CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
Reseach Article

Secure Sum based Privacy Preservation Association Rule Mining on Horizontally Partitioned Data

by Bhawani Singh Rathore, Anju Singh, Divakar Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 134 - Number 14
Year of Publication: 2016
Authors: Bhawani Singh Rathore, Anju Singh, Divakar Singh
10.5120/ijca2016908084

Bhawani Singh Rathore, Anju Singh, Divakar Singh . Secure Sum based Privacy Preservation Association Rule Mining on Horizontally Partitioned Data. International Journal of Computer Applications. 134, 14 ( January 2016), 10-14. DOI=10.5120/ijca2016908084

@article{ 10.5120/ijca2016908084,
author = { Bhawani Singh Rathore, Anju Singh, Divakar Singh },
title = { Secure Sum based Privacy Preservation Association Rule Mining on Horizontally Partitioned Data },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 134 },
number = { 14 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 10-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume134/number14/23981-2016908084/ },
doi = { 10.5120/ijca2016908084 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:34:12.349928+05:30
%A Bhawani Singh Rathore
%A Anju Singh
%A Divakar Singh
%T Secure Sum based Privacy Preservation Association Rule Mining on Horizontally Partitioned Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 134
%N 14
%P 10-14
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The method of perturbation has been basically studied for the privacy preserving data mining. In this technique, from a known distribution random noise is combined to the private data before forwarding the data to the data miner. Consequently, the data miner constructs again a presumption to the original distribution of data from the perturbed data and the reconstructed distribution is used for the purposes of data mining. The goal of privacy preserving data mining researchers is to introduce techniques of data mining which could be implemented on the databases without break the privacy of the persons. Techniques of Privacy preserving for several models of data mining have been suggested, originally for the classification on the organized data then for association rules in the distributed area. This paper suggested a solution for the computing the data mining classification algorithm for the horizontally partitioned data privately without revealing any information related to the sources or data. The given method (PPDM) integrates the benefits of the RSA public key cryptographic system and homomorphic scheme of encryption.

References
  1. Kiran P, S Sathish Kumar and Dr Kavya “A Novel Framework using Elliptic Curve Cryptography for Extremely Secure Transmission in Distributed Privacy Preserving Data Mining”, An International Journal (ACIJ), Vol.3, No.2, March 2012.
  2. “Modified Distributed Rk Secure Sum Protocol”, Jyotirmayee Rautaray, Raghvendra Kumar, Garima Bajpai, International Journal of Innovative Research in Science, Engineering and Technology Vol. 2, Issue 3, March 2013.
  3. M tamer Ozsu Patrick Valduriez, Principles of Distributed Database Systems ,3 rd Edition.
  4. “Privacy Preserving Association Rule Mining in Horizontally Partitioned Databases Using Cryptography Techniques”, N V Muthu lakshmi,Dr. K Sandhya Rani, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 3 (1) , 2012, 3176 – 3182.
  5. Sugumar, Jayakumar, R., Rengarajan, C “Design a Secure Multi Site Computation System for Privacy Preserving Data Mining”. International Journal of Computer Science and Telecommunications, Vol 3, pp.101-105. 2012.
  6. N V Muthu Lakshmi, Dr. K Sandhya Rani ,“Privacy Preserving Association Rule Mining without Trusted Site for Horizontal Partitioned database”, International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.2, pp.17-29, 2012.
  7. N V Muthu lakshmi, Dr. K Sandhya Rani, “Privacy Preserving Association Rule Mining in Horizontally Partitioned Databases Using Cryptography Techniques”, International Journal of Computer Science and Information Technologies( IJCSIT), Vol. 3 (1) , PP. 3176 – 3182, 2012.
  8. “Distributed algorithm for privacy preserving data mining based on ID3 and improved secure sum”, Ehsan Molaei, Hossein Vadiatizadeh, Amirmahdi mohammadighavam, Neda Rajabpour, Fatemeh ziasistani, International Journal of Advanced studies in Computer Science and Engineering IJASCSE, Volume 3, Issue 1, 2014.
  9. “A Review on Privacy Preserving Data Mining: Techniques and Research Challenges”, Shweta Taneja, Shashank Khanna, Sugandha Tilwalia, Ankita, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (2) , 2014, 2310-2315.
  10. “Implementation Of Cryptography For Privacy Preserving Data Mining”, Anand Sharma and Vibha Ojha , International Journal of Database Management Systems ( IJDMS ) Vol.2, No.3, August 2010.
  11. R. Sheikh, B. Kumar and D. K. Mishra, “Changing Neighbors k- Secure Sum Protocol for Secure Multi-party Computation,” Accepted for publication in the International Journal of Computer Science and Information Security, USA, Vol.7 No.1, pp. 239-243, Jan. 2010.
  12. Jian Wang, Yongcheng Luo, Yan Zhao and Jiajin Le, "A Survey on Privacy Preserving Data Mining" ,in IEEE, 2009 First International Workshop on Database Technology and Applications.
Index Terms

Computer Science
Information Sciences

Keywords

Horizontally Partitioned Dataset Secure Sum Privacy Preservation Association Rules.