A Sensor-Based Data Analytics for Patient Monitoring in Connected Healthcare Applications

Abstract

Nowadays, Remote sensor networks have been broadly utilized in medical services applications, like emergency clinic and home patient checking. Compared to wired organizations, Remote clinical sensor networks are more vulnerable to spying, modification, manipulation, and playback attacks. To get remote clinical sensor organizations, a lot of work has been done. The current methods can protect patient information during transmission, but they can't preclude the director of the patient data set from uncovering sensitive patient information during an attack. In this research, we offer a practical method for preventing internal attacks by storing patient data on multiple information servers. The main goal of this work is to properly disseminate patient information across several information servers while using the Paillier and elgamal cryptosystems to conduct measurement investigations on the data without jeopardizing the patients' safety. Remote clinical sensor networks definitely lead to an improved knowledge of the nature of care without affecting patients' comfort. However, there are numerous potential security risks to the patient's sensitive physiological information transferred over public networks and stored in back-end frameworks. Snooping creates a security risk to the privacy of patient information.