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12 June 2023 Development of a machine-learning-based autonomous penetration testing system (Conference Presentation)
Jeremy Straub
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Proceedings Volume 12538, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V; 1253806 (2023) https://doi.org/10.1117/12.2670759
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States
Abstract
Penetration testing is used by numerous organizations, including most in the defense sector, to validate their IT security; however, it has typically been a manually intensive process. Artificial intelligence presents a prospective solution to this challenge, with automated active sensing offering the potential to identify vulnerabilities that time-limited human penetration testers cannot. This paper goes beyond simple automation and presents and evaluates a system that brings together an explainable artificial intelligence technology, a network scanning and modeling technology and an attack automation technology to make penetration testing an optimization problem that can be solved by machine learning.
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Jeremy Straub "Development of a machine-learning-based autonomous penetration testing system (Conference Presentation)", Proc. SPIE 12538, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V, 1253806 (12 June 2023); https://doi.org/10.1117/12.2670759
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KEYWORDS
Machine learning
Active remote sensing
Artificial intelligence
Automation
Defense and security
Design and modelling
Information technology
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