AI-POWERED CYBERSECURITY IN THE CLOUD ERA: A BIBLIOMETRIC ANALYSIS OF RESEARCH TRENDS FROM 2017 TO 2024 A Bibliometric Analysis
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Abstract
Over the past decade, artificial intelligence (AI) has emerged as a transformative force in cybersecurity, particularly within cloud environments. Traditional security approaches struggle to keep pace with complex, evolving threats—making AI-driven models crucial for real-time detection and adaptive response. This paper presents a bibliometric analysis of 2,692 publications indexed in the Scopus database between 2017 and 2024, focusing on research integrating deep learning (DL) and natural language processing (NLP) within cybersecurity. Using VOSviewer and Biblioshiny, we explore thematic evolution, keyword trends, and collaboration networks. Our results highlight a surge in scholarly output post-2018, with deep learning and intrusion detection as central research themes. Emerging areas such as federated learning and adversarial machine learning indicate a growing emphasis on scalable, privacy-aware AI solutions. This study offers valuable insights for researchers and practitioners navigating the evolving intersection of AI and cybersecurity.
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