Aiming at the problem of variable rate DDoS attack detection,a variable rate DDoS attack detection method based on dynamic threshold is proposed.According to the characteristics of DDoS attack traffic,dynamic threshold is generated and the freezing mechanism is applied to prevent the attack traffic from polluting the dynamic threshold parameters.At the same time,combined with the characteristics of the network flow,the BiLSTM model is used to bidirectionally learn the time-segmented network traffic,extract more features,and identify variable-rate DDoS attacks.Experimented on the NSL-KDD dataset,the recall rate reaches 98%and the precision reaches 95%.Experiments show that compared with the fixed threshold DDoS attack detection method and the traditional dynamic threshold DDoS attack detection method,the detection accuracy of this method is increased,and the detection ability of DDoS attack has been significantly improved.
维普
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