Research on Network Attack Vulnerability Prediction Based on Neural Network Model

The identification and prediction of simulated network attacks using artificial neural networks have achieved the prediction of simulated network attacks and transformed them into clear information for security management personnel, striving for defense time and preparation for counterattacks. This article is based on Python and utilizes artificial neural network models and ANN algorithms to preprocess data, adjust model parameters, perform fitting and recognition, present text, and complete feature extraction, data cleaning, and model training of simulated network attack data. The aim is to train ANN artificial neural network models to identify and predict simulated network attack data.