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Research Paper | Computer Science & Engineering | India | Volume 5 Issue 11, November 2016 | Rating: 6.4 / 10

Mining of Association Rules with Privacy Preserving in Horizontally Distributed Databases

Ravi Chinapaga | G Harish Babu | M Balaraju | N Subhash Chandra

Abstract: Information mining is the most quickly developing territory today which is utilized to concentrate basic learning from enormous information accumulations yet frequently these accumulations are isolated among a few parties. Protection responsibility may keep the parties from genuinely giving out the information and some kind of data about the information. In this venture we propose a convention for secure affiliation manage mining in evenly dispersed databases. The current basic convention is that of Kantarcioglu and Clifton surely understood as K & C convention. This convention depends on an unsecured disseminated adaptation of the Apriori calculation named as Fast Distributed Mining (FDM) calculation of Cheung et al. The principle constituents in our convention are two novel secure multi-party calculations one that procedure the union of individual private sets that each of the connecting players hold and another that check whether a component held by one player is incorporated into a subset held by another. This convention recommends improved security concerning the previous conventions. What's more, it is not complex and is conspicuously more effective regarding correspondence cost, correspondence rounds and computational cost.

Keywords: datamining, heterogenous databases, privacy preserving

Edition: Volume 5 Issue 11, November 2016,

Pages: 376 - 379