A survey of network intrusion detection systems based on deep learning approaches
Currently, most IT organizations are inclined towards a cloud computing environment because of its distributed and scalable nature. However, its flexible and open architecture is receiving lots of attention from potential intruders for cyber threats. Here, Intrusion Detection System (IDS) plays a si...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)
2023-04-01
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| Series: | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
| Subjects: | |
| Online Access: | https://ntv.ifmo.ru/file/article/21912.pdf |
| _version_ | 1797845437165600768 |
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| author | Duaa Wahab Al-Safaar Wathiq Laftah Al-Yaseen |
| author_facet | Duaa Wahab Al-Safaar Wathiq Laftah Al-Yaseen |
| author_sort | Duaa Wahab Al-Safaar |
| collection | DOAJ |
| description | Currently, most IT organizations are inclined towards a cloud computing environment because of its distributed and scalable nature. However, its flexible and open architecture is receiving lots of attention from potential intruders for cyber threats. Here, Intrusion Detection System (IDS) plays a significant role in monitoring malicious activities in
cloud-based systems. The state of the art of this paper is to systematically review the existing methods for detecting intrusions based upon various techniques, such as data mining, machine learning, and deep learning methods. Recently, deep learning techniques have gained momentum in the intrusion detection domain, and several IDS approaches are provided in the literature using various deep learning techniques to deal with privacy concerns and security threats. For this purpose, the article focuses on the deep IDS approaches and investigates how deep learning networks are employed by different approaches in various steps of the intrusion detection process to achieve better results. Then, it provided a
comparison of the deep learning approaches and the shallow machine learning methods. Also, it describes datasets that are most used in IDS. |
| first_indexed | 2024-04-09T17:39:00Z |
| format | Article |
| id | doaj.art-eba83def10464044bd3d43beb66e6c01 |
| institution | Directory Open Access Journal |
| issn | 2226-1494 2500-0373 |
| language | English |
| last_indexed | 2024-04-09T17:39:00Z |
| publishDate | 2023-04-01 |
| publisher | Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University) |
| record_format | Article |
| series | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
| spelling | doaj.art-eba83def10464044bd3d43beb66e6c012023-04-17T09:54:19ZengSaint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki2226-14942500-03732023-04-0123235236310.17586/2226-1494-2023-23-2-352-363A survey of network intrusion detection systems based on deep learning approachesDuaa Wahab Al-Safaar0https://orcid.org/0000-0002-2995-2342Wathiq Laftah Al-Yaseen1https://orcid.org/0000-0002-2155-2993Magister, Lecturer, University of Babylon, Babylon, 51002, IraqAssociate Professor, D.Sc., Head of Computer Center, Technical Institute of Karbala, Karbala, 56001, Iraq; Head of Computer Center, Al-Furat Al-Awsat Technical University, Karbala, 56001, Iraq, sc 57188754655Currently, most IT organizations are inclined towards a cloud computing environment because of its distributed and scalable nature. However, its flexible and open architecture is receiving lots of attention from potential intruders for cyber threats. Here, Intrusion Detection System (IDS) plays a significant role in monitoring malicious activities in cloud-based systems. The state of the art of this paper is to systematically review the existing methods for detecting intrusions based upon various techniques, such as data mining, machine learning, and deep learning methods. Recently, deep learning techniques have gained momentum in the intrusion detection domain, and several IDS approaches are provided in the literature using various deep learning techniques to deal with privacy concerns and security threats. For this purpose, the article focuses on the deep IDS approaches and investigates how deep learning networks are employed by different approaches in various steps of the intrusion detection process to achieve better results. Then, it provided a comparison of the deep learning approaches and the shallow machine learning methods. Also, it describes datasets that are most used in IDS.https://ntv.ifmo.ru/file/article/21912.pdfcloud computingintrusion detection systemmachine learningdeep learning |
| spellingShingle | Duaa Wahab Al-Safaar Wathiq Laftah Al-Yaseen A survey of network intrusion detection systems based on deep learning approaches Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki cloud computing intrusion detection system machine learning deep learning |
| title | A survey of network intrusion detection systems based on deep learning approaches |
| title_full | A survey of network intrusion detection systems based on deep learning approaches |
| title_fullStr | A survey of network intrusion detection systems based on deep learning approaches |
| title_full_unstemmed | A survey of network intrusion detection systems based on deep learning approaches |
| title_short | A survey of network intrusion detection systems based on deep learning approaches |
| title_sort | survey of network intrusion detection systems based on deep learning approaches |
| topic | cloud computing intrusion detection system machine learning deep learning |
| url | https://ntv.ifmo.ru/file/article/21912.pdf |
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