Advancing Cybersecurity Through Machine Learning: A Scientometric Analysis of Global Research Trends and Influential Contributions
Implementing machine learning is imperative for enhancing advanced cybersecurity practices globally. The current cybersecurity landscape needs further investigation into the potential impasse. This scientometric study aims to comprehensively analyse the study patterns and key contributions at the ne...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Journal of Cybersecurity and Privacy |
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| Online Access: | https://www.mdpi.com/2624-800X/5/2/12 |
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| author | Kamran Razzaq Mahmood Shah |
| author_facet | Kamran Razzaq Mahmood Shah |
| author_sort | Kamran Razzaq |
| collection | DOAJ |
| description | Implementing machine learning is imperative for enhancing advanced cybersecurity practices globally. The current cybersecurity landscape needs further investigation into the potential impasse. This scientometric study aims to comprehensively analyse the study patterns and key contributions at the nexus of cybersecurity and machine learning. The analysis examines publication trends, citation analysis, and intensive research networks to discover key authors, significant organisations, major countries, and emerging research areas. The search was conducted on the Scopus database, and 3712 final documents were selected after a thorough screening from January 2016 to January 2025. The VOSviewer tool was used to map citation networks and visualise co-authorship networks, enabling the discovery of research patterns, top contributors, and hot topics in the domain. The findings uncovered the substantial growth in publications bridging cybersecurity with machine learning and deep learning, involving 2865 authors across 160 institutions and 114 countries. Saudi Arabia emerged as a top contributing nation with flaunting high productivity. <i>IEEE</i> and <i>Sensors</i> are the key publication sources instrumental in producing interdisciplinary research. Iqbal H. Sarker and N. Moustafa are notable authors, with 17 and 16 publications each. This study emphasises the significance of global partnerships and multidisciplinary research in enhancing cybersecurity posture and identifying key research areas for future studies. This study further highlights its importance by guiding policymakers and practitioners to develop advanced machine learning-based cybersecurity strategies. |
| format | Article |
| id | doaj-art-8a789965552c461fa00d0ca40933ae22 |
| institution | Kabale University |
| issn | 2624-800X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Cybersecurity and Privacy |
| spelling | doaj-art-8a789965552c461fa00d0ca40933ae222025-08-20T03:27:26ZengMDPI AGJournal of Cybersecurity and Privacy2624-800X2025-03-01521210.3390/jcp5020012Advancing Cybersecurity Through Machine Learning: A Scientometric Analysis of Global Research Trends and Influential ContributionsKamran Razzaq0Mahmood Shah1Department of Marketing Operations and Systems, Newcastle Business School, The University of Northumbria Newcastle, Newcastle upon Tyne NE1 8ST, UKDepartment of Marketing Operations and Systems, Newcastle Business School, The University of Northumbria Newcastle, Newcastle upon Tyne NE1 8ST, UKImplementing machine learning is imperative for enhancing advanced cybersecurity practices globally. The current cybersecurity landscape needs further investigation into the potential impasse. This scientometric study aims to comprehensively analyse the study patterns and key contributions at the nexus of cybersecurity and machine learning. The analysis examines publication trends, citation analysis, and intensive research networks to discover key authors, significant organisations, major countries, and emerging research areas. The search was conducted on the Scopus database, and 3712 final documents were selected after a thorough screening from January 2016 to January 2025. The VOSviewer tool was used to map citation networks and visualise co-authorship networks, enabling the discovery of research patterns, top contributors, and hot topics in the domain. The findings uncovered the substantial growth in publications bridging cybersecurity with machine learning and deep learning, involving 2865 authors across 160 institutions and 114 countries. Saudi Arabia emerged as a top contributing nation with flaunting high productivity. <i>IEEE</i> and <i>Sensors</i> are the key publication sources instrumental in producing interdisciplinary research. Iqbal H. Sarker and N. Moustafa are notable authors, with 17 and 16 publications each. This study emphasises the significance of global partnerships and multidisciplinary research in enhancing cybersecurity posture and identifying key research areas for future studies. This study further highlights its importance by guiding policymakers and practitioners to develop advanced machine learning-based cybersecurity strategies.https://www.mdpi.com/2624-800X/5/2/12cybersecuritymachine learningscientometric analysisbibliometric analysisScopusdeep learning |
| spellingShingle | Kamran Razzaq Mahmood Shah Advancing Cybersecurity Through Machine Learning: A Scientometric Analysis of Global Research Trends and Influential Contributions Journal of Cybersecurity and Privacy cybersecurity machine learning scientometric analysis bibliometric analysis Scopus deep learning |
| title | Advancing Cybersecurity Through Machine Learning: A Scientometric Analysis of Global Research Trends and Influential Contributions |
| title_full | Advancing Cybersecurity Through Machine Learning: A Scientometric Analysis of Global Research Trends and Influential Contributions |
| title_fullStr | Advancing Cybersecurity Through Machine Learning: A Scientometric Analysis of Global Research Trends and Influential Contributions |
| title_full_unstemmed | Advancing Cybersecurity Through Machine Learning: A Scientometric Analysis of Global Research Trends and Influential Contributions |
| title_short | Advancing Cybersecurity Through Machine Learning: A Scientometric Analysis of Global Research Trends and Influential Contributions |
| title_sort | advancing cybersecurity through machine learning a scientometric analysis of global research trends and influential contributions |
| topic | cybersecurity machine learning scientometric analysis bibliometric analysis Scopus deep learning |
| url | https://www.mdpi.com/2624-800X/5/2/12 |
| work_keys_str_mv | AT kamranrazzaq advancingcybersecuritythroughmachinelearningascientometricanalysisofglobalresearchtrendsandinfluentialcontributions AT mahmoodshah advancingcybersecuritythroughmachinelearningascientometricanalysisofglobalresearchtrendsandinfluentialcontributions |