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

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Privacy Preserving Techniques on Centralized, Distributed and Social Network Data – A Review

by R. Padmaja, V. Santhi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 140 - Number 8
Year of Publication: 2016
Authors: R. Padmaja, V. Santhi
10.5120/ijca2016909430

R. Padmaja, V. Santhi . Privacy Preserving Techniques on Centralized, Distributed and Social Network Data – A Review. International Journal of Computer Applications. 140, 8 ( April 2016), 48-52. DOI=10.5120/ijca2016909430

@article{ 10.5120/ijca2016909430,
author = { R. Padmaja, V. Santhi },
title = { Privacy Preserving Techniques on Centralized, Distributed and Social Network Data – A Review },
journal = { International Journal of Computer Applications },
issue_date = { April 2016 },
volume = { 140 },
number = { 8 },
month = { April },
year = { 2016 },
issn = { 0975-8887 },
pages = { 48-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume140/number8/24618-2016909430/ },
doi = { 10.5120/ijca2016909430 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:41:46.039722+05:30
%A R. Padmaja
%A V. Santhi
%T Privacy Preserving Techniques on Centralized, Distributed and Social Network Data – A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 140
%N 8
%P 48-52
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Privacy Preserving Data Publishing refers publishing data in such a way that the privacy of the individuals are preserved. The Published data can further be used for various Data Analysis and Data Mining tasks. Techniques used to preserve privacy of individuals before publishing is called Anonymization Techniques. Initially only centralized data need to be published for analysis and Mining. Later with the advent of Internet, it has become necessary to publish Distributed and Social network data. The Anonymization Techniques that are applied on Centralized data can be applied on both Distributed and Social Network data with little modifications. This Paper is to present a brief review of Anonymization Techniques like k-anonymity and l-diversity on Centralized, Distributed and Social Network Data.

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Index Terms

Computer Science
Information Sciences

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