Abstract: Aiming at the DDoS attack threat brought by massive access devices in the 5G Internet of Things (IoT) environment, considering the Software Defined Network (SDN) for the applicability of 5G IoT, a DDoS attack detection scheme using Long Short-Term Memory (LSTM) network in SDN environment is proposed, in order to improve the accuracy of DDoS attack detection. Based on the idea of divide-and-conquer algorithm, a lightweight distributed edge computing architecture, called Only Care Myself (OCM), is proposed. A Bi-LSTM based lightweight neural network is deployed on idle edge nodes in IoT to complete the detection task, which increases the flexibility of detection while maintaining the accuracy. The performance index of the proposed scheme was evaluated on the ISCX2012 dataset, and the feasibility of the proposed scheme is verified. Experimental results show that the proposed scheme can accurately detect DDoS attacks and effectively mitigate DDoS attacks.

Key words: software defined network(SDN), 5G, distributed denial of service(DDoS), Internet of Things (IoT), network security