Giggins, Helen

Brankovic, Ljiljana

2012-12

<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>

Conferences in Research and Practice in Information Technology Series, v.134, p. 139-148

9781921770142

https://hdl.handle.net/1959.11/62016

en

Australian Computer Society, Inc

VICUS - A noise addition technique for categorical data

Conference Publication

Publication