  In this paper, we present a secure logistic regression training protocol and
its implementation, with a new subprotocol to securely compute the activation
function. To the best of our knowledge, we present the fastest existing secure
Multi-Party Computation implementation for training logistic regression models
on high dimensional genome data distributed across a local area network.
