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Association Rule Sharing Model for Privacy Preservation and Collaborative Data Mining Efficiency

KumaraSwamy, S and Manjula, SH and Venugopal, KR and Iyengar, SS and Patnaik, LM (2015) Association Rule Sharing Model for Privacy Preservation and Collaborative Data Mining Efficiency. In: 2014 RECENT ADVANCES IN ENGINEERING AND COMPUTATIONAL SCIENCES (RAECS), MAR 06-08, 2014, Chandigarh, INDIA.

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Official URL: http://dx.doi.org/10.1109/RAECS.2014.6799597

Abstract

The disclosure of information and its misuse in Privacy Preserving Data Mining (PPDM) systems is a concern to the parties involved. In PPDM systems data is available amongst multiple parties collaborating to achieve cumulative mining accuracy. The vertically partitioned data available with the parties involved cannot provide accurate mining results when compared to the collaborative mining results. To overcome the privacy issue in data disclosure this paper describes a Key Distribution-Less Privacy Preserving Data Mining (KDLPPDM) system in which the publication of local association rules generated by the parties is published. The association rules are securely combined to form the combined rule set using the Commutative RSA algorithm. The combined rule sets established are used to classify or mine the data. The results discussed in this paper compare the accuracy of the rules generated using the C4. 5 based KDLPPDM system and the CS. 0 based KDLPPDM system using receiver operating characteristics curves (ROC).

Item Type: Conference Proceedings
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Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Keywords: Privacy Preserving Data Mining; Vertically Partitioned Data; Association Rules; C4.5 Algorithm; See5.0/C5.0 Algorithm; Commutative RSA; ROC
Department/Centre: Division of Electrical Sciences > Electronic Systems Engineering (Formerly, (CEDT) Centre for Electronic Design & Technology)
Date Deposited: 24 Apr 2015 06:25
Last Modified: 24 Apr 2015 06:25
URI: http://eprints.iisc.ernet.in/id/eprint/51412

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