Optimal Deception Asset Deployment in Cybersecurity: A Nash Q-Learning Approach in Multi-Agent Stochastic Games

In the face of an increasingly intricate network structure and a multitude of security threats, cyber deception defenders often employ deception assets to safeguard critical real assets. However, when it comes to the intranet lateral movement attackers in the cyber kill chain, the deployment of dece...

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Principais autores:	Guanhua Kong, Fucai Chen, Xiaohan Yang, Guozhen Cheng, Shuai Zhang, Weizhen He
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2023-12-01
Colecção:	Applied Sciences
Assuntos:	cyber deception defense stochastic game multi-agent reinforcement learning Nash Q-learning
Acesso em linha:	https://www.mdpi.com/2076-3417/14/1/357
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