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)
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Abstract
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.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Bibliometric; Cybersecurity; Deep learning; Malware; Review |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Computing |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 15 Jan 2025 08:16 |
| Last Modified: | 15 Jan 2025 08:16 |
| URI: | http://umpir.ump.edu.my/id/eprint/43584 |
| Download Statistic: | View Download Statistics |
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