Abstract

Financial institutions in emerging economies face significant cybersecurity challenges due to the increasing sophistication of cyber threats and limited resources for detection and prevention. This paper introduces Big Data-Driven Cybersecurity Models, designed to address gaps in threat detection and prevention by leveraging advanced analytics, machine learning, and real-time data processing. These models aim to strengthen the cybersecurity frameworks of financial institutions, particularly in emerging economies, by improving threat intelligence, detection accuracy, and response efficiency. The proposed models focus on the integration of big data technologies, such as distributed computing frameworks, data lakes, and advanced visualization tools, to handle large volumes of structured and unstructured data. By analyzing data from diverse sources, including transaction logs, network traffic, and customer interactions, the models enable the identification of anomalous patterns and potential security threats. Machine learning algorithms enhance predictive capabilities, allowing institutions to detect previously unknown threats and mitigate risks proactively. A key component of the models is their scalability and adaptability to resource-constrained environments. The framework includes cloud-based solutions to reduce infrastructure costs and ensure accessibility for smaller financial institutions. Additionally, the models emphasize the importance of fostering cybersecurity awareness and regulatory compliance to address human and organizational vulnerabilities. Validation through case studies and simulations demonstrates the effectiveness of these models in mitigating cybersecurity risks. Results show significant improvements in threat detection rates, response times, and cost-efficiency. These findings underscore the potential of big data-driven approaches to enhance the resilience of financial institutions against evolving cyber threats. This research provides actionable insights for policymakers, financial institutions, and technology developers seeking to strengthen cybersecurity in emerging economies. By adopting the proposed models, financial institutions can bridge critical gaps in threat detection and prevention, ensuring the security and trust necessary for sustainable economic growth.