Privacy preserving data mining tools only use in a limited way information and knowledge other than the data base being protected. In this paper we plead on the need of knowledge intensive tools in data privacy. More especifically, we discuss the role of knowledge related tools in data protection and in disclosure risk assessment.


Data Protection Data Privacy Record Linkage Semantic Context Protection Process 
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.


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  1. 1.
    Abril, D., Navarro-Arribas, G., Torra, V.: Choquet Integral for Record Linkage (2010) (manuscript)Google Scholar
  2. 2.
    Abril, D., Navarro-Arribas, G., Torra, V.: Towards privacy preserving information retrieval through semantic microaggregation. In: Proc. 2010 IEEE/WIC/ACM Int. Conf. on Web Intelligence / Intelligent Agent Technology (WI/IAT 2010), Toronto, Canada (2010) (in press)Google Scholar
  3. 3.
    Abril, D., Navarro-Arribas, G., Torra, V.: Towards semantic microaggregation of categorical data for confidential documents. In: Torra, V., Narukawa, Y., Daumas, M. (eds.) MDAI 2010. LNCS (LNAI), vol. 6408, pp. 266–276. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Cano, I., Navarro-Arribas, G., Torra, V.: A new framework to automate constrained microaggregation. In: Proc. PAVLAD Workshop in CIKM 2009, Hong Kong, China, pp. 1–8. ACM, New York (2009) ISBN: 978-1-60558-884-1Google Scholar
  5. 5.
    De Waal, T.: An overview of statistical data editing. Statistics Netherlands (2008)Google Scholar
  6. 6.
    Erola, A., Castellà-Roca, J., Navarro-Arribas, G., Torra, V.: Semantic Microaggregation for the Anonymization of Query Logs. In: Domingo-Ferrer, J., Magkos, E. (eds.) PSD 2010. LNCS, vol. 6344, pp. 127–137. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Granquist, L.: The new view on editing. Int. Statistical Review 65(3), 381–387 (1997)CrossRefGoogle Scholar
  8. 8.
    Lane, J., Heus, P., Mulcahy, T.: Data Access in a Cyber World: Making Use of Cyberinfrastructure. Transactions on Data Privacy 1(1), 2–16 (2008)MathSciNetGoogle Scholar
  9. 9.
    Lefevre, K., Dewitt, D.J., Ramakrishnan, R.: Incognito: efficient full-domain K-anonymity. In: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, SIGMOD 2005, pp. 49–60 (2005)Google Scholar
  10. 10.
    Martinez, S., Sánchez, D., Valls, A.: Ontology-based anonymization of categorical values. In: Torra, V., Narukawa, Y., Daumas, M. (eds.) MDAI 2010. LNCS, vol. 6408, pp. 243–254. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Martínez, S., Valls, A., Sánchez, D.: Anonymizing Categorical Data with a Recoding Method Based on Semantic Similarity. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds.) IPMU 2010. CCIS, vol. 81, pp. 602–611. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Miller, G.: WordNet - about us. WordNet. Princeton University (2009),
  13. 13.
    Navarro-Arribas, G., Torra, V.: Tree-based Microaggregation for the Anonymization of Search Logs. In: Proc. 2009 IEEE / WIC / ACM International Conference on Web Intelligence (WI 2009), Milano, Italy, September 15-18, pp. 155–158 (2009) ISBN: 978-0-7695-3801-3Google Scholar
  14. 14.
    Nin, J., Herranz, J., Torra, V.: Rethinking Rank Swapping to Decrease Disclosure Risk. Data and Knowledge Engineering 64(1), 346–364 (2008)CrossRefGoogle Scholar
  15. 15.
    Nin, J., Herranz, J., Torra, V.: On the Disclosure Risk of Multivariate Microaggregation. Data and Knowledge Engineering 67, 399–412 (2008)CrossRefGoogle Scholar
  16. 16.
    ODP. Open directory project (2010)Google Scholar
  17. 17.
    Pierzchala, M.: A review of the state of the art in automated data editing and imputation. In: Statistical Data Editing, Vol. 1, Conference of European Statisticians Statistical Standards and Studies N. 44, United Nations Statistical Commission and Economic Commission for Europe, 10-40 (1994)Google Scholar
  18. 18.
    Samarati, P.: Protecting Respondents’ Identities in Microdata Release. IEEE Trans. on Knowledge and Data Engineering 13(6), 1010–1027 (2001)CrossRefGoogle Scholar
  19. 19.
    Samarati, P., Sweeney, L.: Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression. SRI Intl. Tech. Rep. (1998)Google Scholar
  20. 20.
    Shlomo, N., De Waal, T.: Protection of Micro-data Subjecto to Edit Constraints Against Statistical Disclousure. Journal of Official statistics 24(2), 229–253 (2008)Google Scholar
  21. 21.
    Sun, X., Li, M., Wang, H., Plank, A.: An efficient hash-based algorithm for minimal k-anonymity. In: 31st Australasian Computer Science Conference (ACSC 2008), Wollongong, NSW, Australia, January 22-25 (2008)Google Scholar
  22. 22.
    Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. of Unc., Fuzz. and Knowledge Based Systems 10(5), 557–570 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  23. 23.
    Torra, V.: Towards the re-identification of individuals in data files with non-common variables. In: Proc. of the 14th European Conference on Artificial Intelligence (ECAI 2000), Berlin, Germany, pp. 326–330. IOS Press, Amsterdam (2000) ISBN 1 58603 013 2Google Scholar
  24. 24.
    Torra, V.: Constrained Microaggregation: Adding Constraints for Data Editing. Transactions on Data Privacy 1(2), 86–104 (2008)MathSciNetGoogle Scholar
  25. 25.
    Torra, V.: Privacy in Data Mining. In: Data Mining and Knowledge Discovery Handbook, 2nd edn., pp. 687–716. Springer, Heidelberg (2010)Google Scholar
  26. 26.
    Torra, V.: On the Definition of Linear Constrained Fuzzy c-Means. In: Proc. of the EUROFUSE 2009, Pamplona, Spain, pp. 61–66 (September 2009) ISBN: 978-84-9769-242-7Google Scholar
  27. 27.
    Torra, V., Abowd, J.M., Domingo-Ferrer, J.: Using Mahalanobis Distance-Based Record Linkage for Disclosure Risk Assessment. In: Domingo-Ferrer, J., Franconi, L. (eds.) PSD 2006. LNCS, vol. 4302, pp. 233–242. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  28. 28.
    Torra, V., Domingo-Ferrer, J.: Record linkage methods for multidatabase data mining. In: Torra, V. (ed.) Information Fusion in Data Mining, pp. 101–132. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  29. 29.
    Torra, V., Nin, J.: Record linkage for database integration using fuzzy integrals. Int. J. of Intel. Systems 23, 715–734 (2008)CrossRefzbMATHGoogle Scholar
  30. 30.
    Verykios, V.S., Bertino, E., Nai Fovino, I., Parasiliti, L., Saygin, Y., Theodoridis, Y.: State-of-the-art in Privacy Preserving Data Mining. SIGMOD Record 33(1), 50–57 (2004)CrossRefGoogle Scholar
  31. 31.
    Willenborg, L., de Waal, T.: Elements of Statistical Disclosure Control. Lecture Notes in Statistics. Springer, Heidelberg (2001)CrossRefzbMATHGoogle Scholar
  32. 32.
    Winkler, W.E.: Re-identification methods for masked microdata. In: Domingo-Ferrer, J., Torra, V. (eds.) PSD 2004. LNCS, vol. 3050, pp. 216–230. Springer, Heidelberg (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Vicenç Torra
    • 1
  1. 1.IIIA, Institut d’Investigació en Intel·ligència ArtificialCSIC, Consejo Superior de Investigaciones CientíficasBellaterraSpain

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