A Systematic Review of Defensive and Offensive Cybersecurity with Machine Learning

Imatitikua D. Aiyanyo, Hamman Samuel, Heuiseok Lim
2020 Applied Sciences  
This is a systematic review of over one hundred research papers about machine learning methods applied to defensive and offensive cybersecurity. In contrast to previous reviews, which focused on several fragments of research topics in this area, this paper systematically and comprehensively combines domain knowledge into a single review. Ultimately, this paper seeks to provide a base for researchers that wish to delve into the field of machine learning for cybersecurity. Our findings identify
more » ... e frequently used machine learning methods within supervised, unsupervised, and semi-supervised machine learning, the most useful data sets for evaluating intrusion detection methods within supervised learning, and methods from machine learning that have shown promise in tackling various threats in defensive and offensive cybersecurity.
doi:10.3390/app10175811 fatcat:xnuwg7qumbbzzmuxlsh7d33cam