The concept of the Internet of Things (IoT) has drawn noteworthy attention to use the collected data anywhere in the world. Wireless Sensor Node (WSN) is integrated into the IoT for data collection. The IoT is very intense towards the security investigation. Patient data is medical information about an individual patient. Patient data contains their past and current health, treatment history, lifestyle options and genetic data. The patient data security is a most important issue in IoT. When a collected data get transmitted from the sensor node to the server it theft or altered by various intruders and it may cause a lack of security. In order to address these issues, in this research work, a novel technique called Radial Kernelized Regressive Merkle–Damgard Cryptographic Hash Blockchain (RKRMDCHB) technique is introduced to improve secure data transmission. The wireless sensor nodes are deployed to sense and monitor the data. At first, the sensing data are collected for secure transmission to the server. The RKRMDCHB technique uses the Radial Basis Kernelized Regression Function to perform the data classification. The regression function analyzes the input data and is categorized into various types of classes based on the radial basis kernel function. The classified data is given to the data block of the blockchain for secure transmission. The RKRMDCHB technique uses the Merkle–Damgard Cryptographic technique to generate the hash for each input data with the help of the one-way compression function. The data in the form of a hash is transmitted to the server through the internet. As a result, the RKRMDCHB technique ensures security and confidentiality to preserve the data and provide better communication. Experimental assessment is carried out on certain factors such as data confidentiality rate, data integrity, and processing time, with respect to a number of data sensed from the sensor device. The results demonstrate that the proposed RKRMDCHB technique provides an efficient solution for secure data transmission while preserving sensitive information against potential threats.
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