A Framework for High-Accuracy Privacy-Preserving Mining

Agrawal, Shipra and Haritsa, Jayant R (2005) A Framework for High-Accuracy Privacy-Preserving Mining. In: 21st International Conference on Data Engineering, ICDE 2005, 5-8 April, Japan, 193 -204.

Preview

PDF a_frame_work_for_high.pdf Download (280kB)

Abstract

To preserve client privacy in the data mining process, a variety of techniques based on random perturbation of individual data records have been proposed recently. In this paper, we present FRAPP, a generalized matrix-theoretic framework of random perturbation, which facilitates a systematic approach to the design of perturbation mechanisms for privacy-preserving mining. Specifically, FRAPP is used to demonstrate that (a) the prior techniques differ only in their choices for the perturbation matrix elements, and (b) a symmetric perturbation matrix with minimal condition number can be identified, maximizing the accuracy even under strict privacy guarantees. We also propose a novel perturbation mechanism wherein the matrix elements are themselves characterized as random variables, and demonstrate that this feature provides significant improvements in privacy at only a marginal cost in accuracy. The quantitative utility of FRAPP, which applies to random-perturbation-based privacy-preserving mining in general, is evaluated specifically with regard to frequent-itemset mining on a variety of real datasets. Our experimental results indicate that, for a given privacy requirement, substantially lower errors are incurred, with respect to both itemset identity and itemset support, as compared to the prior techniques.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre:	Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	08 Apr 2008
Last Modified:	19 Sep 2010 04:21
URI:	http://eprints.iisc.ac.in/id/eprint/4076

Actions (login required)

View Item