Recent Advances in DDoS Attacks for SDN Controller: A Review

Abstract

The Software-Defined Networks (SDN) a cutting-edge network architecture, separates the data and control layers, enhancing the ability to recognize and respond to security risks. Despite its impressive design, this architecture is nonetheless susceptible to several security risks, most notably distributed-denial of service (DDoS) attacks. Because DDoS attacks occur more often, therefore SDN is susceptible to resource depletion in their controllers. These attacks hinder the SDN controller's ability to process incoming data effectively, resulting in network outages and denying authorized users access to network services. In this paper, we provide a thorough survey of state-of-the art solutions addressing both DDoS attacks in SDNs. Our study shows that the most popular solutions for detecting DDoS assaults in SDNs are those based on information theory and machine learning. We also go through each technique's advantages and disadvantages. We also look at the difficulties and gaps in the research around DDoS detection in SDNs. Through our comprehensive review, discussion, and analysis, we aim to enhance our understanding of DDoS detection within the context of SDNs.