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The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware

Deep learning is a machine learning technology that allows computational models to learn via experience, mimicking human cognitive processes. This method is critical in the development of identifying certain objects, and provides the computational intelligence required to identify multiple objects a...

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Main Authors: Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Mohd Zamri, Osman, Alanda, Alde, Erianda, Aldo, Shahreen, Kasim, Mohd Faizal, Ab Razak
Format: Article
Language:English
Published: Politeknik Negeri Padang 2024
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/43584/1/The%20Rise%20of%20Deep%20Learning%20in%20Cyber%20Security%20Bibliometric%20Analysis.pdf
http://umpir.ump.edu.my/id/eprint/43584/
http://dx.doi.org/10.62527/joiv.8.3.1535
http://dx.doi.org/10.62527/joiv.8.3.1535
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spelling my.ump.umpir.435842025-01-15T08:16:23Z http://umpir.ump.edu.my/id/eprint/43584/ The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware Nur Khairani, Kamarudin Ahmad Firdaus, Zainal Abidin Mohd Zamri, Osman Alanda, Alde Erianda, Aldo Shahreen, Kasim Mohd Faizal, Ab Razak QA75 Electronic computers. Computer science Deep learning is a machine learning technology that allows computational models to learn via experience, mimicking human cognitive processes. This method is critical in the development of identifying certain objects, and provides the computational intelligence required to identify multiple objects and distinguish it between object A or Object B. On the other hand, malware is defined as malicious software that seeks to harm or disrupt computers and systems. Its main categories include viruses, worms, Trojan horses, spyware, adware, and ransomware. Hence, many deep learning researchers apply deep learning in their malware studies. However, few articles still investigate deep learning and malware in a bibliometric approach (productivity, research area, institutions, authors, impact journals, and keyword analysis). Hence, this paper reports bibliometric analysis used to discover current and future trends and gain new insights into the relationship between deep learning and malware. This paper’s discoveries include: Deployment of deep learning to detect domain generation algorithm (DGA) attacks; Deployment of deep learning to detect malware in Internet of Things (IoT); The rise of adversarial learning and adversarial attack using deep learning; The emergence of Android malware in deep learning; The deployment of transfer learning in malware research; and active authors on deep learning and malware research, including Soman KP, Vinayakumar R, and Zhang Y. Politeknik Negeri Padang 2024 Article PeerReviewed pdf en cc_by_sa_4 http://umpir.ump.edu.my/id/eprint/43584/1/The%20Rise%20of%20Deep%20Learning%20in%20Cyber%20Security%20Bibliometric%20Analysis.pdf Nur Khairani, Kamarudin and Ahmad Firdaus, Zainal Abidin and Mohd Zamri, Osman and Alanda, Alde and Erianda, Aldo and Shahreen, Kasim and Mohd Faizal, Ab Razak (2024) The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware. International Journal on Informatics Visualization, 8 (3). 1398 -1435. ISSN 2549-9904. (Published) http://dx.doi.org/10.62527/joiv.8.3.1535 http://dx.doi.org/10.62527/joiv.8.3.1535
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Nur Khairani, Kamarudin
Ahmad Firdaus, Zainal Abidin
Mohd Zamri, Osman
Alanda, Alde
Erianda, Aldo
Shahreen, Kasim
Mohd Faizal, Ab Razak
The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware
description Deep learning is a machine learning technology that allows computational models to learn via experience, mimicking human cognitive processes. This method is critical in the development of identifying certain objects, and provides the computational intelligence required to identify multiple objects and distinguish it between object A or Object B. On the other hand, malware is defined as malicious software that seeks to harm or disrupt computers and systems. Its main categories include viruses, worms, Trojan horses, spyware, adware, and ransomware. Hence, many deep learning researchers apply deep learning in their malware studies. However, few articles still investigate deep learning and malware in a bibliometric approach (productivity, research area, institutions, authors, impact journals, and keyword analysis). Hence, this paper reports bibliometric analysis used to discover current and future trends and gain new insights into the relationship between deep learning and malware. This paper’s discoveries include: Deployment of deep learning to detect domain generation algorithm (DGA) attacks; Deployment of deep learning to detect malware in Internet of Things (IoT); The rise of adversarial learning and adversarial attack using deep learning; The emergence of Android malware in deep learning; The deployment of transfer learning in malware research; and active authors on deep learning and malware research, including Soman KP, Vinayakumar R, and Zhang Y.
format Article
author Nur Khairani, Kamarudin
Ahmad Firdaus, Zainal Abidin
Mohd Zamri, Osman
Alanda, Alde
Erianda, Aldo
Shahreen, Kasim
Mohd Faizal, Ab Razak
author_facet Nur Khairani, Kamarudin
Ahmad Firdaus, Zainal Abidin
Mohd Zamri, Osman
Alanda, Alde
Erianda, Aldo
Shahreen, Kasim
Mohd Faizal, Ab Razak
author_sort Nur Khairani, Kamarudin
title The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware
title_short The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware
title_full The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware
title_fullStr The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware
title_full_unstemmed The rise of deep learning in cyber security: Bibliometric analysis of deep learning and malware
title_sort rise of deep learning in cyber security: bibliometric analysis of deep learning and malware
publisher Politeknik Negeri Padang
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/43584/1/The%20Rise%20of%20Deep%20Learning%20in%20Cyber%20Security%20Bibliometric%20Analysis.pdf
http://umpir.ump.edu.my/id/eprint/43584/
http://dx.doi.org/10.62527/joiv.8.3.1535
http://dx.doi.org/10.62527/joiv.8.3.1535
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score 13.235318

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