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Título
Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Complexity
Cita Bibliográfica
Alaiz-Moreton, H., Aveleira-Mata, J., Ondicol-Garcia, J., Muñoz-Castañeda, A. L., García, I., & Benavides, C. (2019). Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol. Complexity, 2019. https://doi.org/10.1155/2019/6516253
Editorial
Hindawi
Fecha
2019
ISSN
1076-2787
Resumen
[EN]The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continuously to the Internet. Intrusion detection systems (IDS) are used to protect IoT systems from the various anomalies and attacks at the network level. Intrusion Detection Systems (IDS) can be improved through machine learning techniques. Our work focuses on creating classification models that can feed an IDS using a dataset containing frames under attacks of an IoT system that uses the MQTT protocol. We have addressed two types of method for classifying the attacks, ensemble methods and deep learning models, more specifically recurrent networks with very satisfactory results.
Materia
Palabras clave
Peer review
SI
ID proyecto
- LE078G18
URI
DOI
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- Artículos [4877]
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