Amalgamation of Threat Intelligence for Cognitive Ransomware Detection in 5G Networks

The introduction of fifth generation cellular/mobile network technology (5G) creates new and exciting opportunities for connectivity and real-time interaction, but it also brings with it serious cybersecurity issues. Ransomware has the potential to cause significant damage to individuals, organizations and vital infrastructure if allowed to go unchecked in 5G environments. Staying ahead of the threat requires intelligence and dynamic security capabilities. This study proposes a novel architecture for proactive threat intelligence integration that enables cognitive ransomware detection tailored to 5G networks. The proposed smart integration strategy tightly integrates ransomware defense capabilities into 5G designs, ensuring the availability and reliability of 5G services even in the face of constantly evolving threats. The domain of computational thinking in 5G networks will remain incomplete as long as the benefits of cloud utilization are not fully exploited. This study proposes a conceptual model that still needs to be verified and validated before it can be approved. The aim of this research is to develop an intelligent ransomware detection system specifically designed for the upcoming 5G environment. Testing and validating the results across these parameters will lead to practical experience with deep learning (DL) to enable real-time analysis and detection of ransomware attack patterns and vulnerabilities in the upcoming 5G infrastructure.