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Papers CyberBattleSim

“CyberBattleSim” 태그가 달린 논문 6편 · 필터 해제

Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents

2025-05-16 · Diksha Goel, Kristen Moore, Jeff Wang, Minjune Kim 외

Reinforcement Learning (RL) agents are increasingly used to simulate sophisticated cyberattacks, but their decision-making processes remain opaque, hindering trust, debugging, and defensive preparedness. In high-stakes c…

CyberBattleSimReinforcement Learning (RL)

Out of the Cage: How Stochastic Parrots Win in Cyber Security Environments

2023-08-23 · Maria Rigaki, Ondřej Lukáš, Carlos A. Catania, Sebastian Garcia

Large Language Models (LLMs) have gained widespread popularity across diverse domains involving text generation, summarization, and various natural language processing tasks. Despite their inherent limitations, LLM-based…

CyberBattleSimCyberBattleSim (RL) chain scenarioDecision MakingNetSecGame+6

Adversarial Agents For Attacking Inaudible Voice Activated Devices

2023-07-23 · Forrest McKee, David Noever

The paper applies reinforcement learning to novel Internet of Thing configurations. Our analysis of inaudible attacks on voice-activated devices confirms the alarming risk factor of 7.6 out of 10, underlining significant…

CyberBattleSimQ-Learningreinforcement-learning

A Multiagent CyberBattleSim for RL Cyber Operation Agents

2023-04-03 · Thomas Kunz, Christian Fisher, James La Novara-Gsell, Christopher Nguyen 외

Hardening cyber physical assets is both crucial and labor-intensive. Recently, Machine Learning (ML) in general and Reinforcement Learning RL) more specifically has shown great promise to automate tasks that otherwise wo…

CyberBattleSimReinforcement Learning (RL)

Incorporating Deception into CyberBattleSim for Autonomous Defense

2021-08-31 · Erich Walter, Kimberly Ferguson-Walter, Ahmad Ridley

Deceptive elements, including honeypots and decoys, were incorporated into the Microsoft CyberBattleSim experimentation and research platform. The defensive capabilities of the deceptive elements were tested using reinfo…

CyberBattleSimreinforcement-learningReinforcement LearningReinforcement Learning (RL)

Statistical learning for accurate and interpretable battery lifetime prediction

2021-01-06 · Peter M. Attia, Kristen A. Severson, Jeremy D. Witmer

Data-driven methods for battery lifetime prediction are attracting increasing attention for applications in which the degradation mechanisms are poorly understood and suitable training sets are available. However, while …

BIG-bench Machine LearningCyberBattleSimFeature Engineering
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