Research on Network Intrusion Detection Method Based on Machine Learning

After years of development, the Internet has penetrated into all areas of society, and various network intrusions occur almost every day. In order to enhance the security of the network, intrusion detection technology has received more and more attention. Network intrusion detection is a branch of computer security. Its goal is to automatically and effectively detect intrusion traffic in the network and provide timely warnings. Network intrusion detection technology has become an important means to resist network intrusion in recent years, and network intrusion detection systems of various scales have been applied in the network. Due to the diversity of intrusion methods, traditional digital authentication and firewalls and other network security measures are difficult to meet the needs of network intrusion detection. The machine learning boom has gradually emerged, and machine learning methods have begun to be applied to the field of intrusion detection, which has become a research hotspot in this field. This article discusses machine learning methods, discusses adding machine learning algorithms to the network intrusion detection link to achieve effective detection of network intrusion traffic, so as to obtain a good network intrusion detection effect.