Security factor identification of drone delivery system based on blockchain

Traditional drone delivery systems usually rely on centralized management. They face problems such as insufficient data security and privacy protection, as well as difficulty in information sharing. They also lack real-time automated security monitoring and emergency response mechanisms. To solve these problems, this paper implements a security enhancement solution based on blockchain technology to improve drone delivery systems’ security, transparency, and automated response capabilities. During the research process, a comprehensive analysis of the security threats the drone delivery system faces is conducted first. Key attack surfaces such as communication security, data integrity, identity authentication, and permission management are identified. Typical attack scenarios are built. Subsequently, a blockchain-based security enhancement solution is designed. A distributed trust mechanism, a dynamic response mechanism driven by smart contracts, and a full lifecycle monitoring and traceability mechanism are constructed to enhance data security, system transparency, and automation capabilities. Finally, the effectiveness of the proposed solution is verified through experiments. The experimental results show that the drone delivery system using the blockchain security enhancement solution is superior to the unenhanced system in terms of security, efficiency, and stability. Taking security as an example, when responding to GPS (Global Positioning System) spoofing attacks, the average spoofing detection rate of the enhanced system is 87.67%, significantly higher than the 40% of the unenhanced system. Under DDoS (Distributed Denial of Service attack) attacks, the attack success rates of the enhanced system under different attack intensities are 10.2%, 18.9%, and 41.5%, respectively. In comparison, the attack success rates of the unenhanced system are 23.5%, 49.7%, and 81.3%, respectively. Regarding data tampering protection, the protection success rate of the enhanced system is 94.33%, while that of the unenhanced system is 62.6%. The research results of this paper provide new theoretical support and practical guidance for the security of drone delivery systems.