| Summary: | Software-defined networks offer a new approach that attracts the attention of most academic and industrial circles due to the features it contains. However, some loopholes make such modern networks vulnerable to many types of attacks. Among the most important types of these attacks is the Distributed Denial of Service (DDoS) attack, which in turn affects the network's performance and delays many real user requests. As one of the main features of SDN is the centralization of all the control plane in the SDN controller, it becomes a central point of attack that may compromise the whole network. Hence, in our proposed approach, we aim to mitigate the DDoS attack that maybe launched to compromise the SDN controller, flood the control plane and cripple the entire network. Many DDoS mitigation scheme have been proposed, however, determining the threshold between legitimate requests and malicious requests is still a challenging task. Our proposed approach relies on a two-phases algorithm that assigns a variable trust value for every user. This trust value is compared with schemes relying on a threshold value that changes dynamically and assists in detecting the DDoS attack. The first phase of our two-phases algorithm is Header fields extraction, and the second phase is calculating the trust value based on header fields information. Our proposed approach shows better performance than related detection schemes in terms of accuracy, detection rate, and false-positive rate. Where the accuracy of the system reaches up to 98.83% which is high compared to other traditional methods.
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