NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarios

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00372772" target="_blank" >RIV/68407700:21230/24:00372772 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/978-3-031-54129-2_35" target="_blank" >https://doi.org/10.1007/978-3-031-54129-2_35</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-54129-2_35" target="_blank" >10.1007/978-3-031-54129-2_35</a>

Result language

angličtina

Original language name

NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarios

Original language description

Current frameworks for training offensive penetration testing agents with deep reinforcement learning struggle to produce agents that perform well in real-world scenarios, due to the reality gap in simulation-based frameworks and the lack of scalability in emulation-based frameworks. Additionally, existing frameworks often use an unrealistic metric that measures the agents' performance on the training data. NASimEmu, a new framework introduced in this paper, addresses these issues by providing both a simulator and an emulator with a shared interface. This approach allows agents to be trained in simulation and deployed in the emulator, thus verifying the realism of the used abstraction. Our framework promotes the development of general agents that can transfer to novel scenarios unseen during their training. For the simulation part, we adopt an existing simulator NASim and enhance its realism. The emulator is implemented with industry-level tools, such as Vagrant, VirtualBox, and Metasploit. Experiments demonstrate that a simulation-trained agent can be deployed in emulation, and we show how to use the framework to train a general agent that transfers into novel, structurally different scenarios. NASimEmu is available as open-source.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISBN

978-3-031-54128-5

ISSN

0302-9743

e-ISSN

1611-3349

Number of pages

20

Pages from-to

589-608

Publisher name

Springer Science and Business Media Deutschland GmbH

Place of publication

—

Event location

Hague

Event date

Sep 25, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001212380000025