Skip to main content

A Privacy-Preserving Architecture for the Semantic Web Based on Tag Suppression

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6264))

Abstract

We propose an architecture that preserves user privacy in the semantic Web via tag suppression. In tag suppression, users may wish to tag some resources and refrain from tagging some others in order to hinder privacy attackers in their efforts to profile users’ interests. Following this strategy, our architecture helps users decide which tags should be suppressed. We describe the implementation details of the proposed architecture and provide further insight into the modeling of profiles. In addition, we present a mathematical formulation of the optimal trade-off between privacy and tag suppression rate.

This work was supported in part by the Spanish Government under Projects CONSOLIDER INGENIO 2010 CSD2007-00004 “ARES” and TSI2007-65393-C02-02 “ITACA”, and by the Catalan Government under Grant 2009 SGR 1362.

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

Buying options

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Scient. Amer. (May 2001)

    Google Scholar 

  2. Michlmayr, E., Cazer, S.: Learning user profiles from tagging data and leveraging them for personal(ized) information access. In: Proc. Workshop Tagging and Metadata for Social Inform. Org. Workshop in Int. WWW Conf. (2007)

    Google Scholar 

  3. John, A., Seligmann, D.: Collaborative tagging and expertise in the enterprise. In: Proc. Col. Web Tagging Workshop WWW (2006)

    Google Scholar 

  4. Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquisition 5(2), 199–220 (1993)

    Article  Google Scholar 

  5. Brickley, D., Guha, R.V.: RDF vocabulary description language 1.0: RDF schema. W3c recommendation, W3C (February 2004), http://www.w3.org/TR/2004/REC-rdf-schema-20040210/

  6. OWL Working Group, W.: OWL 2 Web Ontology Language: Document Overview. W3C Recommendation (October 27, 2009), http://www.w3.org/TR/owl2-overview/

  7. Mcdonald, A.M., Reeder, R.W., Kelley, P.G., Cranor, L.F.: A comparative study of online privacy policies and formats. In: Proc. Workshop Privacy Enhanc. Technol. (PET), pp. 37–55. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  8. Jensen, C., Potts, C., Jensen, C.: Privacy practices of internet users: Self-reports versus observed behavior. Int. J. Human-Comput. Stud. 63(1-2), 203–227 (2005)

    Article  Google Scholar 

  9. Kagal, L., Finin, T., Joshi, A.: A policy based approach to security for the semantic web. In: Proc. Int. Semantic Web Conf., pp. 402–418 (2003)

    Google Scholar 

  10. Kagal, L., Paolucci, M., Srinivasan, N., Denker, G., Finin, T., Sycara, K.: Authorization and privacy for semantic web services. IEEE J. Intelligent Syst. 19(4), 50–56 (2004)

    Article  Google Scholar 

  11. Elovici, Y., Shapira, B., Maschiach, A.: A new privacy model for hiding group interests while accessing the web. In: Proc. ACM Workshop on Privacy in the Electron. Society, pp. 63–70. ACM, New York (2002)

    Google Scholar 

  12. Shapira, B., Elovici, Y., Meshiach, A., Kuflik, T.: PRAW – The model for PRivAte Web. J. Amer. Soc. Inform. Sci., Technol. 56(2), 159–172 (2005)

    Article  Google Scholar 

  13. Frakes, W.B., Baeza-Yates, R.A. (eds.): Information Retrieval: Data Structures & Algorithms. Prentice-Hall, Englewood Cliffs (1992)

    Google Scholar 

  14. Kuflik, T., Shapira, B., Elovici, Y., Maschiach, A.: Privacy preservation improvement by learning optimal profile generation rate. In: Brusilovsky, P., Corbett, A.T., de Rosis, F. (eds.) UM 2003. LNCS, vol. 2702, pp. 168–177. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  15. Howe, D.C., Nissenbaum, H.: TrackMeNot (2006)

    Google Scholar 

  16. Toubiana, V.: SquiggleSR (2007)

    Google Scholar 

  17. Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. ACM Commun. 18(11), 613–620 (1975)

    Article  MATH  Google Scholar 

  18. Rebollo-Monedero, D., Forné, J., Domingo-Ferrer, J.: From t-closeness-like privacy to postrandomization via information theory. IEEE Trans. Knowl. Data Eng. (October 2009)

    Google Scholar 

  19. Cover, T.M., Thomas, J.A.: Elements of Information Theory, 2nd edn. Wiley, New York (2006)

    MATH  Google Scholar 

  20. Jaynes, E.T.: On the rationale of maximum-entropy methods. Proc. IEEE 70(9), 939–952 (1982)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Parra-Arnau, J., Rebollo-Monedero, D., Forné, J. (2010). A Privacy-Preserving Architecture for the Semantic Web Based on Tag Suppression. In: Katsikas, S., Lopez, J., Soriano, M. (eds) Trust, Privacy and Security in Digital Business. TrustBus 2010. Lecture Notes in Computer Science, vol 6264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15152-1_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15152-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15151-4

  • Online ISBN: 978-3-642-15152-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics