Author(s) |
Giggins, Helen
Brankovic, Ljiljana
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Publication Date |
2012-12
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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>
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Citation |
Conferences in Research and Practice in Information Technology Series, v.134, p. 139-148
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ISBN |
9781921770142
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Link | |
Publisher |
Australian Computer Society, Inc
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Title |
VICUS - A noise addition technique for categorical data
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Type of document |
Conference Publication
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Entity Type |
Publication
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