Class Image Processing Application of XSS Intrusion Intelligent Detection for Big Data in Campus Network Construction

Abstract

In order to improve the effect of XSS intrusion intelligent detection, this paper proposes an application of big data-oriented XSS intrusion intelligent detection based on class image processing in the construction of university campus network. In this application, image like processing method is used for data acquisition, data cleaning, data sampling, feature extraction, and other data preprocessing; design a word vector quantization algorithm based on neural network to realize word vector quantization and get word vector big data; through theoretical analysis and derivation, a variety of deep neural network intelligent detection algorithms with different depths are realized; through experiments, it is found that the average recognition rate of each deep DNN for the class I big data set is about 99.44%, the variance is about 0.000002, and the standard deviation is about 0.001589; the average recognition rate of class II big data set is about 99.77%, the variance is about 0.000006, and the standard deviation is about 0.002427. The experimental results show that this method has the characteristics of high recognition rate, good stability, and excellent overall performance.