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Reseach Article

A Survey: Privacy Preserving Data Mining

by Komal Kapadia, Raksha Chauhan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 112 - Number 2
Year of Publication: 2015
Authors: Komal Kapadia, Raksha Chauhan
10.5120/19642-1228

Komal Kapadia, Raksha Chauhan . A Survey: Privacy Preserving Data Mining. International Journal of Computer Applications. 112, 2 ( February 2015), 41-44. DOI=10.5120/19642-1228

@article{ 10.5120/19642-1228,
author = { Komal Kapadia, Raksha Chauhan },
title = { A Survey: Privacy Preserving Data Mining },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 112 },
number = { 2 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume112/number2/19642-1228/ },
doi = { 10.5120/19642-1228 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:48:25.207119+05:30
%A Komal Kapadia
%A Raksha Chauhan
%T A Survey: Privacy Preserving Data Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 112
%N 2
%P 41-44
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Privacy preserving data mining techniques are introduced with the aim of extract the relevant knowledge from the large amount of data while protecting the sensible information at the same time. The success of data mining relies on the availability of high quality data. To ensure quality of data mining, effective information sharing between organizations becomes a vital requirement in today's society. Privacy preserving data mining deals with hiding an individual's sensitive identity without sacrificing the usability of data. Whenever we are concerning with data mining, Security is measure issue while extracting data. Privacy Preserving Data Mining concerns with the security of data and provide the data on demand as well as amount of data that is required.

References
  1. Neelamadhab Padhy, Dr. Pragnyaban Mishra & Rasmita Panigrahi. "The Survey of Data Mining Applications and Feature Scope. " 2012 IJCSEIT.
  2. Xinjun qi, Mingkui zong. "An overview of privacy preserving data mining. " 2011 ICESE.
  3. Kishori pawar, Y. B. gurav. "Overview of privacy in horizontally distributed databases. " 2014 IJIRAE.
  4. Manish Sharma, Atul chaudhary , Manish mathuria & Shalini chaudhary. "A review study on the privacy preserving data mining techniques and approaches. ". 2013 IJCST.
  5. Shweta taneja, shashank khanna, sugandha tilwalia, ankita. "A review on privacy preserving data mining: techniques and research challenges. " 2014 IJCSIT.
  6. Jayanti dansana, Raghvendra kumar & Jyotirmayee rautaray. "Techniques for privacy preserving association rule mining in distributed database. " 2012 IJCSITS.
  7. Xuan canh nguyen, Tung anh cao. "An enhanced scheme for privacy preserving association rules minig on horizonatally distributed databases. " 2012 IEEE.
  8. Manish Sharma, Atul chaudhary, Manish mathuria, Shalini chaudhary & Santosh kumar. "An efficient approach for privacy preserving in data mining. " 2014 IEEE.
  9. Rachit v. Adhvaryu, Nikunj h. Domadiya. "Privacy preserving in association rule mining on horizontally partitioned database. " 2014 IJARCET.
  10. Jayanti Dansana , Raghvendra Kumar , Debadutta Dey. "Privacy preservation in horizontally partitioned databases using randomized response technique. " 2013 IEEE.
  11. Rachit v. Adhvaryu, Nikunj h. Domadiya, "Research Trends in Privacy Preserving in Association Rule Mining (PPARM) On Horizontally Partitioned Database". 2014 IJEDR.
  12. Agrawal D. Aggarwal C. C. On the Design and Quantification of Privacy-Preserving Data Mining Algorithms. ACM PODS Conference, 2002.
  13. D. W. Cheung,etal. ,Ecient Mining of Association Rules in Distributed Databases, "IEEE Trans. Knowledge and Data Eng. , vol. 8, no. 6, 1996,pp. 911-922.
Index Terms

Computer Science
Information Sciences

Keywords

MHS algorithm EMHS algorithm CK secure sum and Randomized response technique.