Hybrid AES model with elliptic curve and ID based key generation for IOT in telemedicine

Abstract

With the aid of various medical sensors, a remote patient monitoring system will be designed for Internet of Things (IoT)-based telemedicine applications. With the aid of AI algorithms, the healthcare sensor data will eventually be identified and forecasted. In the current healthcare sector, a lot of sensitive data is exchanged. The integration of an increasing number of digital technologies in hospitals, together with laboratory and outpatient examinations of patients and their accompanying files, have all contributed to the growth of data related to patient care in recent years. Electronic health record systems are medical management systems that include all of a patient's personal and medical data. As a consequence, it is crucial that this data be stored and secured in the cloud. This paper describes a data storage and security solution that is well suited for the Internet of Medical Things. Because of the shorter key length, the improved Elliptic Curve Cryptography (ECC) approach using Blake2 hashing takes substantially less time to encrypt. The data is encrypted with the created key and the Advanced Encrypted Standard (AES). The proposed security approach is a hybrid cryptography technique that combines symmetric and asymmetric key encryption, resulting in a more secure system.