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Distortion Schemes

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Association Rule Hiding for Data Mining

Part of the book series: Advances in Database Systems ((ADBS,volume 41))

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Abstract

In this chapter, we review some popular support-based and confidence-based distortion algorithms that have been proposed in the association rule hiding literature. Distortion-based approaches operate by selecting specific items to include to (or exclude from) selected transactions of the original database in order to facilitate the hiding of the sensitive association rules. Two of the most commonly employed strategies for data distortion involve the swapping of values between transactions [10, 20], as well as the deletion of specific items from the database [54]. In the rest of this chapter, we present an overview of these approaches along with other methodologies that also fit in the same class.

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Correspondence to Aris Gkoulalas-Divanis .

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© 2010 Springer Science+Business Media, LLC

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Gkoulalas-Divanis, A., Verykios, V.S. (2010). Distortion Schemes. In: Association Rule Hiding for Data Mining. Advances in Database Systems, vol 41. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6569-1_6

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  • DOI: https://doi.org/10.1007/978-1-4419-6569-1_6

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  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-6568-4

  • Online ISBN: 978-1-4419-6569-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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