网络异常检测中机器学习的应用

Research on Anomaly Detection and Defense of Machine Learning in Network Security

异常检测在网络安全中是一项至关重要的任务,能够帮助安全专业人员及时发现并应对各种潜在威胁。文章首先介绍了异常检测的概念、分类以及传统的异常检测方法。然后,重点讨论了机器学习在网络安全中的广泛应用,涵盖异常检测、入侵检测和恶意软件检测等方面。最后,本文讨论了机器学习模型的部署和防御对抗性攻击的方法。

Anomaly detection is a crucial task in network security,which can help security professionals find and respond to various potential threats in a timely manner.This article will first introduce the concept and classification of anomaly detection,and then explore traditional anomaly detection methods,including rule-based,statistical,and machine learning.Then,it focuses on the extensive application of machine learning in network security,including anomaly detection,intrusion detection and malware detection.Finally,the deployment of machine learning models and methods to defend against adversarial attacks are discussed.