Louis, Lester and Pierre: Three Protocols for Location Privacy

  • Ge Zhong
  • Ian Goldberg
  • Urs Hengartner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4776)


Location privacy is of utmost concern for location-based services. It is the property that a person’s location is revealed to other entities, such as a service provider or the person’s friends, only if this release is strictly necessary and authorized by the person. We study how to achieve location privacy for a service that alerts people of nearby friends. Here, location privacy guarantees that users of the service can learn a friend’s location if and only if the friend is actually nearby. We introduce three protocols—Louis, Lester and Pierre—that provide location privacy for such a service. The key advantage of our protocols is that they are distributed and do not require a separate service provider that is aware of people’s locations. The evaluation of our sample implementation demonstrates that the protocols are sufficiently fast to be practical.


Location Privacy Homomorphic Encryption Communication Step Transport Layer Security Secure Multiparty Computation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Atallah, M.J., Du, W.: Secure Multi-party Computational Geometry. In: Dehne, F., Sack, J.-R., Tamassia, R. (eds.) WADS 2001. LNCS, vol. 2125, pp. 165–179. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  2. 2.
    Boneh, D., Goh, E.-J., Nissim, K.: Evaluating 2-DNF Formulas on Ciphertexts. In: Kilian, J. (ed.) TCC 2005. LNCS, vol. 3378, pp. 325–341. Springer, Heidelberg (2005)Google Scholar
  3. 3.
    Brandt, F.: Efficient Cryptographic Protocol Design based on Distributed El Gamal Encryption. In: Won, D.H., Kim, S. (eds.) ICISC 2005. LNCS, vol. 3935, pp. 32–47. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Cachin, C.: Efficient Private Bidding and Auctions with an Oblivious Third Party. In: Proceedings of 6th ACM Conference on Computer and Communications Security, pp. 120–127. ACM Press, New York (1999)CrossRefGoogle Scholar
  5. 5.
    Cheng, R., Zhang, Y., Bertino, E., Prabhakar, S.: Preserving User Location Privacy in Mobile Data Management Infrastructures. In: Danezis, G., Golle, P. (eds.) PET 2006. LNCS, vol. 4258, pp. 393–412. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Cramer, R., Gennaro, R., Schoenmakers, B.: A Secure and Optimally Efficient Multi-Authority Election Scheme. In: Fumy, W. (ed.) EUROCRYPT 1997. LNCS, vol. 1233, pp. 103–118. Springer, Heidelberg (1997)Google Scholar
  7. 7.
    Dierks, T., Rescorla, E.: The Transport Layer Security (TLS) Protocol Version 1.1. RFC 4346 (April 2006),
  8. 8.
    Du, W., Zhan, Z.: A Practical Approach to Solve Secure Multi-party Computation Protocols. In: Proceedings of 2002 Workshop on New Security Paradigms Workshop, pp. 127–135 (September 2002)Google Scholar
  9. 9.
    Gedik, B., Liu, L.: Location Privacy in Mobile Systems: A Personalized Anonymization Model. In: ICDCS 2005. Proceedings of 25th International Conference on Distributed Computing Systems (June 2005)Google Scholar
  10. 10.
    Gruteser, M., Grunwald, D.: Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking. In: MobiSys 2003. Proceedings of First International Conference on Mobile Systems, Applications, and Services (May 2003)Google Scholar
  11. 11.
    Kocher, P.: Timing Attacks on Implementations of Diffie-Hellman, RSA, DSS, and Other Systems. In: Koblitz, N. (ed.) CRYPTO 1996. LNCS, vol. 1109, pp. 104–113. Springer, Heidelberg (1996)Google Scholar
  12. 12.
    Køien, G.M., Oleshchuk, V.A.: Location Privacy for Cellular Systems; Analysis and Solutions. In: Danezis, G., Martin, D. (eds.) PET 2005. LNCS, vol. 3856, pp. 40–58. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Liskov, M., Silverman, R.: A Statistical Limited-Knowledge Proof for Secure RSA Keys. IEEE P1363 working group (1998)Google Scholar
  14. 14.
    Loopt, Inc.: loopt - Live In It. (Accessed February 2007),
  15. 15.
    MIT SENSEable City Lab: iFind (Accessed February 2007),
  16. 16.
    Mokbel, M.F., Chow, C.-Y., Aref, W.G.: The New Casper: Query Processing for Location Services without Compromising Privacy. In: Proceedings of the 32nd International Conference on Very Large Data Bases (VLDB 2006), September 2006, pp. 763–774 (2006)Google Scholar
  17. 17.
    The OpenSSL Project. OpenSSL: The Open Source toolkit for SSL/TLS (Accessed February 2007),
  18. 18.
    Paillier, P.: Public-Key Cryptosystems Based on Composite Degree Residuosity Classes. In: Stern, J. (ed.) EUROCRYPT 1999. LNCS, vol. 1592, pp. 223–238. Springer, Heidelberg (1999)Google Scholar
  19. 19.
    Pollard, J.M.: Monte Carlo Methods for Index Computation (mod p). Mathematics of Computation 32(143), 918–924 (1978)zbMATHCrossRefMathSciNetGoogle Scholar
  20. 20.
    Shanks, D.: Class number, a theory of factorization, and genera. Proceedings of Symposia in Pure Mathematics 20, 415–440 (1971)MathSciNetGoogle Scholar
  21. 21.
    Shoup, V.: NTL: A Library for doing Number Theory (Accessed February 2007)
  22. 22.
    Yao, A.C.: Protocols for Secure Computations. In: Proceedings of 23rd IEEE Symposium on Foundations of Computer Science, pp. 160–164. IEEE Computer Society Press, Los Alamitos (1982)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ge Zhong
    • 1
  • Ian Goldberg
    • 1
  • Urs Hengartner
    • 1
  1. 1.David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON,N2L 3G1Canada

Personalised recommendations