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Privacy-Preserving Distributed Data Mining Techniques: A Survey

by V. Baby, N. Subhash Chandra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 143 - Number 10
Year of Publication: 2016
Authors: V. Baby, N. Subhash Chandra
10.5120/ijca2016910381

V. Baby, N. Subhash Chandra . Privacy-Preserving Distributed Data Mining Techniques: A Survey. International Journal of Computer Applications. 143, 10 ( Jun 2016), 37-41. DOI=10.5120/ijca2016910381

@article{ 10.5120/ijca2016910381,
author = { V. Baby, N. Subhash Chandra },
title = { Privacy-Preserving Distributed Data Mining Techniques: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 143 },
number = { 10 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 37-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume143/number10/25116-2016910381/ },
doi = { 10.5120/ijca2016910381 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:46:03.870498+05:30
%A V. Baby
%A N. Subhash Chandra
%T Privacy-Preserving Distributed Data Mining Techniques: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 143
%N 10
%P 37-41
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In various distributed data mining settings, leakage of the real data is not adequate because of privacy issues. To overcome this problem, numerous privacy-preserving distributed data mining practices have been suggested such as protect privacy of their data by perturbing it with a randomization algorithm and using cryptographic techniques. In this paper, we review and provide extensive survey on different privacy preserving data mining methods and analyses the representative techniques for privacy preserving data mining. We majorly discuss the distributed privacy preservation techniques which provide secure solutions using primitive operations of cryptographic protocols such as secure multi-party computation (SMPC), secret sharing schemes (SSS) and homomorphic encryption (HC).

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Index Terms

Computer Science
Information Sciences

Keywords

Data mining K-means clustering Data privacy Privacy preserving Multiparty computation Threshold Cryptography.

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