Intelligent Techniques for Detecting Network Attacks: Review and Research Directions

The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. Network attacks refer to all types of unauthorized access to a network including any attempts to damage and disrupt the network, often leading...

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Autores principales:	Malak Aljabri, Sumayh S. Aljameel, Rami Mustafa A. Mohammad, Sultan H. Almotiri, Samiha Mirza, Fatima M. Anis, Menna Aboulnour, Dorieh M. Alomari, Dina H. Alhamed, Hanan S. Altamimi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	network security network attacks attack detection machine learning deep learning Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/83753ac8cfef40259c8bd8b94378d7e5
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spelling	oai:doaj.org-article:83753ac8cfef40259c8bd8b94378d7e52021-11-11T19:05:18ZIntelligent Techniques for Detecting Network Attacks: Review and Research Directions10.3390/s212170701424-8220https://doaj.org/article/83753ac8cfef40259c8bd8b94378d7e52021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7070https://doaj.org/toc/1424-8220The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. Network attacks refer to all types of unauthorized access to a network including any attempts to damage and disrupt the network, often leading to serious consequences. Network attack detection is an active area of research in the community of cybersecurity. In the literature, there are various descriptions of network attack detection systems involving various intelligent-based techniques including machine learning (ML) and deep learning (DL) models. However, although such techniques have proved useful within specific domains, no technique has proved useful in mitigating all kinds of network attacks. This is because some intelligent-based approaches lack essential capabilities that render them reliable systems that are able to confront different types of network attacks. This was the main motivation behind this research, which evaluates contemporary intelligent-based research directions to address the gap that still exists in the field. The main components of any intelligent-based system are the training datasets, the algorithms, and the evaluation metrics; these were the main benchmark criteria used to assess the intelligent-based systems included in this research article. This research provides a rich source of references for scholars seeking to determine their scope of research in this field. Furthermore, although the paper does present a set of suggestions about future inductive directions, it leaves the reader free to derive additional insights about how to develop intelligent-based systems to counter current and future network attacks.Malak AljabriSumayh S. AljameelRami Mustafa A. MohammadSultan H. AlmotiriSamiha MirzaFatima M. AnisMenna AboulnourDorieh M. AlomariDina H. AlhamedHanan S. AltamimiMDPI AGarticlenetwork securitynetwork attacksattack detectionmachine learningdeep learningChemical technologyTP1-1185ENSensors, Vol 21, Iss 7070, p 7070 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	network security network attacks attack detection machine learning deep learning Chemical technology TP1-1185
spellingShingle	network security network attacks attack detection machine learning deep learning Chemical technology TP1-1185 Malak Aljabri Sumayh S. Aljameel Rami Mustafa A. Mohammad Sultan H. Almotiri Samiha Mirza Fatima M. Anis Menna Aboulnour Dorieh M. Alomari Dina H. Alhamed Hanan S. Altamimi Intelligent Techniques for Detecting Network Attacks: Review and Research Directions
description	The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. Network attacks refer to all types of unauthorized access to a network including any attempts to damage and disrupt the network, often leading to serious consequences. Network attack detection is an active area of research in the community of cybersecurity. In the literature, there are various descriptions of network attack detection systems involving various intelligent-based techniques including machine learning (ML) and deep learning (DL) models. However, although such techniques have proved useful within specific domains, no technique has proved useful in mitigating all kinds of network attacks. This is because some intelligent-based approaches lack essential capabilities that render them reliable systems that are able to confront different types of network attacks. This was the main motivation behind this research, which evaluates contemporary intelligent-based research directions to address the gap that still exists in the field. The main components of any intelligent-based system are the training datasets, the algorithms, and the evaluation metrics; these were the main benchmark criteria used to assess the intelligent-based systems included in this research article. This research provides a rich source of references for scholars seeking to determine their scope of research in this field. Furthermore, although the paper does present a set of suggestions about future inductive directions, it leaves the reader free to derive additional insights about how to develop intelligent-based systems to counter current and future network attacks.
format	article
author	Malak Aljabri Sumayh S. Aljameel Rami Mustafa A. Mohammad Sultan H. Almotiri Samiha Mirza Fatima M. Anis Menna Aboulnour Dorieh M. Alomari Dina H. Alhamed Hanan S. Altamimi
author_facet	Malak Aljabri Sumayh S. Aljameel Rami Mustafa A. Mohammad Sultan H. Almotiri Samiha Mirza Fatima M. Anis Menna Aboulnour Dorieh M. Alomari Dina H. Alhamed Hanan S. Altamimi
author_sort	Malak Aljabri
title	Intelligent Techniques for Detecting Network Attacks: Review and Research Directions
title_short	Intelligent Techniques for Detecting Network Attacks: Review and Research Directions
title_full	Intelligent Techniques for Detecting Network Attacks: Review and Research Directions
title_fullStr	Intelligent Techniques for Detecting Network Attacks: Review and Research Directions
title_full_unstemmed	Intelligent Techniques for Detecting Network Attacks: Review and Research Directions
title_sort	intelligent techniques for detecting network attacks: review and research directions
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/83753ac8cfef40259c8bd8b94378d7e5
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_version_	1718431656370503680

Intelligent Techniques for Detecting Network Attacks: Review and Research Directions

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