The goal is to research and develop a distributed and federated learning architecture for better protection of computers by training a ML model on network attacks. The work includes the migration of current algorithms into the network security problem, then to research variations or new model to address the specific problems of security, then to implement it inside the Slips IDS system.
Federated Learning for Network Security