Cloud- and IoT-based deep learning technique-incorporated secured health monitoring system for dead diseases

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