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arXiv · 2002.11828

A Simple and Agile Cloud Infrastructure to Support Cybersecurity Oriented Machine Learning Workflows

Konstantin Berlin·Ajay Lakshminarayanarao
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Abstract

Generating up to date, well labeled datasets for machine learning (ML) security models is a unique engineering challenge, as large data volumes, complexity of labeling, and constant concept drift makes it difficult to generate effective training datasets. Here we describe a simple, resilient cloud infrastructure for generating ML training and testing datasets, that has enhanced the speed at which our team is able to research and keep in production a multitude of security ML models.

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Konstantin Berlin, Ajay Lakshminarayanarao. 2020-02-26. A Simple and Agile Cloud Infrastructure to Support Cybersecurity Oriented Machine Learning Workflows. https://arxiv.org/abs/2002.11828

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