Software Engineering

ISSN Online: 2376-8037 ISSN Print: 2376-8029

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Volume 1, Issue 1, July 2013

  • Authors: S. Suresh, S. Uvaraj, N. Kannaiya Raja

    Abstract: Association rules mining is a frequently used technique which finds interesting association and correlation relationships among large set of data items which occur frequently together. Nowadays, data collection is ubiquitous in social and business areas. Many companies and organi¬zations want to do the collaborative association rules mining to get the joint benefits. However, the sensitive information leakage is a problem we have to solve and privacy- preserving techniques are strongly needed. In this paper, we focus on the privacy issue of the association rules mining and propose a secure frequent-pattern tree (FP-tree) based scheme to pre- serve private information while doing the collaborative association rules mining. We display that our schema is secure and collusion-resistant for n parties, which means that even if n - 1 dishonest party collude with a dishonest data miner in an attempt to learn the associations’ rules between honest respondents and their responses, they will be unable to success.

    Received: Jun. 1, 2013 Accepted: Published: Jun. 20, 2013

    DOI: 10.11648/j.se.20130101.11 View: Downloads: