Detecção de Ataques DDoS em redes IoT usando Redes Neurais e Seleção de Características

• Ariel L. C. Portela UECE
• Wanderson L. Costa UECE
• Rafael L. Gomes UECE

DOI: https://doi.org/10.5753/sbrc_estendido.2021.17175

Abstract

The deployment of Internet of Things (IoT) infrastructures suffers with the occurrence of Distributed Denial of Service (DDoS) attacks. In this way, it is necessary to apply solutions to detect DDoS attacks in IoT networks, dealing with issues like scalability, adaptability and heterogeinety. Within this context, this paper presents an Fog-Cloud System for detection of DDoS in IoT networks, based on Neural Networks (NNs) and Features Selection techniques, allowing the identification of the most suitable composition of features to train the model, as well as the necessary scalability. The experiments performed, using real network traffic, suggest that the proposed system reaches 99% accuracy while reducing the volume of data exchanged and the detection time.

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