Research on Anomaly Detection Algorithm of Network Traffic Based on Deep Learning
Deep learning technology is widely used in network traffic anomaly detection,which uses deep neural network to mine the potential correlation between data,so as to effectively detect attacks and intrusions that do not meet the network behavior.A network traffic intrusion detection algorithm NECP is proposed to improve the identification of unbalanced network traffic in order to detect unbalanced network traffic.The experiment proves that NECP can maintain the computational efficiency,significantly improve the anomaly detection accuracy of network traffic,so as to provide a novel and effective solution for ensuring network security,and promote the further development of this field.
Deep learningNetwork trafficAnomaly detectionNetwork security
万方数据
维普
