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http://dx.doi.org/10.4218/etrij.10.0109.0333

Augmented Rotation-Based Transformation for Privacy-Preserving Data Clustering  

Hong, Do-Won (Software Research Laboratory, ETRI)
Mohaisen, Abedelaziz (Software and Content Research Laboratory, ETRI)
Publication Information
ETRI Journal / v.32, no.3, 2010 , pp. 351-361 More about this Journal
Abstract
Multiple rotation-based transformation (MRBT) was introduced recently for mitigating the apriori-knowledge independent component analysis (AK-ICA) attack on rotation-based transformation (RBT), which is used for privacy-preserving data clustering. MRBT is shown to mitigate the AK-ICA attack but at the expense of data utility by not enabling conventional clustering. In this paper, we extend the MRBT scheme and introduce an augmented rotation-based transformation (ARBT) scheme that utilizes linearity of transformation and that both mitigates the AK-ICA attack and enables conventional clustering on data subsets transformed using the MRBT. In order to demonstrate the computational feasibility aspect of ARBT along with RBT and MRBT, we develop a toolkit and use it to empirically compare the different schemes of privacy-preserving data clustering based on data transformation in terms of their overhead and privacy.
Keywords
Privacy preservation; data clustering; measurements; rotation-based transformation;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
Times Cited By Web Of Science : 0  (Related Records In Web of Science)
Times Cited By SCOPUS : 0
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