Penetration Testing and Attack Automation Simulation: Deep Reinforcement Learning Approach

In this research, we propose a revolutionary deep reinforcement learning-based methodology for automated penetration testing. The suggested method uses a deep Q-learning network to develop attack sequences that effectively exploit weaknesses in a target system. The method is tested in a virtual envi...

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Bibliographic Details
Main Authors: Ismael Jabr, Yanal Salman, Motasem Shqair, Amjad Hawash
Format: Article
Language:English
Published: An-Najah National University 2024-08-01
Series:مجلة جامعة النجاح للأبحاث العلوم الطبيعية
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Online Access:https://journals.najah.edu/media/journals/full_texts/2_5sPDfPY.pdf
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