This study focuses on the rise of Distributed Denial of Service (DDoS) attacks, exacerbated by the increase in Internet of Things (IoT) devices. Such attacks, like those against Amazon Web Services, GitHub, and BBC, cause significant disruptions and financial losses. The research aims to detect and mitigate these attacks early by comparing various supervised learning algorithms on the CIC-IDS 2017 dataset, utilizing a feature set created through five statistical methods and the Smart Detection feature selection algorithm.