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January 8, 2015
Kelwin Fernandes, Kelwin Fernandes, P. C. P. S · 2015
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Tony Lindgren, J. B · 2016
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Group, A. F. S · 2018
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2020

Privacy Preserving PCA for Multiparty Modeling

Liu, Yingting, Chen, Chaochao, Zheng, Longfei et al.

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In this paper, we present a general multiparty modeling paradigm with Privacy Preserving Principal Component Analysis (PPPCA) for horizontally partitioned data.

PPPCA can accomplish multiparty cooperative execution of PCA under the premise of keeping plaintext data locally.
We also propose implementations using two techniques, i.e., homomorphic encryption and secret sharing.
The output of PPPCA can be sent directly to data consumer to build any machine learning models.