AI-Enhanced Ethical Hacking: A Linux-Focused Experiment
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913535618973696 |
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| author | Al-Sinani, Haitham S. Mitchell, Chris J. |
| author_facet | Al-Sinani, Haitham S. Mitchell, Chris J. |
| contents | This technical report investigates the integration of generative AI (GenAI), specifically ChatGPT, into the practice of ethical hacking through a comprehensive experimental study and conceptual analysis. Conducted in a controlled virtual environment, the study evaluates GenAI's effectiveness across the key stages of penetration testing on Linux-based target machines operating within a virtual local area network (LAN), including reconnaissance, scanning and enumeration, gaining access, maintaining access, and covering tracks. The findings confirm that GenAI can significantly enhance and streamline the ethical hacking process while underscoring the importance of balanced human-AI collaboration rather than the complete replacement of human input. The report also critically examines potential risks such as misuse, data biases, hallucination, and over-reliance on AI. This research contributes to the ongoing discussion on the ethical use of AI in cybersecurity and highlights the need for continued innovation to strengthen security defences. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_05105 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AI-Enhanced Ethical Hacking: A Linux-Focused Experiment Al-Sinani, Haitham S. Mitchell, Chris J. Cryptography and Security Artificial Intelligence This technical report investigates the integration of generative AI (GenAI), specifically ChatGPT, into the practice of ethical hacking through a comprehensive experimental study and conceptual analysis. Conducted in a controlled virtual environment, the study evaluates GenAI's effectiveness across the key stages of penetration testing on Linux-based target machines operating within a virtual local area network (LAN), including reconnaissance, scanning and enumeration, gaining access, maintaining access, and covering tracks. The findings confirm that GenAI can significantly enhance and streamline the ethical hacking process while underscoring the importance of balanced human-AI collaboration rather than the complete replacement of human input. The report also critically examines potential risks such as misuse, data biases, hallucination, and over-reliance on AI. This research contributes to the ongoing discussion on the ethical use of AI in cybersecurity and highlights the need for continued innovation to strengthen security defences. |
| title | AI-Enhanced Ethical Hacking: A Linux-Focused Experiment |
| topic | Cryptography and Security Artificial Intelligence |
| url | https://arxiv.org/abs/2410.05105 |