Abnormal Traffic Detection Method in SDN Based on Deep Learning
Aiming at the problems that traditional anomaly detection methods are complicated in algorithm,high in calcula-tion cost and generate extra traffic when deployed in SDN network,a lightweight anomaly traffic detection method based on deep learning is proposed.By analyzing the importance of traffic data features,detection data is constructed,correlation information of detection data is extracted by using circular neural network,and anomaly traffic is detected by using lightweight classification func-tion.The experimental results show that the proposed method has obvious advantages over the traditional detection methods in terms of accuracy,recall and detection time,and has the characteristics of simple deployment and little impact on the performance of SDN controller.
deep learningsoftware-defined networkabnormal detectionabnormal relief
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