Bibliometric Analysis of Publication in the Field of Artificial Intelligence and Cyber Security

Year 2025, Volume: 13 Issue: 3, 355 - 366

Songül Karakuş , Sevinç Ay

https://doi.org/10.17694/bajece.1585201

Abstract

With the rapid changes in technology, artificial intelligence and cybersecurity have become two important areas inseparable from each other in today's digital world. The aim of this article is to analyze academic research on artificial intelligence and cybersecurity using bibliometric analysis method by providing an overview of artificial intelligence and cybersecurity. The findings obtained from the bibliometric analysis conducted between 2002-2025 (available at the time of the search) using the Web of Science database revealed that there were a total of 1296 publications and 4023 authors related to artificial intelligence and cybersecurity. The most frequently used keywords were examined by the authors using the VOSviewer software, and as a result of this examination, cybersecurity was found to be repeated 344 times, and artificial intelligence was found to be repeated 238 times. It has been also seen that the data obtained included publications from 97 countries and the country with the highest number of publications has China with 282 publications. The relationships between artificial intelligence and cyber security technologies have been also visualized with VOSviewer software. While artificial intelligence has been suggested in the theme analysis, methods such as intrusion detection system and feature selection have been identified as niche themes. As a result, this study shows the current status of studies on artificial intelligence and cyber security. It is also thought to guide future studies in this field.

Keywords

Artificial intelligence , Bibliometric analysis , Cyber security , R Studio , VOSwiever program.

References

• [1] H. Hoşgör, H. Güngördü. “Sağlıkta Yapay Zekanın Kullanım Alanları Üzerine Nitel Bir Araştırma.”, European Journal of Science and Technology, Vol.35, 2022, pp. 395-407.
• [2] F. Coşkun, H.D. Gülleroğlu. “Yapay zekânın tarih içindeki gelişimi ve eğitimde kullanılması.”, Ankara University Journal of Faculty of Educational Sciences (JFES), Vol.54, No.3, 2021, pp.947-966.
• [3] E. Gümüş, B. Medetoğlu, S. Tutar. “Finans ve bankacılık sisteminde yapay zekâ kullanımı: kullanıcılar üzerine bir uygulama.”, Journal of Bucak Business Administration Faculty, Vol.3, No.1, 2020. pp.28-53.
• [4] B. Kesici, M.S. Yıldız. “Kalite kontrol faaliyetlerinde yapay zekâ kullanımı ve bir otomotiv yan sanayisinde uygulanması.”, Yalova Journal of Social Sciences, Vol.6, No.12, 2016, pp.307-323.
• [5] E.Ö. Çizer, “Pazarlamada Yapay Zeka Uygulamaları.” Individual, Society, Politics in the Digitalizing World, Congress Abstracts, İstanbul, Turkey, 26-27 May 2022.
• [6] H. Güven, E.T.A. Güven. “Yapay Zekâ Uygulamalarının E-Ticarette Kullanımı.”, International Journal of Management and Administration, Vol.7, No.13, 2023, pp.69-94.
• [7] İ Terzi, M.M. Özgüven, Z Altaş, T. Uygun. “Tarımda Yapay Zeka Kullanımı.”, International Erciyes Agriculture, Animal & Food Sciences Conference, Kayseri, Turkey, 24-27 April 2019.
• [8] Z. Öğretmen Kotil. ”Hukukta Yapay Zekâ Uygulamaları.”, Artificial Intelligence Working Group, 2022, pp.1-12.
• [9] C. Tiftik. “Insan kaynakları yönetiminde yapay zekâ teknolojileri ve uygulamaları.”, IBAD Journal of Social Sciences, Vol.9, 2021. pp.374-390.
• [10] R. Dirik, E. Taşkesen, Ö. Dirik. “Yenilenebilir Enerji Kaynaklarında Yapay Zekâ Kullanımı.”, In International Conference on Recent Academic Studies, Vol.1, 2023, pp.28-35.
• [11] N.S. Partigöç. “Afet risk yönetiminde yapay zekâ kullanımının rolü.”, Journal of Information Technologies (JIT), Vol.15, No.4, 2022, pp.401-411.
• [12] A. Tekin. “Yapay zeka kullanımının sanata etkileri.”, Journal of Urban Academy, Vol.11 No.4, 2018, pp.692-702.
• [13] M.Y. Başer, A. Olcay. “Akıllı turizmde yapay zekâ teknolojisi.” Gaziantep University Journal of Social Sciences, Vol. 21, No.3, 2022. pp. 1795-1817.
• [14] T.M. Erbir, O. Sevli. “Arama Motorlarında Yapay Zekâ Teknolojilerinin Kullanımı.” 10th International Nardin Artuklu Scientific Researches Conference , Turkey, 2023.
• [15] X. Liu, C. Li. (2023). Yapay zeka ve çeviri. Routledge Çeviri Teknolojisi Ansiklopedisi Routledge, 2023, p. 280-302.
• [16] B. Anadolu. “Dijital hikâye anlatıcılığı bağlamında yapay zekânın sinemaya etkisi: Sunspring ve It’s No Game filmlerinin analizi.”, Journal of Erciyes Communication, Vol.1, 2019, pp.39-56.
• [17] A. Efe. “Oyun Teorisi Perspektifinden Bilgisayar Oyunlarında Yapay Zekâ Kullanımı Üzerine Bir Değerlendirme.”, Istanbul Gelisim University Journal of Social Sciences (IGUJSS), Vol. 11, No.1, 2024, pp.422-441.
• [18] M.M. Mıjwıl, E. Sadıkoğlu, E. Cengiz, H. Candan. “Siber Güvenlikte Yapay Zekanın Rolü ve Önemi: Bir Derleme.”, Journal of Data Science, Vol.5, No.2, 2022, pp.97-105.
• [19] R. Von Solms, J. Van Niekerk. “From information security to cyber security.”, Computers & Security, Vol.38, 2013, pp.97-102.
• [20] A. Tekke, A. Lale. “Sosyal Medyada Etik, Bilgi Manipülasyonu ve Siber Güvenlik”, Journal of Academic Inquiries (AID), Vol.16, No.2, 2021, pp. 44-62.
• [21] N. De Bellis. “Bibliometrics and citation analysis: from the science citation index to cybermetrics.”, scarecrow press, 2009.
• [22] B. Godin. “On the origins of bibliometrics.”, Scientometrics, Vol.68, No.1, 2006, pp.109-133.
• [23] C. Chen. “Science mapping: A systematic review of the literature”, Journal of Data and Information Science, Vol.2, 2017, pp. 1-40.
• [24] N. Jan Eck, L. Waltman. “Software survey: VOSviewer, a computer program for bibliometric mapping.”, Scientometrics, Vol.84, No.2, 2010, pp.523-538.
• [25] Z.A. Polat, M. Alkan. “Jeodezi, jeoinformasyon ve arazi yönetimi dergisi’nin bibliyometrik analizi.”, TMMOB Chamber of Surveying and Cadastre Engineers, Vol.15, 2015, pp.25-28.
• [26] F. Ullah, H. Naeem, S. Jabbar, S. Khalid, M.A. Latif, F. Al-Turjman, L. Mostarda. “Cyber security threats detection in internet of things using deep learning approach.”, IEEE access, Vol.7, 2019, pp.124379-124389.
• [27] B.J. Radford, L.M. Apolonio, A.J. Trias, J.A. Simpson, Network traffic anomaly detection using recurrent neural networks, arXiv preprint arXiv:1803.10769, 2018.
• [28] M.J.H. Faruk, H. Shahriar, M. Valero, F.L. Barsha, S. Sobhan, M.A. Khan, M. Whitman, A. Cuzzocrea, D. Lo, A. Rahman, F. Wu, “Malware detection and prevention using artificial intelligence techniques.”, In 2021 IEEE international conference on big data (big data), 15-18 December 2021 (pp. 5369-5377). IEEE.
• [29] M. Stampar, K. Fertalj. “Artificial intelligence in network intrusion detection.” In 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), IEEE. May 2015.
• [30] F.M. Teichmann, S.R. Boticiu. “Adequate responses to cyber-attacks.”, International Cybersecurity Law Review, Vol.5, No.2, 2024, pp.337-345.
• [31] S. More, A. Rohela. “Vulnerability assessment and penetration testing through artificial intelligence.”, International Journal of Recent Trends in Engineering Research, Vol.4, No.1, 2018, pp.217-224.
• [32] M. Schmitt, I. Flechais. “Digital deception: generative artificial intelligence in social engineering and phishing.”, Artificial Intelligence Review, Vol.57, No.12, 2024, pp.1-23.
• [33] İ. Yurtseven, S. Bagriyanik, S. Ayvaz. “A review of spam detection in social media.”, In 2021 6th International Conference on Computer Science and Engineering (UBMK), IEEE, September 2021.
• [34] D.J. Dsouza, A.P. Rodrigues, R. Fernandes. Multi-modal Comparative Analysis on Execution of Phishing Detection using Artificial Intelligence. IEEE Access, 2024.
• [35] B. Aytan, N. Barışçı. “Siber savunma alanında yapay zekâ tabanlı saldırı tespiti ve analizi.” In Proceeding of the 2nd International Symposium on Innovative Approaches in Scientific Studies, Samsun, December 2018.
• [36] B. Özdemir. “Siber tehdit istihbaratında yapay zeka ve makine öğrenmesi.”, The Journal of Defence and Security Research, Vol.1, No.1, 2024, pp.75-96.
• [37] S. Li, D. Qin, X. Wu, J. Li, B. Li, W. Han. “False alert detection based on deep learning and machine learning.”, International Journal on Semantic Web and Information Systems (IJSWIS), Vol.18, No.1, 2022, pp.1-21.
• [38] Y. Liu, S. Li, X. Wang, L. Xu. “A review of hybrid cyber threats modelling and detection using artificial intelligence in IIoT.”, Computer Modeling in Engineering & Sciences, Vol.140, No.2, 2024.
• [39] J.H. Li. “Cyber security meets artificial intelligence: a survey.” Frontiers of Information Technology & Electronic Engineering, Vol.19, No.12, 2018, pp.1462-1474.
• [40] Web of Science. https://www.webofscience.com/wos/ woscc/analyze-results/b2364eca-c198-4339-b048-dc965c916cdd-4986caa2 (Access Date: 15. 10. 2024