Abstract
The Industrial Internet of Things (IIoT) is designed to leverage the smart industries' performance with information and communication technologies. The functions of the industrial devices and the process control are managed using IoT components for automated production. However, external IoT support increases the risk of vulnerabilities that intervene in the industries' operational process. In this article, Blockchain-aided Secure Process Control is introduced. This proposal focuses on mitigating the intervening external vulnerabilities in the sequential task processing intervals. The resilient and vulnerable process controls are differentiated based on their allocation-to-outcome factor. This factor serves as the key to classify the nature of the process control. For this purpose, classification tree-based learning is employed. The outcome of the classification tree is useful in blockchain interactions with the process controller. The process controller is administered using the blockchain system based on the classification output. The harmonized process of blockchain and outcome factor-based classification improves the job delivery rate under controlled time. The metrics latency, adversary detection, false rate, and job failures are used for analyzing the proposed method's performance. The proposed method achieves an 11.9% high allocation rate, 14.14% less adversary impact, and 16.45% less processing time for different tasks.
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Hemamalini, V., Zayaraz, G. & Vijayalakshmi, V. BSPC: blockchain-aided secure process control for improving the efficiency of industrial Internet of Things. J Ambient Intell Human Comput 14, 11517–11530 (2023). https://doi.org/10.1007/s12652-022-03721-3
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DOI: https://doi.org/10.1007/s12652-022-03721-3