ABSTRACT Existing IoT frameworks that rely on traditional blockchain require high computational power and cannot scale effectively in an IoT environment. We introduce Tangle, a DAG‐based blockchain framework that uses MAM to implement role‐based data access control for cognitive health monitoring. In our proposed approach, we send IoT data to a blockchain network. We added two new nodes in the network, Upload nodes and Processing nodes. Upload nodes encrypt the data and generate the MAM root, which then gets published to the Tangle network. Processing nodes receive this data and decrypt it using their assigned access keys before applying preprocessing steps and running Machine Learning algorithms. To handle both static and dynamic IoT data features effectively, we designed a transformer‐based incremental ML model for training. In our experimental results, our model attains a 98% accuracy compared to several existing state‐of‐the‐art machine learning techniques.
Srivastava et al. (Fri,) studied this question.
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