The ultra-reliable and low-latency communication (uRLLC) plays a vital role in road safety and traffic management of intelligent transportation systems (ITS). Integrating unmanned aerial vehicles (UAVs) and non-orthogonal multiple access (NOMA) has become a prospective strategy for uRLLC by separately establishing line-of-sight (LoS) link and simultaneous transmissions. The confidentiality and security of information transmission in the context of uRLLC faces serious challenges, due to the openness nature of the wireless medium. Different from traditional encryption methods, featured by high computing complexity and serious processing delay, physical layer security (PLS) exploits the inherent properties of the wireless medium to prevent transmitted messages from being eavesdropped. In addition, NOMA-UAV systems pose unique challenges for secure transmission due to potential stronger LoS channels between the source and the eavesdroppers. Therefore, in this paper, we investigate the confidentiality and security of a NOMA-UAV uRLLC system, under which an UAV serves two types of users with different requirements, i.e., secret users (both security and reliability) and public users (only reliability). Based on the tools of stochastic geometry, we address the challenges of secure communications caused by the mobility of UAV, and derive the closed-form expression of secrecy rate maximization, a key metric for observing the key system parameters on the security and reliability. Furthermore, joint design of UAV trajectory and transmit power is proposed to enhance the system security. Finally, compared with popular PLS scheme empowered by UAV trajectory design, the proposed scheme is evaluated by numerical simulations for theoretical analyses and effectiveness in practice.

Considering that the actual operating environment of UAV is complex and easily disturbed by the space environment of urban buildings, the RoutE Planning Algorithm of Resilience Enhancement (REPARE) for UAV 3D route planning based on the A* algorithm and artificial potential fields algorithm is carried out in a targeted manner. First of all, in order to ensure the safety of the UAV design, we focus on the capabilities of the UAV body and build a risk identification, assessment, and modeling method such that the mission control parameters of the UAV can be determined. Then, the three-dimensional route planning algorithm based on the artificial potential fields algorithm is used to ensure the safe operation of the UAV online and in real time. At the same time, by adjusting the discriminant coefficient of potential risks in real time to deal with time-varying random disturbance encountered by the UAV, the resilience of the UAV 3D flight route planning can be improved. Finally, the effectiveness of the algorithm is verified by the simulation. The simulation results show that the REPARE algorithm can effectively solve the traditional route planning algorithm’s insufficiency in anti-disturbance. It is safer than a traditional A* route planning algorithm, and its running time is shorter than that of the traditional artificial potential field route planning algorithm. It solves the problems of local optimization, enhances the UAV’s ability to tolerate general uncertain disturbances, and eventually improves resilience of the system.