As a promising technique for the next generation communication network, integrated sensing and communication (ISAC) has attracted incremental research attentions due to its capabilities in spectrum sharing, cost saving, and data collecting. In this paper we utilize unmanned aerial vehicle (UAV) swarm to perform downlink ISAC transmission to serve multiple terrestrial legitimate users and sensing targets. To accommodate more practical application scenarios, we assume that there are also multiple malicious eavesdroppers in the network attempting to eavesdrop on the confidential signal. In order to enhance the security of the downlink transmission while maintaining sufficient sensing performance, we propose a joint optimization of the centralized trajectory of UAV swarm, the transmit beamforming on each UAV, and the ISAC schedule, which is eventually formulated as an average secrecy rate (ASR) maximization problem. A deep reinforcement learning (DRL) based algorithm is developed to solve the considered optimization problem and its effectiveness is validated via experimental simulations, which also proves its superiority over benchmark methods.

Reconfigurable intelligent surface (RIS) is viewed as a promising technique that can be utilized to improve the performance of systems by reconfiguring signal propagation environments. This article investigates green and secure unmanned aerial vehicle (UAV) Internet of Things (IoT) communications with the aid of RIS, where multiple UAVs harvest energy from a power beacon (PB) and send information uplink to access point (AP) with nonorthogonal multiple access (NOMA). In particular, communication can be divided into two phases during each time frame: 1) energy transfer and 2) information transmission (IT). Three RIS deployment strategies are proposed. In mode I, RISs are deployed between UAVs and AP to enhance the IT. In mode II, RISs are deployed between PB and UAVs to enhance the energy transfer. In mode III, RISs are deployed between UAVs and a hybrid AP (HAP) to enhance energy transfer and IT simultaneously. Considering phase compensation error caused by imperfect conditions, we define and evaluate ergodic capacity (EC), EC probability (ECP) and ergodic secrecy capacity (ESC) of three modes to measure the reliability and security of the system. The asymptotic expressions are also derived for further insights. Numerical results are presented to validate the correctness of theoretical derivations. Results demonstrate that the passive beamforming gain promised by RIS can significantly enhance the performance of systems. Mode III outperforms other modes in terms of reliability and security. When the transmission power and the number of UAVs increase, the ESCs of modes I and III converge to the same performance floor.