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Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
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Modeling Extraction Transformation Load Embedding Privacy Preservation using UML

by Kiran P, S Sathish Kumar, Kavya N P
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 6
Year of Publication: 2012
Authors: Kiran P, S Sathish Kumar, Kavya N P
10.5120/7772-0854

Kiran P, S Sathish Kumar, Kavya N P . Modeling Extraction Transformation Load Embedding Privacy Preservation using UML. International Journal of Computer Applications. 50, 6 ( July 2012), 1-5. DOI=10.5120/7772-0854

@article{ 10.5120/7772-0854,
author = { Kiran P, S Sathish Kumar, Kavya N P },
title = { Modeling Extraction Transformation Load Embedding Privacy Preservation using UML },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 6 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number6/7772-0854/ },
doi = { 10.5120/7772-0854 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:47:34.870762+05:30
%A Kiran P
%A S Sathish Kumar
%A Kavya N P
%T Modeling Extraction Transformation Load Embedding Privacy Preservation using UML
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 6
%P 1-5
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Extraction Transformation Load plays an important phase in development of data warehouse due its complexity of selecting data from different location and having different structures. The recent industry of data warehouse is driven by Privacy Preserving Data Mining which ensures privacy of sensitive information during Mining and is a requirement of most Data Bases. Current approaches to modelling extraction transformation load do not include privacy representation in Conceptual Modelling. This paper proposes object-oriented approach to model Extraction Transformation Load embedding privacy preservation. The major components of extraction include Data Source, Source Identifier, Retrieval, Join, Privacy Preserving Area and Data Staging Area. All the above mentioned components have been modelled using Unified Modelling Language.

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Index Terms

Computer Science
Information Sciences

Keywords

Privacy Preserving Data Mining ETL Data Stage Area Privacy Preserving Area Data Warehouse

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