Augmented Rotation-Based Transformation for Privacy-Preserving Data Clustering

Details Augmented Rotation-Based Transformation for Privacy-Preserving Data Clustering Augmented Rotation-Based Transformation for Privacy-Preserving Data Clustering

2010-06-10

arxiv.org/abs/1006.1948v1

ETRI Journal, vol.32, no.3, June 2010, pp.351-361

Computer Science

Cryptography and Security

11 pages, 11 figures, and 6 tables

Scientific paper

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.

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