Feature Analysis for Machine Learning-based IoT Intrusion Detection. (arXiv:2108.12732v2 [cs.CR] UPDATED)

Internet of Things (IoT) networks have become an increasingly attractive
target of cyberattacks. Powerful Machine Learning (ML) models have recently
been adopted to implement network intrusion detection systems to protect IoT
networks. For the successful training of such ML models, selecting the right
data features is crucial, maximising the detection accuracy and computational
efficiency. This paper comprehensively analyses feature sets' importance and
predictive power for detecting network attacks. Three feature selection
algorithms: chi-square, information gain and correlation, have been utilised …

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