Multi-Objective Optimization for Secure UAV-Assisted Data Collection via Intermittent Jamming

Unmanned Aerial Vehicles (UAVs) have emerged as pivotal tools for Internet of Things (IoT) data collection by leveraging their superior mobility. However, the open nature of wireless channels renders UAV communications susceptible to malicious eavesdropping. Furthermore, the limited onboard energy of UAVs and the stringent requirements for Age of Information (AoI) freshness pose significant challenges to data collection operations. To address these issues, this paper proposes a dual-UAV cooperative secure data collection scheme based on an intermittent jamming strategy. We formulate a multi-objective optimization problem aimed at minimizing AoI and energy consumption while maximizing the eavesdropper’s Bit Error Rate (BER) by jointly optimizing UAV trajectories, time scheduling, and jamming parameters. Given the non-convexity of the problem and the complex coupling between variables, we develop an efficient iterative algorithm based on Block Coordinate Descent (BCD) and Successive Convex Approximation (SCA). Simulation results demonstrate that the proposed scheme achieves an optimal trade-off among the metrics.