Abstract
In privacy preserving classification for centralized data distorted with a randomization-based techniques nominal and continuous attributes are used. Several methods of preserving privacy classification have been proposed in literature, but no method focused on the special case of attributes - ordered attributes. This paper presents a new approach for ordinal and integer attributes. This approach takes the order of attributes into account during distortion and reconstruction procedure. Effectiveness of the new solution has been tested and presented in this paper.
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Andruszkiewicz, P. (2009). Privacy Preserving Classification for Ordered Attributes. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_37
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DOI: https://doi.org/10.1007/978-3-642-00563-3_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00562-6
Online ISBN: 978-3-642-00563-3
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