ArticleScientific reports2025
Enhancing IIoT security through blockchain-enabled workload analysis in fog computing environments.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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8 authors.
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Abstract
Robots and software are utilized in industrial automation to run machinery and processes in a variety of sectors. Numerous applications incorporate machine learning, the Internet of Things (IoT), and other methods to offer clever features that enhance user experience. Businesses and individuals can successfully accomplish both commercial and noncommercial requirements with the help of such technologies. Due to high risk as well as inefficiency of traditional procedures, organisations are expected to automate industrial processes. Aim of this research is to propose novel technique in workload analysis for fog network and blockchain model in security improvement for IIoT application. Here the IIoT network malicious activity is analysed using blockchain reinforcement gaussian neural network. Then the manufacturing industry workload analysis is carried out using fog cloud based virtual machine multilayer perceptron model. The experimental analysis is carried out for various security dataset in manufacturing industry in terms of latency, QoS, accuracy, reliability, data integrity.
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