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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| 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 |
| Subjects: | |
| Online Access: | https://journals.najah.edu/media/journals/full_texts/2_5sPDfPY.pdf |
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