The Role of Graph Theory in Network Security: Bibliometric Insights into Research Patterns and Developments

Abstract

This bibliometric analysis examines the role of graph theory in network security, leveraging the Scopus database to analyze research trends, significant contributors, and thematic developments in the field. Graph theory offers a robust mathematical framework for modeling networked systems, identifying vulnerabilities, and analyzing attack paths, which are crucial for enhancing resilience against cyber threats. Using Biblioshiny and VOSviewer software, this study maps out various aspects of the literature, including annual scientific production, most significant authors, and key publication sources. The findings highlight the increasing scholarly interest in this area, with a consistent growth rate reflecting the field’s response to evolving cybersecurity challenges. Notable authors, sources, and highly cited documents underscore the foundational contributions that shape current research. Trend topics, such as machine learning and anomaly detection, illustrate a shift toward addressing modern threats, while a thematic map categorizes research themes by development and centrality, distinguishing between established and emerging areas. The co-occurrence analysis of keywords reveals interconnected research areas, emphasizing the multidisciplinary nature of graph theory applications in network security. Bibliographic coupling of sources shows scholarly connections and collaborative focus areas within the literature. Additionally, the co-authorship analysis of countries demonstrates strong international collaboration, with nations like China and the United Kingdom acting as central hubs. This study provides insights into the field’s evolution, highlighting key research themes and collaborative networks that support advancements in network security through graph theory.