An Intelligent and Trust-Enabled Farming Systems With Blockchain and Digital Twins on Mobile Edge Computing

Advancement and flourishment in mobile edge computing (MEC) have motivated the farmers to deploy an efficient ecosystem in their farms. For further real-time monitoring and surveillance of the environment along with the deployment of intelligent farming, digital twin is considered as one of the emerging and most promising technologies. For proper optimization and utilization of physical systems, the physical components of the ecosystems are connected with the digital space. Further, the smart technologies and devices have convinced to address the expected level of requirements for accessing the rapid growth in farming associated with digital twins. However, with a large number of smart devices, huge amount of generated information from heterogeneous devices may increase the privacy and security concern by challenging the interrupting operations and management of services in smart farming. In addition, the growing risks associated with MEC by modifying the sensor readings and quality of service further affect the overall growth of intelligent farming. In order to resolve these challenges, this paper has proposed a secure surveillance architecture to detect deviations by incorporating digital twins in the ecosystem. Further, for real-time monitoring and preprocessing of information, we have integrated a four-dimensional trust mechanism along with blockchain. The four-dimensional trusted method recognizes the behavior of each communicating device during the transmission of information in the network. Further, blockchain strengthens the surveillance process of each device behavior by continuously monitoring their activities. The proposed mechanism is tested and verified against various abnormalities received from sensors by simulating false use cases in the ecosystem and compared against various security metrics over existing approaches. Furthermore, the proposed mechanism is validated against several security threats such as control command threat, coordinated cyber threats, accuracy, and decision-making and prediction of records over existing methods.