This paper investigates the secrecy performance of reconfigurable intelligent surfaces (RISs)-unmanned aerial vehicles (UAVs) within a 6G communication system. Specifically, a base station employing rate-splitting multiple access (RSMA) transmits both common and private messages to Internet of Things (IoT) devices (IDs) via a UAV relay (UR). Additionally, a mobile UAV eavesdropper (UE) is considered, capable of moving to intercept signals relayed by the UR. Therefore, we address the challenge of mobile UE position tracking to enhance physical layer security (PLS). We propose a framework that integrates real-time UE tracking using a particle filter (PF), a sequential Monte Carlo, for estimating the UE’s state. By continuously updating the UE location estimates, the considered system enables a proactive security measure, such as friendly jammers, to minimize the risk of intercepted communications. Simulation results demonstrate that accurate UE tracking significantly improves secrecy capacity and reduces the likelihood of successful eavesdropping.