IEEE Access (Jan 2018)

Machine Learning and Deep Learning Methods for Cybersecurity

  • Yang Xin,
  • Lingshuang Kong,
  • Zhi Liu,
  • Yuling Chen,
  • Yanmiao Li,
  • Hongliang Zhu,
  • Mingcheng Gao,
  • Haixia Hou,
  • Chunhua Wang

DOI
https://doi.org/10.1109/ACCESS.2018.2836950
Journal volume & issue
Vol. 6
pp. 35365 – 35381

Abstract

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With the development of the Internet, cyber-attacks are changing rapidly and the cyber security situation is not optimistic. This survey report describes key literature surveys on machine learning (ML) and deep learning (DL) methods for network analysis of intrusion detection and provides a brief tutorial description of each ML/DL method. Papers representing each method were indexed, read, and summarized based on their temporal or thermal correlations. Because data are so important in ML/DL methods, we describe some of the commonly used network datasets used in ML/DL, discuss the challenges of using ML/DL for cybersecurity and provide suggestions for research directions.

Keywords