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Distributed Denial of Service (DDoS) attack is a massive menace to web based systems. It immediately overwhelms the web-based system in a short time and interrupts their services. Numerous traditional techniques have been available to detect different kind of DDoS attacks. However, there are several issues encountered with these traditional techniques, such as they require more time for analyzing incoming traffic, failing to identify attacks in realtime, thus itself becoming the victim of DDoS attacks. Therefore, to resolve these issues, we need to implement the DDoS detection system in distributed framework and our proposed approach relies on the distributed Spark Framework. In our DDoS detection approach we worked with different machine learning algorithms, such as Multiclass Logistic Regression, Naive Byes, Decision Trees, and Random Forest. We evaluated our approach using the CIC-DDoS2019 …