Information Theory-Based DDoS Attack Detection in Cloud Computing: A Systematic Survey of Approaches, Challenges, and Future Directions

Distributed denial of service (DDoS) attacks have emerged as a critical challenge for cloud computing, impacting service availability and raising concerns among providers. Despite cloud computing's scalable and flexible architecture, its vulnerabilities make it an attractive target for attackers. This paper presents a comprehensive survey of DDoS attacks in cloud environments, focusing on detection mechanisms leveraging information theory. Key contributions include an analysis of cloud computing characteristics exploited by attackers, a taxonomy of DDoS attacks, and a discussion of effective anomaly detection approaches. Solutions based on information theory, encompassing detection parameters, metrics, and validation techniques, are reviewed for their ability to enhance security with high accuracy and low computational costs. This survey aims to guide researchers and practitioners in developing advanced defenses for cloud applications. Open issues and future research directions are identified to inspire further innovation in mitigating DDoS attacks.