Intelligent detection and adaptive mitigation of radio interference with RIS-supported drones - AI-supported anomaly identification, precise radio interference attack classification, adaptive mitigation measures, RIS-supported drones, expanded environmental awareness and network protection, autonomous sensor platforms for efficient V2X communication

Driving assistance systems and autonomous vehicles offer great advantages for traffic safety and energy efficiency. X2X (everything-to-everything) communication allows real-time information exchange between vehicles, pedestrians, and infrastructure, but is susceptible to cyberattacks such as jamming that could impair communication and safety. Scientists at the Hamm-Lippstadt University of Applied Sciences have developed a method of anomaly identification, precise classification, and adaptive radio interference mitigation measures that allows early detection and efficient reaction to such attacks. Fig. 1 shows a scenario in which a malicious drone disrupts V2P (vehicle-to-pedestrian) communication at an intersection, placing unprotected traffic participants in danger. Supporting drones function as reconfigurable intelligent surfaces (RISs) that allow targeted spatial filtering. MIMO systems are used to filter the signal based on the direction of arrival (DoA), minimizing interference effects and restoring communication stability. Fig. 2 shows a multi-step process for anomaly identification, precise interference attack classification, and adaptive mitigation measures. It begins with AI-supported basic and in-depth monitoring for performance parameter analysis. AI techniques are then used on a model to analyze the interference for precise classification. Finally, a targeted countermeasure is selected and used to effectively reduce the attack’s impact.