VICUS - A noise addition technique for categorical data

Author(s)
Giggins, Helen
Brankovic, Ljiljana
Publication Date
2012-12
Abstract
<p>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 <i>VICUS</i>, a novel privacy preserving technique that adds noise to categorical data. Experimental evaluation indicates that <i>VICUS</i> performs better than random noise addition both in terms of security and data quality.</p>
Citation
Conferences in Research and Practice in Information Technology Series, v.134, p. 139-148
ISBN
9781921770142
Link
Publisher
Australian Computer Society, Inc
Title
VICUS - A noise addition technique for categorical data
Type of document
Conference Publication
Entity Type
Publication

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