Abstract

In this review, key literature reviews on network analysis and intrusion detection using machine learning (ML) and deep learning (DL) approaches are explained. It also provides a brief lesson description for each ML/DL procedure. This paper covers the datasets used in machine learning techniques, which are the main instruments for evaluating network traffic and detecting irregularities. Data holds a key role in ML/DL approaches. We also go into further detail about the problems with using ML/DL to cybersecurity and make suggestions for future research.

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