Predicting Adversary Lateral Movement Patterns with Deep Learning

Nathan Danneman; James Hyde

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arXiv · 2104.13195

Predicting Adversary Lateral Movement Patterns with Deep Learning

Nathan Danneman·James Hyde

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Abstract

This paper develops a predictive model for which host, in an enterprise network, an adversary is likely to compromise next in the course of a campaign. Such a model might support dynamic monitoring or defenses. We generate data for this model using simulated networks, with hosts, users, and adversaries as first-class entities. We demonstrate the predictive accuracy of the model on out-of-sample simulated data, and validate the findings against data captured from a Red Team event on a live enterprise network

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Nathan Danneman, James Hyde. 2021-04-23. Predicting Adversary Lateral Movement Patterns with Deep Learning. https://arxiv.org/abs/2104.13195

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