 (Springer, Singapore, 2018), pp. 55–65Google Scholar
  27. 27.
    V. Jariwala, D. Jinwala, Evaluating homomorphic encryption algorithms for privacy in wireless sensor network. Int. J. Adv. Comput. Technol. 3(6), 1–11 (2011)Google Scholar
  28. 28.
    X. Zhu, Y. Lu, X. Zhu, S. Qiu, A location privacy-preserving protocol based on homomorphic encryption and key agreement, in International Conference on Information Science and Cloud Computing Companion IEEE, 2014Google Scholar
  29. 29.
    R.J. Patil, K.K. Joshi, S. Raksha, Analysis on preserving location privacy. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 5(3), 562–566 (2015)Google Scholar
  30. 30.
    J. Liu, J. Luo, J.Z. Huang, X. Li, Privacy Preserving Distributed DBSCAN Clustering (ACM, Berlin, 2012)CrossRefGoogle Scholar
  31. 31.
    P. Batra Nagpal, P. Ahlawat Mann, Comparative study of density based clustering algorithms. Int. J. Comput. Appl. 27(11), 421–435 (2011)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ajaysinh Rathod
    • 1
  • Vivaksha Jariwala
    • 2
  1. 1.Department of Computer EngineeringRDIC, C. U. Shah UniversityWadhwanIndia
  2. 2.Department of Information TechnologySarvajanik College of Engineering and TechnologySuratIndia

Personalised recommendations