Artificial Intelligence in Cyber Security: A Bibliometric Analysis
Priyanka Chadha, Rajat Gera, Yogita Sharma, Saurav Dixit · Apple Academic Press eBooks · 2024
The purpose of the study is to review and understand the field of AI and cyber-security research to identify areas that need further investigation. The bibliometric methodology was followed which included productivity analysis to evaluate the total article productivity and impact through citation analysis and the most impactful authors, sources of publication, and countries. Through scientometric analysis, the intellectual and conceptual structure of this research domain was systematically mapped with WordCloud, trend analysis, co-occurrence network, and thematic mapping. For systematic review, the “Preferred Reporting Items for Systematic Reviews (PRISMA)” plans were followed for article search and selection from the Scopus Index for the period 2000-2022. The niche and emergent nature of this research domain is evident from the 232 productivity of the most prominent authors in this field. The majority of the significant contributions come from Europe and the USA, followed by South Asia, a few African nations, and countries in middle-east Asia. The emerging field of AI in cyber security is mostly confined to the AI tools of learning systems and machine learning (ML) and business domains of IOT, network cyber-attacks, and security which shows a selective focus of research in this domain on specific AI techniques and applications. Conclusions are drawn and future research areas are identified.