Privacy Preserving Association Rule Mining in Distributed Environments using Fp-Growth Algorithm and Elliptic Curve Cryptography

T  Nusrat Jabeen   and M  Chidambaram

doi:10.17485/ijst/2016/v9i48/93737

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Privacy Preserving Association Rule Mining in Distributed Environments using Fp-Growth Algorithm and Elliptic Curve Cryptography

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2016/v9i48/93737

Year: 2016, Volume: 9, Issue: 48, Pages: 1-5

Original Article

Privacy Preserving Association Rule Mining in Distributed Environments using Fp-Growth Algorithm and Elliptic Curve Cryptography

T. Nusrat Jabeen^1* and M. Chidambaram2

¹ Department of Computer Science, Bharathiyar University, Coimbatore, Tamil Nadu, India; [email protected]
² Computer Science Department, Rajah Serfoji Government College, Thanjavur, Tamil Nadu, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

In this paper, we present a privacy preserving association rule mining method in distributed environments. The proposed method uses FP-growth algorithm and combination of elliptic curve cryptography and digital signature. The proposed method is low in cost for both computation and communication. This method uses associative third party, which is the central authority, holding common cryptographic keys of all the sites and responsible for performing distributed ARM. This method maintains privacy regardless of any number of dishonest sites in the distributed environment.
Keywords: Association Rule Mining, ARM, Cryptography, Digital Signature, Elliptic Curve, FP-Growth, Privacy in ARM