Mitigation of DDoS Attacks in Cloud Servers Using Software-Defined Networking with Validation on CICDDoS 2019 and CAIDA Datasets

Cloud computing has become a critical technology for hosting services, applications, and storage due to its scalability and flexibility. However, its open and distributed architecture makes it a prime target for Distributed Denial of Service (DDoS) attacks, which attempt to overwhelm servers by generating a flood of malicious traffic. These attacks can severely degrade performance, exhaust resources, and cause service outages, resulting in significant financial and operational losses. Traditional defense techniques, such as firewalls and signature-based intrusion detection systems, are increasingly ineffective because they lack the ability to adapt to evolving attack patterns and cannot scale efficiently in large cloud environments. This research proposes a Software-Defined Networking (SDN) based framework for mitigating DDoS attacks in cloud servers. SDN provides a centralized and programmable control plane that allows dynamic monitoring and mitigation of network traffic. In the proposed system, the SDN controller analyzes incoming flows, extracts traffic features, and enforces mitigation rules through OpenFlow switches to block or reroute malicious traffic. The approach is validated using two widely recognized datasets: CICDDoS2019, which represents modern DDoS attack scenarios, and CAIDA, which contains real-world Internet backbone traces of large-scale DDoS attacks. Experimental evaluation shows that the SDN-based framework achieves high detection accuracy, strong precision and recall, and a low false positive rate compared to conventional approaches. The results confirm that SDN enables faster and more adaptive responses to abnormal traffic patterns, making it a suitable defense mechanism for protecting cloud infrastructures. This study demonstrates the potential of combining SDN with traffic analysis for robust DDoS mitigation and provides insights into deploying scalable security solutions in cloud computing environments.