Internet Abnormal Traffic Detection Based on WOA-BiLSTM-Attention

With the rise of the Internet, network application coverage is becoming more and more extensive, and a large amount of data has brought security issues to the network environment. In order to detect abnormal network traffic, this research builds a model based on the WOA using BiLSTM-Attention, and conducts empirical research using certain network traffic data as an example. The research results show that the root mean square error (RMSE) of WOA-BiLSTM-Attention is 79.1746, which is better than the traditional prediction model and is more suitable for predicting Internet traffic. Its prediction results can provide certain reference significance for abnormal traffic detection and abnormal data detection in other fields in the future.