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Machine Learning in Penetration Testing by panigrahirudraprasad1 is a document available to read on EtoBox.

What is Machine Learning in Penetration Testing about?

The paper discusses the integration of machine learning into penetration testing to automate the process and enhance efficiency, addressing the skills and time constraints of manual testing. It proposes the development of an automated penetration testing tool using reinforcement learning and the MITRE ATT&CK Framework to identify vulnerabilities and generate attack paths. The results indicate that the machine learning-based tool, named Shennina, outperforms traditional methods by efficiently discovering vul

Author

panigrahirudraprasad1

Language

EN