Data/tasks of Industrial Internet of Things (IIoT) are extremely private and valuable to computing. Edge computing facilitates IIoT services by offering platforms of supportive facilities and functionalities. However, the convergence of intelligent edge computing and IIoT platforms has been held back by the need to develop systems for maintaining security and privacy. In this article, we propose a new framework for securely and confidentially sending, storing, and computing IIoT tasks. This framework employs a lightweight encryption scheme alongside modified ElGamal encryption and digital signature schemes. We analyzed the robustness of this framework in terms of security and privacy, and assessed its performance through simulations. Ultimately, the proposed framework outperformed the existing models in terms of time complexity, latency, and energy consumption.
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) under Grant 2021R1F1A1059840.
- Edge computing
- Industrial Internet of Things (IIoT)
- security and privacy
- task management