Efficient privacy preserving distributed clustering based on secret sharing

Authors:
Selim V. Kaya;Thomas B. Pedersen;Erkay Savaş;Yücel Saygin
Affiliations:
Sabanci University, Istanbul, Turkey;Sabanci University, Istanbul, Turkey;Sabanci University, Istanbul, Turkey;Sabanci University, Istanbul, Turkey
Venue:
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Year:
2007

Citing 12
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Abstract

In this paper, we propose a privacy preserving distributed clustering protocol for horizontally partitioned data based on a very efficient homomorphic additive secret sharing scheme. The model we use for the protocol is novel in the sense that it utilizes two noncolluding third parties. We provide a brief security analysis of our protocol from information theoretic point of view, which is a stronger security model. We show communication and computation complexity analysis of our protocol along with another protocol previously proposed for the same problem. We also include experimental results for computation and communication overhead of these two protocols. Our protocol not only out-performs the others in execution time and communication overhead on data holders, but also uses a more efficient model for many data mining applications.