MADS Based on DL Techniques on the Internet of Things (IoT): Survey

Technologically speaking, humanity lives in an age of evolution, prosperity, and great development, as a new generation of the Internet has emerged; it is the Internet of Things (IoT) which controls all aspects of lives, from the different devices of the home to the large industries. Despite the tre...

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Autores principales:	Hussah Talal, Rachid Zagrouba
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	anomaly detection system machine learning techniques Deep Learning (DL) techniques IoT devices IoT networks malware detection Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/1f4c992e1e8f41dfb4fb154bed32615f
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id	oai:doaj.org-article:1f4c992e1e8f41dfb4fb154bed32615f
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spelling	oai:doaj.org-article:1f4c992e1e8f41dfb4fb154bed32615f2021-11-11T15:37:32ZMADS Based on DL Techniques on the Internet of Things (IoT): Survey10.3390/electronics102125982079-9292https://doaj.org/article/1f4c992e1e8f41dfb4fb154bed32615f2021-10-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/21/2598https://doaj.org/toc/2079-9292Technologically speaking, humanity lives in an age of evolution, prosperity, and great development, as a new generation of the Internet has emerged; it is the Internet of Things (IoT) which controls all aspects of lives, from the different devices of the home to the large industries. Despite the tremendous benefits offered by IoT, still there are some challenges regarding privacy and information security. The traditional techniques used in Malware Anomaly Detection Systems (MADS) could not give us as robust protection as we need in IoT environments. Therefore, it needed to be replaced with Deep Learning (DL) techniques to improve the MADS and provide the intelligence solutions to protect against malware, attacks, and intrusions, in order to preserve the privacy of users and increase their confidence in and dependence on IoT systems. This research presents a comprehensive study on security solutions in IoT applications, Intrusion Detection Systems (IDS), Malware Detection Systems (MDS), and the role of artificial intelligent (AI) in improving security in IoT.Hussah TalalRachid ZagroubaMDPI AGarticleanomaly detection systemmachine learning techniquesDeep Learning (DL) techniquesIoT devicesIoT networksmalware detectionElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2598, p 2598 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	anomaly detection system machine learning techniques Deep Learning (DL) techniques IoT devices IoT networks malware detection Electronics TK7800-8360
spellingShingle	anomaly detection system machine learning techniques Deep Learning (DL) techniques IoT devices IoT networks malware detection Electronics TK7800-8360 Hussah Talal Rachid Zagrouba MADS Based on DL Techniques on the Internet of Things (IoT): Survey
description	Technologically speaking, humanity lives in an age of evolution, prosperity, and great development, as a new generation of the Internet has emerged; it is the Internet of Things (IoT) which controls all aspects of lives, from the different devices of the home to the large industries. Despite the tremendous benefits offered by IoT, still there are some challenges regarding privacy and information security. The traditional techniques used in Malware Anomaly Detection Systems (MADS) could not give us as robust protection as we need in IoT environments. Therefore, it needed to be replaced with Deep Learning (DL) techniques to improve the MADS and provide the intelligence solutions to protect against malware, attacks, and intrusions, in order to preserve the privacy of users and increase their confidence in and dependence on IoT systems. This research presents a comprehensive study on security solutions in IoT applications, Intrusion Detection Systems (IDS), Malware Detection Systems (MDS), and the role of artificial intelligent (AI) in improving security in IoT.
format	article
author	Hussah Talal Rachid Zagrouba
author_facet	Hussah Talal Rachid Zagrouba
author_sort	Hussah Talal
title	MADS Based on DL Techniques on the Internet of Things (IoT): Survey
title_short	MADS Based on DL Techniques on the Internet of Things (IoT): Survey
title_full	MADS Based on DL Techniques on the Internet of Things (IoT): Survey
title_fullStr	MADS Based on DL Techniques on the Internet of Things (IoT): Survey
title_full_unstemmed	MADS Based on DL Techniques on the Internet of Things (IoT): Survey
title_sort	mads based on dl techniques on the internet of things (iot): survey
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1f4c992e1e8f41dfb4fb154bed32615f
work_keys_str_mv	AT hussahtalal madsbasedondltechniquesontheinternetofthingsiotsurvey AT rachidzagrouba madsbasedondltechniquesontheinternetofthingsiotsurvey
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MADS Based on DL Techniques on the Internet of Things (IoT): Survey

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