Generative AI for Cyber-Physical System Automated Penetration Testing
Keywords:
Generative AI, penetration testing, cyber-physical systems, cybersecurityAbstract
Modern infrastructure links cyber-physical systems to the physical and digital worlds. Rising complexity and interconnection risk cybersecurity. CPS security may improve with generative AI penetration testing. This work investigates whether deep learning and reinforcement learning-based generative AI models can automatically find CPS vulnerabilities. The paper discusses penetration testing using AI and its pros and cons. Generative models may uncover and resolve security flaws using AI-simulated attack scenarios. The study explores ethical issues, constraints, and potential CPS security trends using generative AI, promoting more research. Generative AI has great potential for CPS penetration testing, but implementation, accuracy, and abuse must be addressed.
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