Multilayered CBDC Fraud Detection Framework: Securing Digital Currency Ecosystems

This article shows the development and implementation of fraud monitoring systems for Central Bank Digital Currencies (CBDCs). The article tackles the distinctive security issues associated with digital currencies by employing a comprehensive methodology that integrates a systematic literature review, detailed case study examination, statistical analysis of transaction datasets, and rigorous validation testing protocols. The article identifies critical vulnerabilities in existing financial systems and proposes a multi-layered defense framework that balances security imperatives with privacy considerations. Statistical analysis demonstrates that the proposed architecture achieves superior fraud detection capabilities while maintaining operational efficiency across diverse attack vectors. The article explores tensions between privacy preservation and comprehensive monitoring, examines scalability concerns for large-scale implementations, analyzes cross-border transaction complexities, and evaluates regulatory frameworks for CBDC fraud investigation. Future directions emphasize the integration of advanced AI techniques, collaborative frameworks for cross-jurisdictional monitoring, privacy-enhancing technologies, standardization opportunities, and strategic research priorities to address remaining gaps in CBDC security capabilities.