Application of Abnormal Network Traffic Classification in the Teaching System of Distance Political Course

Abstract

Based on the method of the abnormal network traffic classification system of the CNN network, the traffic is encrypted according to the split and capture strategy, which makes it difficult to find the most important value in the whole world. An unconventional network is proposed based on CNN. This method combines several substeps, such as image creation, image selection, sorting, and end-to-end structure, and automatic learning of indirect relations is detected from the required original input and output, and it is possible applicable globally. The ideology of the ideological and political courses and political system of these distance universities is aimed at ensuring the political direction of college students and ensuring a comprehensive understanding of socialism in order to effectively conduct higher education courses. The ideological and political courses of a certain college have different characteristics from other courses. The teaching system provides students with an independent learning environment. Students can use the courses, teaching materials, text, drawings, and video information provided by the system to deepen their understanding and application knowledge.