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Reseach Article

Secure Distributed Data Mining

Published on December 2014 by Priyanka Khairnar
Innovations and Trends in Computer and Communication Engineering
Foundation of Computer Science USA
ITCCE - Number 2
December 2014
Authors: Priyanka Khairnar
96c3be20-2c07-419b-b0ce-77a65eb71cfd

Priyanka Khairnar . Secure Distributed Data Mining. Innovations and Trends in Computer and Communication Engineering. ITCCE, 2 (December 2014), 23-25.

@article{
author = { Priyanka Khairnar },
title = { Secure Distributed Data Mining },
journal = { Innovations and Trends in Computer and Communication Engineering },
issue_date = { December 2014 },
volume = { ITCCE },
number = { 2 },
month = { December },
year = { 2014 },
issn = 0975-8887,
pages = { 23-25 },
numpages = 3,
url = { /proceedings/itcce/number2/19050-2016/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 Innovations and Trends in Computer and Communication Engineering
%A Priyanka Khairnar
%T Secure Distributed Data Mining
%J Innovations and Trends in Computer and Communication Engineering
%@ 0975-8887
%V ITCCE
%N 2
%P 23-25
%D 2014
%I International Journal of Computer Applications
Abstract

Security is the important paradigmin data rule mining projects. This project addresses the problem of secure distributed association rule mining over the horizontally distributed database. Through mining, interesting relations and patterns between variables of large database can be observed securely using cryptographic techniques and the mining algorithms. Round robin technique is used for Horizontal distribution of Data sets to reduce the data skew. Security concerns may prevent the sites from direct sharing of data and some type of information about the data. The paper introduces cryptographic techniques to provide security in order to minimize the information shared in mining.

References
  1. T. Tassa Secure Mining of association rules in horizontally distributed Database. 2014
  2. G. Alex and A. Freitas, "Scalable, high-performance data mining with parallel processing,"in Principles and Practice of Knowledge Discovery in Databases, (Nantes, France),1998.
  3. R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large Database. In VLDB, pages 487499, 1994.
  4. A. V. Ev_mievski, R. Srikant, R. Agrawal, and J. Gehrke. Privacy preserving mining of association rules. In KDD, pages 217228, 2002.
  5. D. W. L. Cheung, J. Han, V. T. Y. Ng, A. W. C. Fu, and Y. Fu. A fast distributed algorithm for mining association rules. In PDIS, pages 3142, 1996.
  6. R. L. Rivest, A. Shamir, and L. M. Adleman, "A Method for Obtaining Digital Signatures and Public-Key Cryptosystems," Comm. ACM, vol. 21, no. 2, pp. 120-126, 1978.
  7. A. Ben-David, N. Nisan, and B. Pinkas, "FairplayMP - A System for Secure Multi-Party Computation," Proc. 15th ACM Conf. Computer and Comm. Security (CCS), pp. 257-266, 2008.
  8. M. Bellare, R. Canetti, and H. Krawczyk, "Keying Hash Functions for Message Authentication," Proc. 16th Ann. Int'l Cryptology Conf. Advances in Cryptology (Crypto), pp. 1-15, 1996.
  9. M. Kantarcioglu and C. Clifton. Privacy-preserving distributed mining of association rules on horizontally partitioned data. IEEE Transactions on Knowledge and Data Engineering, 16:10261037, 2004.
  10. T. Tassa and E. Gudes. Secure distributed computation of anonymizedviews of shared databases. Transactions on Database Systems, 37, Article 11, 2012.
  11. T. Tassa, A. Jarrous, and J. Ben-Ya'akov. Oblivious evaluation ofmultivariate polynomials. Submitted.
  12. J. Brickell and V. Shmatikov. Privacy-preserving graph algorithms inthe semi-honest model. In ASIACRYPT, pages 236–252, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Distributed Mining Rsa Distributed Apriori Algorithm Multiparty Computation