Adaptive Real-Time Risk and Impact Assessment for 5G Network Security

The expansion of 5G networks has led to larger attack surfaces due to more applications and use cases, more IoT connections, and the distributed 5G system architecture. Existing security frameworks often lack the ability to perform real-time, context-aware risk assessments that are specifically adapted to dynamic 5G environments. In this paper, we present an integrated framework that combines Snort intrusion detection with a risk and impact assessment model to evaluate threats in real time. By correlating intrusion alerts with contextual risk metrics tied to 5G core functions, the framework prioritizes incidents and supports timely mitigation. Evaluation in a controlled testbed shows the framework’s stability, scalability, and effective risk classification, thereby strengthening cybersecurity for next-generation networks.