中圖分類號：TP309文獻標識碼：ADOI:10.19358/j.issn.2097-1788.2024.12.001
引用格式：張茜，王曉菲，王亞洲，等. 基于機器學習的網(wǎng)絡入侵檢測技術綜述［J］.網(wǎng)絡安全與數(shù)據(jù)治理，2024，43（12）：1-9，18.

Overview of network intrusion detection technology based on machine learning

Abstract： The development of emerging technologies has promoted the wide application of intelligent methods such as machine learning in the field of network intrusion detection, and effectively improved the efficiency and accuracy of intrusion detection. However, the field of network intrusion detection based on machine learning still faces challenges such as difficulty in processing large-scale network data, imbalance of data samples, difficulty in effectively detecting unknown threats, and poor generalization ability of models. This paper aims to summarize the network intrusion detection technology based on machine learning, compare and analyze the advantages and limitations of the current mainstream methods, and summarize and discuss the current challenges and future prospects in this field, so as to provide reference for people in this field to understand the latest research trends.

Key words : machine learning; intrusion detection; intelligence