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Anais do XXI Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais (SBSeg 2021)
The Internet of Things (IoT) systems have limited resources, making it difficult to implement some security mechanisms. It is important to detect attacks against these environments and identify their type. However, existing multi-class detection approaches present difficulties related to false positives and detection of less common attacks. Thus, this work proposes an approach with a two-stage analysis architecture based on One-Vs-All (OVA) and Artificial Neural Networks (ANN) to detect anddoi:10.5753/sbseg.2021.17308 fatcat:hcvcu5n3g5a4nbqbzbv73efc64