Blockchain-Driven AI-Enhanced Post-Quantum Multivariate Identity-based Signature and Privacy-Preserving Data Aggregation Scheme for Fog-enabled Flying Ad-Hoc Networks
For researchers and practitioners in UAV and fog computing security, this paper addresses the need for post-quantum secure and privacy-preserving data aggregation in FANETs, but the contribution is incremental as it combines known techniques.
This work proposes a blockchain-based, AI-enhanced key management framework for fog-enabled FANETs that uses a post-quantum multivariate identity-based signature scheme and zero-knowledge proofs to achieve secure key establishment and privacy-preserving data aggregation. NS-3 simulations show reduced communication overhead and improved speed and reliability compared to existing methods.
The integration of Fog Computing with Flying Ad-Hoc Networks (FANETs) offers promising capabilities for decentralized, low-latency intelligence in UAV-based applications. However, the distributed nature, mobility, and resource constraints of FANETs expose them to significant security and privacy challenges, particularly against quantum threats. To address these issues, this work introduces a blockchain-based, AI-enhanced key management framework designed for fog-enabled FANETs. The proposed scheme employs a Post-Quantum Multivariate Identity-Based Signature Scheme (PQ-MISS) and Zero-Knowledge Proofs (ZKPs) to achieve secure key establishment, privacy-preserving data aggregation, and integrity verification. A polynomial composition-based encryption mechanism and an aggregate signature model support secure and efficient multi-device communication across fog and UAV layers. Fog servers construct partial blockchain blocks from validated UAV data. These blocks are completed and mined by Cloud Servers (CSs). AI algorithms then analyze the verified data to generate accurate predictions and insights. NS-3 simulations validate the efficiency of PQ-MISS in reducing communication overhead while improving the speed and reliability of data aggregation and verification. Comparative analysis demonstrates the proposed scheme's advantages over existing methods in computational cost, post-quantum security, and scalability, making it a robust solution for secure, intelligent, and future-ready FANET systems.