Advanced Techniques for Secure and Efficient SDN Management a Survey

Abstract

Software-Defined Networking (SDN) has revolutionized network management by decoupling the control plane from the data plane, offering dynamic, programmable, and centralized network control. However, the complexity and scale of modern networks demand advanced techniques for secure and efficient SDN management. This survey explores cutting-edge methodologies, technologies, and strategies aimed at enhancing the security and efficiency of SDN infrastructures. The survey begins by examining security challenges in SDN environments, such as controller vulnerabilities, network attacks, and data privacy concerns. It then delves into security-enhancing techniques like access control mechanisms, encryption protocols, anomaly detection, and threat intelligence integration, providing insights into how these methods mitigate risks and fortify SDN infrastructures against cyber threats. On the efficiency front, the survey explores optimization techniques for resource allocation, traffic engineering, and Quality of Service (QoS) provisioning in SDN networks. It covers topics like network slicing, load balancing algorithms, dynamic routing strategies, and bandwidth management solutions, showcasing how these approaches enhance network performance, scalability, and resource utilization. Furthermore, the survey highlights emerging trends such as Artificial Intelligence (AI) and Machine Learning (ML) applications in SDN security and management, discussing their potential to automate threat detection, optimize network operations, and adaptively respond to evolving network conditions.