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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Hlavní autoři:	Mohammed A. Makarem, Muneef A. Razaz, Zead Saleh
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2026-04-01
Edice:	Future Internet
Témata:	reinforcement learning Q-learning DQN attack graphs network defense attacker–defender game
On-line přístup:	https://www.mdpi.com/1999-5903/18/5/239
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