Detecting Patterns of Attacks to Network Security in Urban Air Mobility with Answer Set Programming
Gioacchino Sterlicchio, Francesca Alessandra Lisi · Frontiers in artificial intelligence and applications · 2024
The growth of unmanned aerial vehicles (UAVs) will make the sky more crowded and pose several challenges as regards safety and security. Enabling high-rate, low-latency and ultra-reliable wireless communication between UAVs and ground base is crucial to realize their large-scale usage in the future, especially in the field of Urban Air Mobility. Recently, cellular-connected UAVs have drawn significant attention as a promising technology for Automatic Dependence Surveillance Broadcast (ADS-B) Like communication, which leverages other types of communication such as 4G LTE. In this work, we address the current lack of ADS-B security features and propose to use Answer Set Programming (ASP) for finding contrast sequential patterns that characterize different attacks on the 4G LTE network. The experiments show that a declarative approach is feasible in this context, and that the implementation of span and gap constraints make the search for patterns more efficient and effective.