Abstract
Software defined network (SDN) is an important part of the next generation computer network. The controller enables SDN to provide flexible data processing and programmable functions, which is the core of SDN. Once the controller is paralyzed, the whole network will be disrupted. DDoS attack targeting the controller will pose a great threat to SDN. However, most of the existing DDoS attack detection schemes only focus on the temporal or content feature of network data, it is easy to fail to detect attack or produce misjudgment. In this paper, we use the temporal and spatial feature of network data to detect DDoS attack on SDN Controller. Furthermore, flow table is used to defend against DDoS attack. We used the DARPA data set to perform experiments, and compared the performance with other scheme. The results show that our scheme can accurately detect DDoS attack and defend against it efficiently.KeywordsSDNDDoS attackCNN-LSTMSpatiotemporal featureNetwork defense mechanisms
Published Version
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