Resource Allocation in Secure ISAC-Enabled UAV Swarms for SAR Operations

Search and Rescue (SAR) operations in disasteraffected areas require rapid victim detection while ensuring secure and energy-efficient communication under severe resource constraints. This paper presents a novel multi-objective optimization framework for Integrated Sensing and Communication (ISAC)-enabled Unmanned Aerial Vehicle (UAV) swarms that jointly optimizes victim detection accuracy, data security, energy consumption, and mission completion time. The framework determines optimal UAV-To-Targets associations, sensing and communication power allocation and encryption algorithm selection. The framework explicitly addresses the critical tradeoffs between detection performance and security overhead by incorporating encryption-dependent communication rates and latency constraints, while accounting for strict mission time limits. The proposed formulation enables UAVs to adapt their sensing, encryption, and communication strategies based on dynamic mission requirements, ensuring that sensitive victim location data is protected from potential adversaries without compromising the timeliness of rescue operations. Simulation results demonstrate the effectiveness of the framework in balancing competing objectives, providing valuable insights for deploying secure and efficient UAV-based ISAC systems in emergency response scenarios. The work contributes to advancing intelligent disaster response systems where security and operational efficiency must coexist under stringent resource constraints.