网络流量分析系统的设计与实现

Abstract

Background

As information technology develops, the amount of data transmitted over the Internet is growing rapidly. In order to better manage and analyze this massive data, network traffic analysis has become an important research area. A good network traffic analysis system can help detect network threats, optimize network performance, and identify user behavior.

Methodology

This paper introduces the design and implementation of a network traffic analysis system. The system is composed of three modules: data acquisition, data processing and data analysis. The data acquisition module collects network traffic data using a variety of methods, including packet capture and flow analysis. The data processing module performs data cleaning, filtering and feature selection. The data analysis module uses machine learning algorithms to classify traffic, identify anomalies and make predictions.

Results

The experiments show that the proposed system can effectively analyze network traffic and identify various types of traffic, including normal traffic, malicious traffic and unknown traffic. The system can also be used to detect network attacks, predict network performance and identify network bottlenecks.In conclusion, the network traffic analysis system proposed in this paper has practical significance for network management and security. It can help network administrators to better understand the network situation and make accurate decisions.