A Resilience-Driven Concept to Manage Drone Intrusions in U-Space

With the U-space revolution, drones are going to reshape both the physical space and the cyberspace of the future urban environment, also with the support of autonomy and artificial intelligence (AI). However, this revolution comes with the cost of new multi-domain risks, which may be traced back to cyber and physical threats within drone-based new entrants. A proper assessment and treatment of these risks is essential to achieve the safety and security objectives of U-space for the drone ecosystem. This will entail further research, especially for the analysis of drone intruders and for the mitigation of the related U-space impacts. This work proposes a concept for improving the U-space resilience through a novel AI-centric service, named DARS (drone attack resilience service), focused on managing unauthorised operations of intruder drones in the physical and cyber domains. DARS-related threat scenarios and risk-assessment capabilities are discussed, resorting also to modelling specific drone cyber-physical attacks. A detailed analysis of DARS AI-centric functional architecture is provided, with a survey of the potential approaches for intruder trajectory prediction and intent recognition, to be used for the next design stages. Lastly, the work provides a preliminary analysis of how the neutralisation functions could be implemented in DARS.