Cryptology ePrint Archive: Report 2019/1246

A Note on Our Submission to Track 4 of iDASH 2019

Marcel Keller and Ke Sun

Abstract: iDASH is a competition soliciting implementations of cryptographic schemes of interest in the context of biology. In 2019, one track asked for multi-party computation implementations of training of a machine learning model suitable for two datasets from cancer research. In this note, we describe our solution submitted to the competition. We found that the training can be run on three AWS c5.9xlarge instances in less then one minute using MPC tolerating one semi-honest corruption, and less than ten seconds at a slightly lower accuracy. After seeing some winning solutions, we have lowered this figure to less than a second.

Category / Keywords: implementation / Machine learning, multi-party computation

Date: received 24 Oct 2019, last revised 29 Mar 2020

Contact author: marcel keller at data61 csiro au

Available format(s): PDF | BibTeX Citation

Note: Improved results using approximate sigmoid function

Version: 20200330:024204 (All versions of this report)

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