Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Foundations and Practice of Security

FPS 2013: Foundations and Practice of Security pp 189–208Cite as

Collusion Resistant Inference Control for Cadastral Databases

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8352))

Abstract

In this paper we present a novel inference control technique, based on graphs, to control the number of accessible parcels in a cadastral database. Different levels of collusion resistance are introduced as part of the approach. The dynamic aspect of the cadastral application, caused by mutation operations, is handled. We propose a scheme for gradually resetting the inference graph allowing continuous access to the data.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Les guides de la cnil. les collectivités locales. http://www.cnil.fr/fileadmin/documents/Guides_pratiques/CNIL_Guide_CollLocales.pdf (2009)

  2. Fiscalité locale et cadastre. http://www.cada.fr/fiscalite-locale-et-cadastre,6090.html. Accessed June 2013

  3. Biskup, J., Bonatti, P.: Controlled query evaluation for known policies by combining lying and refusal. Ann. Math. Artif. Intell. 40(1), 37–62 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  4. Biskup, J., Tadros, C.: Inference-proof view update transactions with minimal refusals. In: Garcia-Alfaro, J., Navarro-Arribas, G., Cuppens-Boulahia, N., de Capitani di Vimercati, S. (eds.) DPM 2011 and SETOP 2011. LNCS, vol. 7122, pp. 104–121. Springer, Heidelberg (2012)

    Google Scholar 

  5. Chen, Y., Chu, W.: Protection of database security via collaborative inference detection. In: Chen, H., Yang, C.C. (eds.) Intelligence and Security Informatics, pp. 275–303. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  6. Conejo, C., Velasco, A.: Cadastral web services in spain. http://www.ec-gis.org/Workshops/13ec-gis/presentations/4_sdi_implementaion_I_Conejo_1.pdf. Accessed June 2013

  7. Cuppens, F., Gabillon, A.: Logical foundations of multilevel databases. Data Knowl. Eng. 29(3), 259–291 (1999)

    Article  MATH  Google Scholar 

  8. Cuppens, F., Gabillon, A.: Cover story management. Data Knowl. Eng. 37(2), 177–201 (2001)

    Article  MATH  Google Scholar 

  9. Delugach, H., Hinke, T.: Wizard: a database inference analysis and detection system. IEEE Trans. Knowl. Data Eng. 8(1), 56–66 (1996)

    Article  Google Scholar 

  10. Denning, D.E., Lunt, T.F., Schell, R.R., Shockley, W.R., Heckman, M.: The seaview security model. In: Proceedings of the 1988 IEEE Symposium on Security and Privacy, 1988, pp. 218–233. IEEE (1988)

    Google Scholar 

  11. Dwork, C.: Differential privacy: a survey of results. In: Agrawal, M., Du, D.-Z., Duan, Z., Li, A. (eds.) TAMC 2008. LNCS, vol. 4978, pp. 1–19. Springer, Heidelberg (2008)

    Google Scholar 

  12. Farkas, C., Jajodia, S.: The inference problem: a survey. ACM SIGKDD Explor. Newsl. 4(2), 6–11 (2002)

    Article  Google Scholar 

  13. Farkas, C., Toland, T.S., Eastman, C.M.: The inference problem and updates in relational databases. In: Proceedings of the Fifteenth Annual Working Conference on Database and Application Security Das’01, pp. 181–194. Kluwer Academic Publishers, Norwell (2002)

    Google Scholar 

  14. Jajodia, S., Meadows, C.: Inference problems in multilevel secure database management systems. In: Abrams, M.D., Jajodia, S., Podell, H. (eds.) Information Security: An Integrated Collection of Essays, pp. 570–584. IEEE Computer Society Press, Los Alamitos (1995)

    Google Scholar 

  15. Katos, V., Vrakas, D., Katsaros, P.: A framework for access control with inference constraints. In: 2011 IEEE 35th Annual Computer Software and Applications Conference (COMPSAC), pp. 289–297. IEEE (2011)

    Google Scholar 

  16. Lunt, T.F.: Aggregation and inference: facts and fallacies. In: Proceedings of the 1989 IEEE Symposium on Security and Privacy, 1989, pp. 102–109. IEEE (1989)

    Google Scholar 

  17. Machanavajjhala, A., Kifer, D., Gehrke, J., Venkitasubramaniam, M.: l-diversity: privacy beyond k-anonymity. ACM Trans. Knowl. Discov. Data (TKDD) 1(1), 3 (2007)

    Article  Google Scholar 

  18. McSherry, F., Talwar, K.: Mechanism design via differential privacy. In: 48th Annual IEEE Symposium on Foundations of Computer Science, 2007, FOCS’07, pp. 94–103. IEEE (2007)

    Google Scholar 

  19. Sandhu, R.S., Jajodia, S.: Polyinstantiation for cover stories. In: Deswarte, Y., Quisquater, J.-J., Eizenberg, G. (eds.) Computer Security - ESORICS 92. LNCS, vol. 648, pp. 305–328. Springer, Heidelberg (1992)

    Google Scholar 

  20. Staddon, J.: Dynamic inference control. In: Proceedings of the 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, pp. 94–100. ACM (2003)

    Google Scholar 

  21. Staddon, J., Golle, P., Zimny, B.: Web-based inference detection. In: Proceedings of 16th USENIX Security Symposium, pp. 71–86 (2007)

    Google Scholar 

  22. Sweeney, L.: Simple Demographics Often Identify People Uniquely. Health (San Francisco), pp. 1–34. Carnegie Mellon University, Pittsburgh (2000)

    Google Scholar 

  23. Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 10(05), 557–570 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  24. Toland, T., Farkas, C., Eastman, C.: The inference problem: maintaining maximal availability in the presence of database updates. Comput. Secur. 29(1), 88–103 (2010)

    Article  Google Scholar 

  25. Xiao, X., Tao, Y.: Anatomy: simple and effective privacy preservation. In: Proceedings of the 32nd International Conference on Very Large Data Bases, pp. 139–150. VLDB Endowment (2006)

    Google Scholar 

  26. Yang, X., Li, C.: Secure xml publishing without information leakage in the presence of data inference. In: Proceedings of the Thirtieth International Conference on Very Large Data Bases, vol. 30, pp. 96–107. VLDB Endowment (2004)

    Google Scholar 

  27. Yip, R., Levitt, E.: Data level inference detection in database systems. In: Proceedings of the 11th IEEE Computer Security Foundations Workshop, 1998, pp. 179–189. IEEE (1998)

    Google Scholar 

  28. Yixiang, D., Tao, P., Minghua, J.: Secure multiple xml documents publishing without information leakage. In: International Conference on Convergence Information Technology, 2007, pp. 2114–2119. IEEE (2007)

    Google Scholar 

Download references

Acknowledgments

The authors wish to thank the following people for fruitful discussions on some legal aspects applying to the cadastral application and for providing them access to a sample cadastral database. – Tania Berthou, Directrice des Affaires Foncières de la Polynésie Française; – Bertrand Malet, Chef de la Division du Cadastre, Direction des Affaires Foncières; – Jean-Louis Garry, Directeur du Service Informatique de la Polynésie Française; – Emmanuel Bouniot, Chef de la Cellule Systèmes d’Informations Géographique du Service Informatique de la Polynésie Française.

Author information

Authors and Affiliations

  1. Université de la Polynésie française, BP 6570, Faa’a Aéroport, French Polynesia

    Firas Al Khalil, Alban Gabillon & Patrick Capolsini

Authors
  1. Firas Al Khalil
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alban Gabillon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Patrick Capolsini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Firas Al Khalil .

Editor information

Editors and Affiliations

  1. Dept. Commun. & Electronique, Télécom ParisTech, Paris, France

    Jean Luc Danger

  2. Concordia Institute for Information Syst Concordia University Research Chair Tier, Concordia University, Montreal, Québec, Canada

    Mourad Debbabi

  3. École des Mines, Nancy, France

    Jean-Yves Marion

  4. RST Department, Rm A105-2, Télécom SudParis, Evry, France

    Joaquin Garcia-Alfaro

  5. Dalhousie University, Halifax, Nova Scotia, Canada

    Nur Zincir Heywood

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Al Khalil, F., Gabillon, A., Capolsini, P. (2014). Collusion Resistant Inference Control for Cadastral Databases. In: Danger, J., Debbabi, M., Marion, JY., Garcia-Alfaro, J., Zincir Heywood, N. (eds) Foundations and Practice of Security. FPS 2013. Lecture Notes in Computer Science(), vol 8352. Springer, Cham. https://doi.org/10.1007/978-3-319-05302-8_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-05302-8_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05301-1

  • Online ISBN: 978-3-319-05302-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation