Intelligent one-class classifiers for the development of an intrusion detection system: the MQTT case study

Jove, Esteban; Aveleira Mata, Jose Antonio; Alaiz Moretón, Héctor; Casteleiro-Roca, José-Luis; Marcos del Blanco, David Yeregui; Zayas-Gato, Francisco; Quintián, Héctor; Calvo-Rolle, José Luis

Use this link to cite:

http://hdl.handle.net/2183/30652

Intelligent one-class classifiers for the development of an intrusion detection system: the MQTT case study

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Jove_Esteban_2022_Intelligent_one-class_classifiers_development_intrusion_detection_system_MQTT_case_study.pdf (904.68 KB)

Identifiers

URI: http://hdl.handle.net/2183/30652

DOI: https://doi.org/10.3390/electronics11030422

Publication date

2022-01-30

Authors

Jove, Esteban

Aveleira Mata, Jose Antonio

Alaiz Moretón, Héctor

Casteleiro-Roca, José-Luis

Marcos del Blanco, David Yeregui

Zayas-Gato, Francisco

Quintián, Héctor

Calvo-Rolle, José Luis

Bibliographic citation

Jove, E.; Aveleira-Mata, J.; Alaiz-Moretón, H.; Casteleiro-Roca, J.-L.; Marcos del Blanco, D.Y.; Zayas-Gato, F.; Quintián, H.; Calvo-Rolle, J.L. Intelligent One-Class Classifiers for the Development of an Intrusion Detection System: The MQTT Case Study. Electronics 2022, 11, 422. https://doi.org/10.3390/ electronics11030422

Abstract

[Abstarct] The ever-increasing number of smart devices connected to the internet poses an unprecedented security challenge. This article presents the implementation of an Intrusion Detection System (IDS) based on the deployment of different one-class classifiers to prevent attacks over the Internet of Things (IoT) protocol Message Queuing Telemetry Transport (MQTT). The utilization of real data sets has allowed us to train the one-class algorithms, showing a remarkable performance in detecting attacks.