Blockchain and AI-Based Threat Detection for Enhanced Security in Financial Networks

The objective of this study is to comprehensively evaluate the methods to enhance cybersecurity in response to cyber threats against financial networks. The research is based on the integration of blockchain technology and AI-driven threat detection approaches. Our objective is to address a notable research gap with the use of Google Trends and VOS Viewer software to examine the scholarly environment related to this innovative methodology. We examined the keywords and utilized data visualization techniques to represent the areas of study, wherein we identified the key variables and emphasized on their necessity for future research. To improve our comprehension, we employed the technique of expert mining, which involves collecting significant insights from individuals who possess specialized knowledge in the respective field. The analysis of these observations yields a compilation of essential aspects that are instrumental in the successful incorporation of blockchain and AI-driven cybersecurity measures in financial networks. Drawing upon the aforementioned aspects, we have constructed a proposed model that presents a methodical framework that derives policy implications. The proposed model offers a comprehensive framework for many stakeholders, especially financial institutions and regulatory authorities, to enhance cybersecurity protocols within financial networks. The study’s results underscore the importance of the implementation of proactive measures in the realm of cybersecurity, specifically to emphasize the potential of blockchain and AI technologies to bolster the capacity of financial institutions to deal with cyber threats.