Converging Blockchain and Deep Learning in UAV Network Defense Strategy: Ensuring Data Security During Flight

Unmanned Aerial Vehicles (UAVs) serve as highly versatile and efficient tools utilized across diverse industries for data collection purposes. However, they face vulnerabilities associated with wireless communication and data exchange, such as unauthorized access, data theft, and cyberattacks. These risks pose significant challenges to the establishment of reliable UAV network services. This study introduces a comprehensive blockchain-based architecture for UAV network services, designed to address these challenges. The proposed architecture tackles concerns related to identity authentication and privacy protection through the seamless integration of blockchain technology. Moreover, it incorporates advanced deep learning techniques to enhance UAV safety during operations and provide robust protection against cyber threats. A series of experimental tests were conducted, simulating various UAV network attack scenarios. The results of these experiments unequivocally demonstrate the feasibility and effectiveness of the blockchain-driven UAV network service architecture.