Denial-of-service attack

World Wide Web

Computer security

The Internet

Communications protocol

Computer science

Protocol (science)

Distributed computing

MQTT

Computer network

Alternative medicine

Internet of Things

Artificial intelligence

Intrusion detection system

Medicine

Machine learning

Pathology

Complexity

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.

Multiclass Classification Procedure for Detecting Attacks on MQTT‐IoT Protocol