Artificial Intelligence (AI) & Machine Learning (ML) in Security and Penetration Testing
Abstract
This paper investigates the integration of AI and Machine Learning (ML) into security by focusing on automated penetration testing. It explores the reasons for this transition, including the need for increased efficiency, speed, accuracy, and scalability in security assessments. Crucially, the paper also highlights that the rapid adoption of AI introduces a new and diverse attack surface. Attackers are now employing unique AI-specific attacks such as Data Poisoning, Model Poisoning, Data Extraction, Model Extraction, and Model Evasion. Moreover, the availability of AI tools lowers the barrier to entry for cybercrime, a concept referred to as "Vibe Hacking".
Keywords
Artificial Intelligence (AI)
Machine Learning (ML)
Penetration Testing (Pen testing)
Vibe Hacking
Zero Trust Architecture (ZTA)
https://scholar9.com/publication-detail/artificial-intelligence-ai-amp-machine-learnin--38248
Details
Impact Metrics
Ali Basalama
"Artificial Intelligence (AI) & Machine Learning (ML) in Security and Penetration Testing".
Journal of Emerging Technologies and Innovative Research,
vol: 12,
No. 11
Nov. 2025, pp: 29,
https://scholar9.com/publication-detail/artificial-intelligence-ai-amp-machine-learnin--38248