Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Predicting Adversary Lateral Movement Patterns with Deep Learning   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

32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph