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Software-defined networking (SDN) is a unique network architecture isolating the network control plane from the data plane, offering programmable elastic features that allow network operators to monitor their networks and efficiently manage them. However, the new technology is security deficient. A DDoS attack is one of the common attacks that threaten SDN controllers, leading to the degradation or even collapse of the entire SDN network. Entropy-based approaches and their variants are considered the most efficient approaches to detecting DDoS attacks on SDN controllers. Therefore, this work analyzes the feasibility and impacts of an entropy-based DDoS attack detection approach for detecting low-rate and high-rate DDoS attacks against the controller, measured in terms of detection rate (DR) and false-positive rate (FPR), triggered by a single or multiple host attacks targeting a single or multiple victims. Eight simulation scenarios, representing low and high DDoS attack traffic rates on the controller, have been used to evaluate an entropy-based DDoS attack detection approach. The experimental results reveal that the entropy-based approach enhances the average DR for detecting high-rate DDoS attack traffic compared with low-rate DDoS attack traffic by 6.25%, 20.26%, 6.74%, and 8.81%. In addition, it reduces the average FPRs for detecting a high DDoS attack traffic rate compared with a low DDoS attack traffic rate by 67.68%, 77.54%, 66.94%, and 64.81.

The increasing incidence of distributed denial-of-service (DDoS) attacks has made software-defined networking (SDN) more vulnerable to the depletion of controller resources. DDoS attacks prevent the SDN controller from processing all incoming data efficiently, potentially disrupting a network or denying legitimate users access to network services. Thus, the protection of the SDN controller is crucial, especially from the ones that exploit the SDN characteristics. In this paper, the authors propose an efficient detection approach for low- and high-rate DDoS attacks on the controller with a high detection rate and a low false positive rate by adapting a dynamic threshold algorithm rather than a static one and proposing a new rule-based detection mechanism. In addition, the proposed approach was evaluated using eight simulation scenarios representing all potential attacks against the SDN controller in terms of attack traffic rates (low or high), sources (either single or multiple hosts), and targets (single or multiple victims). The experiment results show that the proposed approach is more effective than the existing approaches based on attack detection and false positive rates.