A Survey on Sanitizing Methods in Association Rule Hiding Technique

Authors(2) :-Apoorva Joshi , Pratima Gautam

In current years, the use of data mining techniques and related applications has enlarged a lot as it is used to extract important knowledge from large amount of data. Now a days the incredible growth of data in every field[1]. This increment of the data created lots of challenges in privacy. Privacy preserving in data mining becomes too essential due to share this data for our benefit purpose[2].This shared data may contain sensitive attributes, Database containing sensitive knowledge must be protected against illegal access. Therefore this it has become necessary to hide sensitive knowledge in database. Privacy preserving data mining (PPDM) try to conquer this problem by protecting the privacy of data without sacrificing the integrity of data. A number of techniques have been proposed for privacy-preserving data mining. To address this problem, Privacy Preservation Data Mining (PPDM) include association rule hiding method to protect privacy of sensitive data against association rule mining. In this paper, we survey different existing approaches to association rule hiding, along with some open challenges. We have also summarized few of the recent evolution. and a review of different techniques for privacy preserving data mining along with merits and demerits.

Authors and Affiliations

Apoorva Joshi
Career College Bhopal, Aisect University, Bhopal, Madhya Pradesh, India
Pratima Gautam
Career College Bhopal, Aisect University, Bhopal, Madhya Pradesh, India

Privacy Preservation Data Mining, Association rule hiding, Data Mining

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Publication Details

Published in : Volume 2 | Issue 6 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 780-785
Manuscript Number : CSEIT1726215
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Apoorva Joshi , Pratima Gautam, "A Survey on Sanitizing Methods in Association Rule Hiding Technique", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.780-785, November-December-2017.
Journal URL : http://ijsrcseit.com/CSEIT1726215

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