DDoS Attacks Mitigation: A Review of AI-Based Strategies and Techniques

In the evolving landscape of cyber threats, Distributed Denial of Service (DDoS) attacks represent a significant challenge for online infrastructure security. This review paper delves into the efficacy of Artificial Intelligence (AI)-based strategies and techniques in mitigating DDoS attacks. It synthesizes current research and developments in the field, emphasizing the adaptability and resilience of AI methods against the dynamic nature of these attacks. The paper categorizes various AI approaches, including machine leaming algorithms, deep learning frameworks, and heuristic methods, analyzing their strengths and limitations in real-world scenarios. Additionally, it explores the integration of AI with traditional security protocols to enhance defense mechanisms. Through a comprehensive examination of case studies and experimental results, this paper highlights the transformative impact of AI in detecting, analyzing, and neutralizing DDoS threats, thereby offering valuable insights for researchers and practitioners in cybersecurity. The review concludes with a discussion on future trends and potential research directions, underscoring the importance of continuous innovation in AI technologies to combat the evolving sophistication of DDoS attacks.