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Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering

Annals of Computer Science and Information Systems, Volume 33

Application of Machine Learning in Malicious IoT Classification and Detection on Fog-IoT Architecture

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DOI: http://dx.doi.org/10.15439/2022R39

Citation: Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering, Vu Dinh Khoa, Shivani Agarwal, Gloria Jeanette Rincon Aponte, Nguyen Thi Hong Nga, Vijender Kumar Solanki, Ewa Ziemba (eds). ACSIS, Vol. 33, pages 299–303 ()

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Abstract. Due to the limitations in self-protection and information processing capabilities at IoT (Internet of Things) nodes, these nodes are susceptible to attacks, turning them into malicious nodes that cause damage or danger to the system. Early detection of these threats is essential to make timely recommendations and limit severe consequences for individuals and organizations. The study proposes applying a machine learning model to detect malicious traffic and IoT devices, which can be deployed and applied on the Fog IoT platform. This solution helps detect and early warn threats from IoT data before they are sent to the cloud. The model is evaluated on the IoT-23 dataset and gives good results.

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