Advancing cloud security
Mohamed Ouhssini, Karim Afdel, Mohamed Akouhar, Elhafed Agherrabi, Abdallah Abrada · 2025
This chapter focuses on the detection of Distributed Denial of Service (DDoS) attacks in cloud environments. DDoS attacks pose a significant threat to the reliability and security of cloud services. The chapter highlights the increasing reliance on cloud technology and the need for robust DDoS detection mechanisms in this context. The research aims to develop interpretable machine learning (ML) (IML) models for DDoS detection in the cloud and evaluates the performance of three algorithms (Random Forest, Decision Tree, and CatBoost) in detecting DDoS attacks. The study emphasizes the importance of interpretability in artificial intelligence (AI) systems and its practical applications in empowering enterprises to effectively counteract DDoS threats and safeguard their cloud infrastructure.