EOST-An Access Method for Obfuscating Spatio-Temporal Data in LBS

  • Ashwini Gavali
  • Suresh Limkar
  • Dnyanashwar Patil
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 199)

Abstract

Most widely use of mobile communication devices and the technical improvements of location techniques are fostering the development of new applications that use the physical position of users to offer location-based services for business, social, or informational purposes. Since the development of location-based services, privacy-preserving has gained special attention and many algorithms aiming at protecting user’s privacy have been created such as obfuscation or k-anonymity. The OST-tree capable of obfuscating the spatio-temporal data of users. Also it is easy for the adversary to infer a user’s exact position in the obfuscated area if the probability distribution of user’s position is uniformly distributed in case of OST- tree. So this problem can be addressed by proposing EOST-tree, which obfuscates the spatiotemporal data for the probability distribution of user’s position belongs to a region is not uniformly distributed. As in real life, the region where a user belongs to depends on many factors related to geography.

Keywords

LBS obfuscation privacy-preserving spatio-temporal indexing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ardagna, C.A., Cremonini, M., Vimercati, S.D.C., Samarati, P.: An Obfuscation-Based Approach for Protecting Location Privacy. TDSC 8(1), 13–27 (2009)Google Scholar
  2. 2.
    Mohamed, F.M.: Privacy in Location-based Services: State-of-the-art and Research Directions. Tutorial, MDM, Germany (2007)Google Scholar
  3. 3.
    Jafarian, J.H., Ravari, A.N., Amini, M., Jalili, R.: Protecting Location Privacy through a Graph-Based Location Representation and a Robust Obfuscation Technique. In: Lee, P.J., Cheon, J.H. (eds.) ICISC 2008. LNCS, vol. 5461, pp. 116–133. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  4. 4.
    Jafarian, J.H., Ravari, A.N., Amini, M., Jalili, R.: Protecting Location Privacy through a Graph-Based Location Representation and a Robust Obfuscation Technique. In: Lee, P.J., Cheon, J.H. (eds.) ICISC 2008. LNCS, vol. 5461, pp. 116–133. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    Ardagna, C.A., Cremonini, M., De Capitani di Vimercati, S., Samarati, P.: An Obfuscation-based Approach for Protecting Location Privacy. In: 7th Framework Programme (FP7/2007-2013) under grant agreement no. 216483 “PrimeLife”Google Scholar
  6. 6.
    Truong, A.T., Truong, Q.C., Dang, T.K.: An Adaptive Grid-Based Approach to Location Privacy Preservation. In: Nguyen, N.T., Katarzyniak, R., Chen, S.-M. (eds.) Advances in Intelligent Information and Database Systems. SCI, vol. 283, pp. 133–144. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Gruteser, M., Grunwald, D.: Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking. In: MOBISYS (2003)Google Scholar
  8. 8.
    Bugra, G., Ling, L.: Protecting Location Privacy with Personalized k- Anonymity: Architecture and Algorithms. IEEETMC 7(1), 1–18 (2008)Google Scholar
  9. 9.
    Truong, A.T., Truong, Q.C., Dang, T.K.: An Adaptive Grid-Based Approach to Location Privacy Preservation. In: Nguyen, N.T., Katarzyniak, R., Chen, S.-M. (eds.) Advances in Intelligent Information and Database Systems. SCI, vol. 283, pp. 133–144. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  10. 10.
    Dinh, L.V.N., Aref, W.G., Mokbel, M.F.: Spatio-temporal Access Methods-Part 2. IEEE Data Engineering Bulletin (2010)Google Scholar
  11. 11.
    Ardagna, C.A., Cremonini, M., Vimercati, S.D.C., Samarati, P.: An Obfuscation-Based Approach for Protecting Location Privacy. IEEE Transactions on Dependable and Secure Computing 8(1) (January- February 2011)Google Scholar
  12. 12.
    Damiani, M.N., Bertino, E., Silvestri, C.: Protecting Location Privacy through Semanticsaware Obfuscation Techniques. In: IFIPTM, Norway, pp. 231–245 (2008)Google Scholar
  13. 13.
    Dang, T.K.: Semantic Based Similarity Searches in Database Systems (Multidimensional Access Methods, Similarity Search Algorithms). PhD thesis, FAW-Institute, Johannes Kepler University of Linz, Austria (May 2003)Google Scholar
  14. 14.
    Damiani, M., Bertino, E., Silvestri, C.: PROBE: an Obfuscation System for the Protection of Sensitive Location Information in LBS. TR2001-145, CERIAS (2008)Google Scholar
  15. 15.
    Saltenis, S., Jensen, C.S., Leutenegger, S.T., Lopez, M.A.: Indexing the Positions of Continuously Moving Objects. In: ACM SIGMOD, USA, pp. 331–342 (2000)Google Scholar
  16. 16.
    Kwon, D., Lee, S., Lee, S.: Indexing the Current Positions of Moving Objects Using the Lazy Update R-tree, supported by the Brain Korea 21 ProjectGoogle Scholar
  17. 17.
    Dang, T.K., Küng, J., Wagner, R.: The SH-tree: A Super Hybrid Index Structure for Multidimensional Data. Springer, Heidelberg (2001)Google Scholar
  18. 18.
    Tao, Y., Sun, J., Papadias, D.: The TPR *- Tree: An Optimized Spatio- Temporal Access Method for Predective queries. In: VLDB Conference, Berlin, Jerminy (2003)Google Scholar
  19. 19.
    Location-Tracking Applications, Published by the IEEE COMPUTER SOCIETY _ 1540-7993/04/$20.00 ©, IEEE _ IEEE Security & Privacy (2004)Google Scholar
  20. 20.
    Guttman, A.: R-trees: A Dynamic Index Structure for Spatial Searching. In: ACM SIGMOD, USA, pp. 47–57 (1984)Google Scholar
  21. 21.
    Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R*-tree: An Efficient and Robust Access Method for Points and Rectangles. In: ACM SIGMOD, pp. 322–331 (1990)Google Scholar
  22. 22.
    Lee, M.L., Hsu, W., Jensen, C.S., Cui, B., Teo, K.L.: Supporting Frequent Updates in R-Trees: A Bottom-Up Approach. Technical Report (April 2004)Google Scholar
  23. 23.
    To, Q.C., Dang, T.K., Küng, J.: OST-tree: An Access Method for Obfuscating Spatiotemporal Data in Location-based Services. In: NTMS, France (2011)Google Scholar
  24. 24.
    Atluri, V., Adam, N.R., Youssef, M.: Towards a unified index scheme for mobile data and customer profiles in a location-based service environment. In: NG2I (2003)Google Scholar
  25. 25.
    Dang, T.K., To, Q.C.: An Extensible and Pragmatic Hybrid Indexing Scheme for MAC-based LBS Privacy-Preserving in Commercial DBMSs. In: ACOMP, pp. 58–67 (2010)Google Scholar
  26. 26.
    To, Q.C., Dang, T.K., Küng, J.: Bob-Tree: An Efficient B + -Tree Based Index Structure for Geographic-Aware Obfuscation. In: Nguyen, N.T., Kim, C.-G., Janiak, A. (eds.) ACIIDS 2011, Part I. LNCS, vol. 6591, pp. 109–118. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  27. 27.
    Atluri, V., Shin, H.: Efficient Security Policy Enforcement in a Location Based Service Environment. In: DBSEC, USA, pp. 61–76 (2007)Google Scholar
  28. 28.
    Gruteser, M., Grunwald, D.: Anonymous Usage of Location-Based Services through Spatial and Temporal Cloaking. In: MOBISYS (2003)Google Scholar
  29. 29.
    Duckham, M., Kulik, L.: A Formal Model of Obfuscation and Negotiation for Location Privacy. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) PERVASIVE 2005. LNCS, vol. 3468, pp. 152–170. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  30. 30.
    Ardagna, C.A., Cremonini, M., Damiani, E., De Capitani di Vimercati, S., Samarati, P.: Supporting location-based conditions in access control policies. In: Proc. of ACM ASIACCS 2006, Taipei, Taiwan (March 2006)Google Scholar
  31. 31.
    Bettini, Wang, X.S., Jajodia., S.: Protecting privacy against location-based personal identification. In: Proc. of the 2nd LDB LDB Workshop on Secure Data Management, Trondheim, Norway (2005)Google Scholar
  32. 32.
    Limkar, S., Kadam, N., Jha, R.K.: Access Control Based on Location and Time. In: Das, V.V., Ariwa, E., Rahayu, S.B. (eds.) SPIT 2011. LNICS, vol. 62, pp. 102–107. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  33. 33.
    Limkar, S.V., Jha, R.K., et al.: Geo-Encryption: A New Way to Secure Critical National Infrastructure. In: International Conference on Information Technology, New Generations, ITNG (2011)Google Scholar
  34. 34.
    Jha, R., Dalal, U.: WiMAX System Simulation and Performance Analysis under the influence of Jamming. Wireless Engineering and Technology (WET) Journal by Scientific Research 1(1), 20–26 (2010)CrossRefGoogle Scholar
  35. 35.
    Jha, R., Dalal, U.D.: A Journey on WiMAX and Its Security Issues. International Journal of Computer Science and Information Technologies 1(4), 256–263 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ashwini Gavali
    • 1
  • Suresh Limkar
    • 2
  • Dnyanashwar Patil
    • 3
  1. 1.Department of Computer EngineeringGHRCEMPuneIndia
  2. 2.Department of Computer EngineeringAISSMS’s IOITPuneIndia
  3. 3.Department of Computer EngineeringDYPCOEPuneIndia

Personalised recommendations