Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach

Internet of Things (IoT) networks have been integrated into industrial infrastructure schemes, positioning themselves as devices that communicate highly classified information for the most critical companies of world nations. Currently, and in order to look for alternatives to mitigate this risk, so...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Henry Vargas, Carlos Lozano-Garzon, Germán A. Montoya, Yezid Donoso
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	blockchain Industrial Internet of Things (IIoT) intrusion machine learning Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/bff565733e2b416ca631105b08eec862
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:bff565733e2b416ca631105b08eec862
record_format	dspace
spelling	oai:doaj.org-article:bff565733e2b416ca631105b08eec8622021-11-11T15:39:29ZDetection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach10.3390/electronics102126622079-9292https://doaj.org/article/bff565733e2b416ca631105b08eec8622021-10-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/21/2662https://doaj.org/toc/2079-9292Internet of Things (IoT) networks have been integrated into industrial infrastructure schemes, positioning themselves as devices that communicate highly classified information for the most critical companies of world nations. Currently, and in order to look for alternatives to mitigate this risk, solutions based on Blockchain algorithms and Machine Learning techniques have been implemented separately with the aim of mitigating potential threats in IIoT networks. In this paper, we sought to integrate the previous solutions to create an integral protection mechanism for IoT device networks, which would allow the identification of threats, activate secure information transfer mechanisms, and it would be adapted to the computational capabilities of industrial IoT. The proposed solution achieved the proposed objectives and is presented as a viable mechanism for detecting and containing intruders in an IoT network. In some cases, it overcomes traditional detection mechanisms such as an IDS.Henry VargasCarlos Lozano-GarzonGermán A. MontoyaYezid DonosoMDPI AGarticleblockchainIndustrial Internet of Things (IIoT)intrusionmachine learningElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2662, p 2662 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	blockchain Industrial Internet of Things (IIoT) intrusion machine learning Electronics TK7800-8360
spellingShingle	blockchain Industrial Internet of Things (IIoT) intrusion machine learning Electronics TK7800-8360 Henry Vargas Carlos Lozano-Garzon Germán A. Montoya Yezid Donoso Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach
description	Internet of Things (IoT) networks have been integrated into industrial infrastructure schemes, positioning themselves as devices that communicate highly classified information for the most critical companies of world nations. Currently, and in order to look for alternatives to mitigate this risk, solutions based on Blockchain algorithms and Machine Learning techniques have been implemented separately with the aim of mitigating potential threats in IIoT networks. In this paper, we sought to integrate the previous solutions to create an integral protection mechanism for IoT device networks, which would allow the identification of threats, activate secure information transfer mechanisms, and it would be adapted to the computational capabilities of industrial IoT. The proposed solution achieved the proposed objectives and is presented as a viable mechanism for detecting and containing intruders in an IoT network. In some cases, it overcomes traditional detection mechanisms such as an IDS.
format	article
author	Henry Vargas Carlos Lozano-Garzon Germán A. Montoya Yezid Donoso
author_facet	Henry Vargas Carlos Lozano-Garzon Germán A. Montoya Yezid Donoso
author_sort	Henry Vargas
title	Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach
title_short	Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach
title_full	Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach
title_fullStr	Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach
title_full_unstemmed	Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach
title_sort	detection of security attacks in industrial iot networks: a blockchain and machine learning approach
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bff565733e2b416ca631105b08eec862
work_keys_str_mv	AT henryvargas detectionofsecurityattacksinindustrialiotnetworksablockchainandmachinelearningapproach AT carloslozanogarzon detectionofsecurityattacksinindustrialiotnetworksablockchainandmachinelearningapproach AT germanamontoya detectionofsecurityattacksinindustrialiotnetworksablockchainandmachinelearningapproach AT yeziddonoso detectionofsecurityattacksinindustrialiotnetworksablockchainandmachinelearningapproach
_version_	1718434628865359872

Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach

Ejemplares similares