Mobile Unmanned Aerial Vehicles (UAVs) forming Flying Ad Hoc Networks (FANETs) offer promising applications, but dynamic network structures, limited resources, and potential single points of failure create security challenges. While cluster-based data aggregation, where data is collected and combined at Cluster Heads (CHs) before transmission, improves efficiency, traditional techniques can compromise data privacy. This paper introduces SSDBFAN, a scalable and secure cluster-based data aggregation framework for Flying Ad Hoc Networks (FANETs). The proposed approach integrates the Frilled Lizard Optimization Algorithm (FLOA) for efficient cluster head selection with blockchain technology and post-quantum cryptographic techniques, including lattice-based homomorphic encryption and the Chinese Remainder Theorem, to ensure privacy-preserving data aggregation. Additionally, a hybrid online/offline signature mechanism is employed to achieve secure and efficient authentication with reduced computational overhead. The performance of the proposed framework is evaluated using NS-3 simulations under varying network sizes. Experimental results demonstrate that SSDBFAN significantly improves communication efficiency, reduces computational cost, and enhances network stability compared to existing schemes. Furthermore, scalability analysis with up to 500 UAV nodes confirms that the proposed framework effectively controls blockchain overhead, including bandwidth consumption, consensus latency, and storage requirements. Comparative evaluation with existing optimization algorithms shows that FLOA achieves superior performance in terms of cluster stability, delay, and throughput. These results validate the effectiveness of SSDBFAN as a scalable and security-aware solution for large-scale FANET environments.

This work presents an innovative blockchain-based AI-driven key management scheme designed to enhance the security and efficiency of Fog environment while extending its application to Flying Ad-Hoc Networks (FANETs). The proposed protocol facilitates secure key establishment among UAV-enabled devices, UAVs in FANETs and their respective gateway nodes. The scheme incorporates a Post-Quantum Multivariate Identity-based Signature Scheme (PQ-MISS) along with Zero-Knowledge Proof (ZKP) to improve data aggregation efficiency and privacy. Additionally, it employs a polynomial composition-based encryption mechanism for secure computation and an aggregate signature scheme to ensure data authenticity and integrity across Fog and FANET networks. Fog servers partially construct blockchain blocks with secure data from smart devices and UAVs, which are then completed. cloud servers (CSs ) who is in-charge in the P2P network validates and commits blocks through PBFT-based distributed consensus. This architecture enables seamless integration of AI algorithms for FANET and smart user’s data analytics and accurate predictions, addressing operational requirements of Fog Devices (FDs) and FANET environment. Moreover, simulations using ns3 tool demonstrate efficiency of PQMISS in reducing communication overhead and improving data aggregation and verification processes in FANET systems. Comparative analysis highlights the proposed scheme’s superiority in computational cost, security and reliability, making it a robust solution for secure and efficient operation in fog-enabled FANETs.