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International Journal of

Recent Trends in Engineering

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International Journal of Recent Trends in Engineering (IJRTE)

ISSN 1797-9617

Volume 1, Number 1, May 2009

Issue on Computer Science

Page(s): 627-629

Sprouting Modus Operandi for Selection of the Best PPDM using Agent Based PPDMT in the Health Care Domain

K. Murugesan, J.Gitanjali, J.Indumathi, D. Manjula

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Abstract

Escalating data safety entails an agency to publish less detailed or more befuddled data. In this paper we have attempted to appraise the evolving agent based Modus Operandi for Selection of The Best Privacy Preserving Data Mining (PPDM) PPDM Technique for a health care application. We illustrate how our Modus Operandi are used for the comparison of optional data releases and how we can customize it for selection of The Best PPDM Technique for any real time Application. We target our attention on the predicament of grading optional concealed data sets on the basis of the values of data privacy and data utility that the befuddles produce. We attempt to use models to generate the simulated data when the users have a multiplicity of models and even classes of models which they would like to apply to the released data.

Index Terms

Befuddle, Confidentiality, Data distribution, Privacy, Privacy Preserving Data Mining (PPDM), Safety, Statistical Disclosure Control, Validity

Published by Academy Publisher in cooperation with the ACEEE

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