It security incident response on DDOS attack using machine learning

This thesis aims to study Distributed Denial of Service (DDoS) attacks, a malevolent method used by attackers to prevent legitimate user access by overwhelming network resources. Specifically, these attacks often involve the attacker exploiting a multitude of client devices, infected with malware, and coordinating them to inundate the network infrastructure. In this thesis, a variety of machine learning algorithms will be utilized and investigated for their effectiveness in detecting DDoS attacks.