A Blockchain-Assisted Model for Data Security and Supervision in Unmanned Coal Measurement: Towards Sustainable Industry

With the rapid advancement of information technology, the coal transportation and sales industry has undergone a significant shift from traditional manual operations, such as vehicle dispatch, loading, and weighing, to intelligent unmanned shipping technologies. This transformation has notably improved operational efficiency and reduced costs, making coal transportation faster and more cost-effective. However, this shift toward digitalization has also introduced new risks, particularly in the form of heightened vulnerability to data attacks. Malicious activities such as coal measurement fraud and privacy data breaches have become critical concerns, threatening not only the security of operations but also the sustainable development of the coal industry. To address these challenges, this study presents an innovative blockchain-driven model designed to enhance the security and supervision of unmanned coal measurement data. The model integrates cutting-edge technologies to create a comprehensive solution. First, digital signature technology is employed to ensure secure authentication of platform operators, preventing identity fraud and unauthorized access. Second, differential privacy algorithms are utilized to encrypt sensitive operational data, such as remote command transmissions, significantly enhancing data confidentiality. Third, smart contract technology is implemented to automate the alignment of on-site measurement data with the blockchain system. This ensures seamless integration while detecting and mitigating malicious data tampering, thereby strengthening the system's defenses against cyber-attacks. The proposed model was implemented and validated on the Fabric blockchain platform, with simulation experiments demonstrating its effectiveness. The system successfully identified and defended against fraudulent activities, ensuring data integrity and security. Moreover, task execution times were maintained at a millisecond level, showcasing the model's efficiency. By providing a robust and efficient solution for data protection in unmanned coal transportation systems, this study not only addresses pressing security challenges but also promotes the sustainable development of the coal industry in an increasingly digitalized era.