Ensemble of probabilistic learning networks for IOT edge intrusion detection

Tony Jan, A. S.M. Sajeev

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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 real- time 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.

Original languageEnglish
Pages (from-to)135-147
Number of pages13
JournalInternational Journal of Computer Networks and Communications
Issue number6
Publication statusPublished - 2018
Externally publishedYes


  • Adaboosted ensemble learning
  • IoT edge security
  • Machine learning for IoT


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