Bibliometric Analysis and Knowledge Discovery Patterns in Cybersecurity-Based Fraud Detection Systems in the Banking Sector

This study introduces the Knowledge Discovery in Bibliometrics (KDB) Cycle, a novel conceptual framework that integrates bibliometric mapping, semantic knowledge extraction, predictive intelligence, and innovation forecasting to analyze cybersecurity-based fraud detection research in the banking sector. Unlike conventional bibliometric studies that primarily describe publication and citation trends, the proposed framework combines scientometric analysis with thematic evolution and predictive insights to identify emerging research frontiers and guide future technological and policy developments. The integration of multi-source bibliometric datasets with advanced visualization and knowledge discovery techniques represents a distinctive contribution to both cybersecurity research and bibliometric methodology.