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 thatit utilizes two non-colluding third parties. We provide a brief security analysis of our protocol from information theoreticpoint of view, which is a stronger security model. We show communication and computation complexity analysis of our protocolalong with another protocol previously proposed for the same problem. We also include experimental results for computationand communication overhead of these two protocols. Our protocol not only outperforms the others in execution time and communicationoverhead on data holders, but also uses a more efficient model for many data mining applications.
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