Co-Adaptive Attacker–Defender Learning over Attack Graphs: A Stochastic Game Approach to Dynamic Network Defense

The evolving landscape of cybersecurity threats, characterized by increasingly sophisticated and adaptive attackers, poses major challenges to traditional static network defense mechanisms. To address these limitations, this paper proposes an adaptive cyber defense framework that integrates Reinforc...

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Detalhes bibliográficos

Principais autores:	Mohammed A. Makarem, Muneef A. Razaz, Zead Saleh
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-04-01
Colecção:	Future Internet
Assuntos:	reinforcement learning Q-learning DQN attack graphs network defense attacker–defender game
Acesso em linha:	https://www.mdpi.com/1999-5903/18/5/239
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