RADSEC

Environmental radioactivity monitoring networks are critical for detecting and responding to radiological hazards. These networks, comprising advanced spectrometric sensors and data transmission systems, are increasingly integrated into national critical infrastructures. However, their growing complexity and interconnectivity expose them to cybersecurity threats and operational disruptions.

This project aims to enhance the preparedness, response, and recovery capabilities of these monitoring networks against large-scale disruptions. By integrating machine learning techniques for anomaly detection, developing robust cybersecurity frameworks, and improving atmospheric modeling for threat prediction, we seek to fortify the resilience of these systems.