Learning Cyber ​​Security and Machine Engineering at the University

  • Karuniawan R
  • Santoso S
  • Fikri M
  • et al.
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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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CITATION STYLE

APA

Karuniawan, R. R., Santoso, S., Fikri, M. A., & Argadilah, M. (2022). Learning Cyber ​​Security and Machine Engineering at the University. Blockchain Frontier Technology, 3(1), 89–94. https://doi.org/10.34306/bfront.v3i1.242

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