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Privacy Protection by Matrix Transformation

Weijia YANG

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Summary :

Privacy preserving is indispensable in data mining. In this paper, we present a novel clustering method for distributed multi-party data sets using orthogonal transformation and data randomization techniques. Our method can not only protect privacy in face of collusion, but also achieve a higher level of accuracy compared to the existing methods.

Publication
IEICE TRANSACTIONS on Information Vol.E92-D No.4 pp.740-741
Publication Date
2009/04/01
Publicized
Online ISSN
1745-1361
DOI
10.1587/transinf.E92.D.740
Type of Manuscript
LETTER
Category
Data Mining

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