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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Mohammed A. Makarem, Muneef A. Razaz, Zead Saleh
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2026-04-01
Sarja:	Future Internet
Aiheet:	reinforcement learning Q-learning DQN attack graphs network defense attacker–defender game
Linkit:	https://www.mdpi.com/1999-5903/18/5/239
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!