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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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Principais autores: Mohammed A. Makarem, Muneef A. Razaz, Zead Saleh
פורמט: Artigo
שפה:Inglês
יצא לאור: MDPI AG 2026-04-01
סדרה:Future Internet
נושאים:
reinforcement learning
Q-learning
DQN
attack graphs
network defense
attacker–defender game
גישה מקוונת:https://www.mdpi.com/1999-5903/18/5/239
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