Tony Jan and A.S.M Sajeev
Melbourne Institute of Technology, Australia
ABSTRACT
This paper proposes an intelligent and compact machine learning model for IoT intrusion detection using
an ensemble of semi-parametric models with Ada boost. The proposed model provides an adequate realtime
intrusion detection at an affordable computational complexity suitable for the IoT edge networks. The
proposed model is evaluated against other comparable models using the benchmark data on IoT-IDS and
shows comparable performance with reduced computations as required.
KEYWORDS
adaboosted ensemble learning, IoT edge security, machine learning for IoT.
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