Master's Thesis at the University of Basrah Discusses Airport Cybersecurity
A Master's thesis at the College of Engineering at the University of Basrah examined airport cybersecurity: using machine learning techniques to detect and mitigate advanced persistent threats.
The thesis, presented by student Zainab Salem Aziz, aims to enhance airport cybersecurity using machine learning techniques to detect and counter advanced long-term attacks (ALAs). These are complex attacks that infiltrate networks and remain undetected for long periods of time, with the aim of stealing data or disrupting systems.
The thesis included four chapters in which the student discussed the adoption of a large language model (LLaMA2) from Meta, one of the latest AI models for language processing. It was used to analyze network logs, recognize anomalies, and detect indicators of compromise early. The basic idea is to integrate AI with traditional cybersecurity tools to reduce reliance on manual analysis and accelerate response to attacks.
Department of Media and Governmental Communication
