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International Workshop on Data Privacy Management

International Workshop on Autonomous and Spontaneous Security

DPM 2013, SETOP 2013: Data Privacy Management and Autonomous Spontaneous Security pp 362–368Cite as

Dynamic Anonymous Index for Confidential Data

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8247))

Abstract

In this paper we introduce a \(k\)-anonymous vector space model, which can be used as an index of a set of confidential documents. This model allows to index, for example, encrypted data. New documents can be added or removed while maintaining the k-anonymity property of the vector space.

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References

  1. Abril, D., Navarro-Arribas, G., Torra, V.: Vector space model anonymization. In: Sixteenth International Conference of the Catalan Association of Artificial Intelligence (CCIA 2013) (to appear)

    Google Scholar 

  2. Byun, J.-W., Sohn, Y., Bertino, E., Li, N.: Secure anonymization for incremental datasets. In: Jonker, W., Petković, M. (eds.) SDM 2006. LNCS, vol. 4165, pp. 48–63. Springer, Heidelberg (2006)

    Google Scholar 

  3. Domingo-Ferrer, J., Mateo-Sanz, J.M.: Practical data-oriented microaggregation for statistical disclosure control. IEEE Trans. Knowl. Data Eng. 14, 189–201 (2002)

    Article  Google Scholar 

  4. Cao, J., Carminati, B., Ferrari, E., Tan, K.-L.: CASTLE: continuously anonymizing data streams. IEEE Trans. Dependable Secure Comput. 8(3), 337–352 (2011)

    Article  Google Scholar 

  5. De Capitani di Vimercati, S., Foresti, S., Livraga, G.: Privacy in data publishing. In: Garcia-Alfaro, J., Navarro-Arribas, G., Cavalli, A., Leneutre, J. (eds.) DPM 2010 and SETOP 2010. LNCS, vol. 6514, pp. 8–21. Springer, Heidelberg (2011)

    Google Scholar 

  6. Iwuchukwu, T., Naughton, J.F.: K-anonymization as spatial indexing: toward scalable and incremental anonymization. In: Proceedings of the 33rd International Conference on Very Large Data Bases, Vienna, Austria, pp. 746–757 (2007)

    Google Scholar 

  7. Li, J., Ooi, B.C., Wang, W.: Anonymizing streaming data for privacy protection. In: IEEE 24th International Conference on Data Engineering, ICDE 2008, pp. 1367–1369 (2008)

    Google Scholar 

  8. Manning, C.D., Raghavan, P., Schütze, H.: An Introduction to Information Retrieval. Cambridge University Press, Cambridge (2009)

    Google Scholar 

  9. Pei, J., Xu, J., Wang, Z., Wang, W., Wang, K.: Maintaining K-anonymity against incremental updates. In: 19th International Conference on Scientific and Statistical Database Management, SSBDM 2007 (2007)

    Google Scholar 

  10. Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)

    Article  Google Scholar 

  11. Reuters Ltd., Reuters-21578, Distribution 1.0 (2004). http://www.daviddlewis.com/resources/testcollections/reuters21578

  12. Samarati, P.: Protecting respondents identities in microdata release. IEEE Trans. Knowl. Data Eng. 13(6), 1010–1027 (2001)

    Article  Google Scholar 

  13. Stokes, K., Torra, V.: Multiple releases of k-anonymous data sets and k-anonymous relational databases. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 20(06), 839–853 (2012)

    Article  MathSciNet  Google Scholar 

  14. Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 10(5), 557–570 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  15. Truta, T.M., Campan, A.: K-anonymization incremental maintenance and optimization techniques. In: Proceedings of the ACM Symposium on Applied Computing, pp. 380–387 (2007)

    Google Scholar 

  16. Xiao, X., Tao, Y.: M-invariance: towards privacy preserving re-publication of dynamic datasets. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 689–700 (2007)

    Google Scholar 

  17. Zakerzadeh, H., Osborn, S.L.: FAANST: fast anonymizing algorithm for numerical streaming DaTa. In: Garcia-Alfaro, J., Navarro-Arribas, G., Cavalli, A., Leneutre, J. (eds.) DPM 2010 and SETOP 2010. LNCS, vol. 6514, pp. 36–50. Springer, Heidelberg (2011)

    Google Scholar 

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Acknowledgments

This Work is partially funded by projects TSI2007-65406-C03-02, ARES-CONSOLIDER INGENIO 2010 CSD2007-00004, TIN2010-15764, and TIN2011-27076-C03-03 of the Spanish Government, and by project FP7/2007-2013 (Data without Boundaries). work contributed by one of the authors was carried out as part of the Computer Science Ph.D. program of the Universitat Autònoma de Barcelona (UAB).

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Authors and Affiliations

  1. Department Enginyeria de la Informació i de les Comunicacions (DEIC), Universitat Autònoma de Barcelona (UAB), Campus de la UAB, 08193, Bellaterra, Catalonia, Spain

    Guillermo Navarro-Arribas

  2. Institut d’Investigació en Intel.ligència Artificial (IIIA), Consejo Superior de Investigaciones Científicas (CSIC), Campus de la UAB, 08193, Bellaterra, Catalonia, Spain

    Daniel Abril & Vicenç Torra

Authors
  1. Guillermo Navarro-Arribas
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  2. Daniel Abril
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  3. Vicenç Torra
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Corresponding author

Correspondence to Guillermo Navarro-Arribas .

Editor information

Editors and Affiliations

  1. TELECOM SudParis, Evry, France

    Joaquin Garcia-Alfaro

  2. National Technical University of Athens, Athens, Greece

    Georgios Lioudakis

  3. TELECOM Bretagne, Cesson Sévigné, France

    Nora Cuppens-Boulahia

  4. University College Cork, Cork, Ireland

    Simon Foley

  5. IDA Ovens, EMC Information Systems International, Cork, Ireland

    William M. Fitzgerald

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Navarro-Arribas, G., Abril, D., Torra, V. (2014). Dynamic Anonymous Index for Confidential Data. In: Garcia-Alfaro, J., Lioudakis, G., Cuppens-Boulahia, N., Foley, S., Fitzgerald, W. (eds) Data Privacy Management and Autonomous Spontaneous Security. DPM SETOP 2013 2013. Lecture Notes in Computer Science(), vol 8247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54568-9_23

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  • DOI: https://doi.org/10.1007/978-3-642-54568-9_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54567-2

  • Online ISBN: 978-3-642-54568-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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