Abstract
•This research use kernel based gradient boosting neural network architecture integrated with classification using stochastic convolutional neural network.•The security of network has been enhanced using cryptographic cloud based cyber blockchain model.•To enhance the data security using cryptographic cloud based cyber blockchain model.•The experimental analysis is carried out for various EHR datasets in which parametric analysis is carried out in terms of classification and security.
The rapid rise of information technology and Internet technology has resulted in the emergence of electronic health records (EHR). This research proposes novel techniques in cyber security prevention-based electronic health records in feature selection as well as classification using DL methods. Here input EHR (electronic health record) data is processed for noise removal as well as removing of null values. This processed data is selected based on their features utilizing kernel based gradient boosting NN architecture integrated with classification using stochastic convolutional neural network. The data security of the network has been enhanced using a Cryptographic cloud based cyber blockchain model. The classification of EHR is analyzed in terms of accuracy of 97%, precision of 93%, recall of 91%, f-measure of 90%, RMSE of 88%. The security of the network is analyzed based on Data Transmission rate of 85%, Time Consumption of 55%, Data Privacy Rate of 95%.
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