BIBLIOMETRIC RESEARCH IN THE FIELD OF CYBERSECURITY: FOCUS ON ARTIFICIAL INTELLIGENCE AND ATTACK DETECTION

Aleksandar ŠIJAN; Luka ILIĆ; Dejan VIDUKA; Chulung LEE; Bratislav  PREDIĆ

doi:10.5937/jpmnt14-66097

Aleksandar ŠIJAN Faculty of Electronic Engineering, University of Niš, Niš, Serbia https://orcid.org/0000-0002-7133-5700
Luka ILIĆ Faculty of Electronic Engineering, University of Niš, Niš, Serbia https://orcid.org/0009-0004-5577-4713
Dejan VIDUKA Faculty of Information Technologies, Alfa BK University, Belgrade, Serbia https://orcid.org/0000-0001-9147-8103
Chulung LEE Department of Industrial and Management Engineering, Korea University, Seoul, Republic of Korea https://orcid.org/0000-0002-2041-0221
Bratislav PREDIĆ Faculty of Electronic Engineering, University of Niš, Niš, Serbia https://orcid.org/0000-0002-3679-5058

DOI: https://doi.org/10.5937/jpmnt14-66097

Sažetak

This paper presents a comprehensive bibliometric analysis of the field of cybersecurity, with a specific focus on the application of artificial intelligence (AI) in attack detection. The study aims to provide insights into the trends, research areas, and key contributions in this rapidly evolving field, while also exploring the theoretical underpinnings of security and the challenges associated with the implementation of AI in attack detection. The integration of AI in cybersecurity has introduced significant advancements in detecting and mitigating cyber threats. However, it also poses several challenges, including the need for large datasets to train AI models, the complexity of accurately identifying novel and sophisticated attacks, and concerns regarding the transparency and interpretability of AI decisions. Theoretical frameworks in cybersecurity emphasize the importance of robust and adaptive defense mechanisms, which AI technologies strive to enhance. Despite these advancements, the dynamic nature of cyber threats necessitates continuous innovation and interdisciplinary collaboration. The search spanned publications from 2004 to 2024 and was performed on June 13, 2024. The findings of this bibliometric analysis provide valuable insights into the development and current state of research at the intersection of cybersecurity and AI. The study highlights the most influential works, prominent authors, and emerging trends in this critical area of study. Additionally, it shed light on the theoretical aspects of cybersecurity and the practical challenges faced in implementing AI for attack detection. This comprehensive analysis aims to serve as a valuable resource for researchers, practitioners, and policymakers, fostering a deeper understanding of how AI technologies can be effectively leveraged to enhance cybersecurity measures and address the complexities of modern cyber threats.

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