Generative AI for Cyber Security Response

This project aims to examine the potential for current cyber security methods to be replaced or augmented with machine learning models by methodologically utilising an array of generative models to perform a variety of cyber security tasks. This research will consist of the following research questions (RQ):

1) Are generative AI capable of producing realistic network topologies, including where and how to integrate cyber security applications optimally? 2) Can ML models generate background network traffic for a given network topology and detect anomalous network traffic? 3) To extent can generative ML models generate malicious cyber threat attack paths for a

given network topography?