An Efficient, Secure, and Privacy-Preserving Communication Protocol for Drone-Assisted Disaster Management in Smart Cities

Drones (also referred to as unmanned aerial vehicles) have attracted significant attention within smart city ecosystems due to their ability to detect crises promptly and provide real-time support for disaster management. However, the increasing risks of cyber and physical attacks, along with potential private data leaks, present substantial challenges to their deployment in smart city environments. In this paper, we propose a secure communication protocol that leverages a novel group authentication scheme (GAS), tailored for disaster management scenarios in smart cities. The proposed scheme enables both group key agreement among drones and individual session key establishment between each drone and the control center (CC). Hence, our protocol preserves data confidentiality, message integrity, and data privacy, and verifies the authenticity of communicating parties. We employ physically unclonable functions (PUFs) and reverse fuzzy extractors to withstand critical threats, including machine learning (ML)-based modeling attacks and physical attacks. Our protocol also uses lightweight cryptographic primitives, such as hash-based message authentication codes (HMAC) and exclusive-OR (XOR) operations to ensure efficiency. Comprehensive security analysis using the formal proof and the Scyther tool demonstrates that our scheme resists corresponding attacks and protects data privacy. Ultimately, performance analysis results confirm that the proposed protocol is efficient and feasible.