Volume 10, Number 6

Ensemble of Probabilistic Learning Networks for IoT Edge Intrusion Detection

  Authors

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