SecDD: Efficient and Secure Method for Remotely Training Neural Networks

Ilia Sucholutsky; Matthias Schonlau

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arXiv · 2009.09155

SecDD: Efficient and Secure Method for Remotely Training Neural Networks

Ilia Sucholutsky·Matthias Schonlau

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Abstract

We leverage what are typically considered the worst qualities of deep learning algorithms - high computational cost, requirement for large data, no explainability, high dependence on hyper-parameter choice, overfitting, and vulnerability to adversarial perturbations - in order to create a method for the secure and efficient training of remotely deployed neural networks over unsecured channels.

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Ilia Sucholutsky, Matthias Schonlau. 2020-09-19. SecDD: Efficient and Secure Method for Remotely Training Neural Networks. https://arxiv.org/abs/2009.09155

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