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What is Machine Learning for Network Anomaly Detection about?

This document presents a comprehensive survey on the use of machine learning (ML) techniques for network anomaly detection, addressing challenges in both traditional and next-generation networks. It reviews various ML models, including supervised, unsupervised, semi-supervised, and reinforcement learning, and discusses their applications and advantages in detecting anomalies across different network contexts. The paper aims to provide a detailed comparison of existing solutions and highlight the importance

Author

Dayanand K s

Language

EN