Network Security Threats and Defense Mechanisms for 6G Multi-Virtual Network Scenarios

Abstract

The introduction of 6G networks presents substantial challenges for network security, particularly in multi-virtual network topologies. The combination of network function virtualization (NFV) and software-defined networking (SDN) in 6G is designed to increase scalability and flexibility; nevertheless, these advances complicate network security management. The goal is to identify risks to network security and develop defense solutions for 6G multi-virtual network situations. SDN's virtualized network functions (VNFs) are utilized to provide stateful firewall services that provide scalable and dynamic threat prevention. The SDN controller is critical in developing a set of rules to prevent risky network connectivity and decrease possible risks. 6G multi-virtual network domains—attacking threats that involve different socket addresses so complex that usually applicable protection measures hardly tackle that scenario, machine learning (ML) algorithms, and Intelligent Osprey Optimized Versatile Random Forest (IOO-VRF) model—have been proposed for potentially harmful connection detection and predicting cyber threats accessing the network. Multiple open-access sources can be exploited to gather diverse data for collecting valuable information on studying network traffic and cyber threats. The experimental results indicate that IOO-VRF achieved prediction accuracy comparable to that of other traditional algorithms. The proposed model is assessed on various types of metrics, including accuracy (98%), precision (97.4%), recall (94%), and F1-score (93%). The results emphasized the importance of ML in combination with SDN and NFV for security in the case of resilient, expandable, and flexible security measures for future multi-virtual 6G network communications networks.