Researcher Zainab Salem Aziz's master's thesis was discussed at the College of Engineering, University of Basra, Department of Computer Engineering. It focuses on enhancing airport cybersecurity using machine learning techniques to detect and counter advanced persistent threats (APTs). 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 work relied on a large language model (LLaMA2) from Meta, one of the latest AI models for language processing. It was employed 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 speed up response to attacks.
It is worth noting that the researcher published three research papers during her research: the first at the World Congress of Engineers, the second in a Scopus-indexed international journal, and the third in a local journal. It is worth noting that the framework for this project, in its first trial version, is ready for marketing to companies and institutions involved in cybersecurity affairs, and for further development to suit the needs of those institutions in serving this vital sector in our beloved country
