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The Road Towards Autonomous Cybersecurity Agents: Remedies for Simulation Environments

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F24%3A00135174" target="_blank" >RIV/00216224:14330/24:00135174 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-031-54129-2_43" target="_blank" >http://dx.doi.org/10.1007/978-3-031-54129-2_43</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-54129-2_43" target="_blank" >10.1007/978-3-031-54129-2_43</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    The Road Towards Autonomous Cybersecurity Agents: Remedies for Simulation Environments

  • Original language description

    One of the fundamental challenges in developing autonomous cybersecurity agents (AICA) is providing them with appropriate training environments for skills acquisition and evaluation. Current reinforcement learning (RL) algorithms rely on myriads of training runs to instill proper behavior, and this is reasonably achievable only within a simulated environment. In this paper, we explore the topic of simulation models and environments for RL and present an assessment framework to compare simulation models designed for simulating cyberattack scenarios. We examine four existing simulation tools, including a new one by the authors of the paper, and discuss their properties, particularly in terms of deployability, to support RL-based AICA. In the example of complex scenarios, we compare the two most sophisticated simulation tools and discuss their strengths.

  • Czech name

  • Czech description

Classification

  • 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)

Result continuities

  • Project

    <a href="/en/project/VJ02010020" target="_blank" >VJ02010020: AI-Dojo: Multiagent Testbed for Research and Testing of AI-driven Cybersecurity Technologies</a><br>

  • Continuities

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

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    COMPUTER SECURITY. ESORICS 2023 INTERNATIONAL WORKSHOPS, CPS4CIP, PT II

  • ISBN

    9783031541285

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    738-749

  • Publisher name

    Springer Nature Switzerland AG

  • Place of publication

    BERLIN

  • Event location

    The Haague

  • Event date

    Sep 28, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001212380000033