Other Knowledge Hiding Methodologies

  • Aris Gkoulalas-Divanis
  • Vassilios S. Verykios
Part of the Advances in Database Systems book series (ADBS, volume 41)


Association rule hiding algorithms aim at protecting sensitive knowledge captured in the form of frequent itemsets or association rules. However, (sensitive) knowledge may appear in various forms directly related to the applied data mining algorithm that achieved to expose it. Consequently, a set of hiding approaches have been proposed over the years to allow for the safeguarding of sensitive knowledge exposed by data mining tasks such as clustering, classification and sequence mining. In this chapter, we briefly discuss some state-of-the-art approaches for the hiding of sensitive knowledge that is depicted in any of the aforementioned formats.


Association Rule Frequent Itemsets Data Owner Original Database Privacy Preserve 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Aris Gkoulalas-Divanis
    • 1
  • Vassilios S. Verykios
    • 2
  1. 1.Information Analytics LabIBM Research GmbH - ZurichRueschlikonSwitzerland
  2. 2.Department of Computer and Communication EngineeringUniversity of ThessalyVolosGreece

Personalised recommendations