RETRACTED: Cloud- and IoT-based deep learning technique-incorporated secured health monitoring system for dead diseases (Retracted article. See DEC, 2022)

Internet of Things (IoT)-enabled e-healthcare applications are contributing more to the society for providing healthcare monitoring services efficiently in smart environment. Security of healthcare system is to be considered as an important issue due to the huge volume of users and their secret data availability in this fast internet era and cloud databases. To store the patient's health data securely in the form of electronic version raises the concerns about the patient data privacy and security. Moreover, handling volume of data is also very complex task today with normal classifiers. For this purpose, many deep learning algorithms are available for classifying the huge volume of data successfully. For these all purposes, we propose a new healthcare monitoring system to monitor the disease level by predicting the diseases according to the original data that are collected from the patients who are available in remote places. Moreover, we propose a secured data storage model for storing the patient's data securely in cloud databases. Here, we introduce two new cryptographic algorithms for performing encryption and decryption processes. The experiments have been conducted for evaluating the performance of health monitoring system according to the particular diseases such as heart and diabetic diseases. This work considered the UCI medical dataset and the data collected from patients whose are available remotely through IoT devices. The proposed system is evaluated based on sensitivity, specificity, F-measure and prediction accuracy. The experimental results demonstrate that the proposed system outperforms the existing e-healthcare systems.