VICUS - A noise addition technique for categorical data

Title: VICUS - A noise addition technique for categorical data
Creator: Giggins, Helen; Brankovic, Ljiljana
Publisher Link: http://dx.doi.org/10th Australasian Data Mining Conference (AusDM 2012). Proceedings of Data Mining and Analytics 2012 (AusDM 2012): Conferences in Research and Practice in Information Technology (CRPIT), Vol. 134, (Sydney, Australia 05-07 December, 2012) p. 139-148
Relation: ARC.DP0452182
Relation: http://www.crpit.com/abstracts/CRPITV134Giggins.html
Publisher: Australian Computer Society
Resource Type: conference paper
Date: 2012
Description: Privacy preserving data mining and statistical disclosure control have received a great deal of attention during the last few decades. Existing techniques are generally classified as restriction and data modification. Within data modification techniques noise addition has been one of the most widely studied but has traditionally been applied to numerical values, where the measure of similarity is straightforward. In this paper we introduce VICUS, a novel privacy preserving technique that adds noise to categorical data. Experimental evaluation indicates that VICUS performs better than random noise addition both in terms of security and data quality.
Subject: data mining; data modification techniques; VICUS; random noise addition
Identifier: http://hdl.handle.net/1959.13/1064494
Identifier: uon:17571
Identifier: ISBN:9781921770142
Language: eng
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