Improved Gentry–Halevi's fully homomorphic encryption‐based lightweight privacy preserving scheme for securing medical Internet of Things

Abstract

AbstractInternet of Medical Things (IoMT) solutions have proliferated rapidly in the COVID‐19 pandemic era. The smart medical sensors capture real‐time data from remote patients and communicate it to medical servers in a secure and privacy‐preserving manner. It is a herculean challenge to guarantee security and privacy in Medical IoT applications. Hence, an improved Gentry–Halevi's fully homomorphic encryption‐based (IGHFHE) lightweight privacy preserving user authentication scheme is proposed in this work. The scheme is proposed with an integer matrix computation strategy for securing data computation with privacy protection. It adopts the translation process of Gentry–Halevi's fully homomorphic encryption process for performing homomorphic addition and multiplication, then encrypt an integer matrix modulo that represents a positive integer. Extensive informal investigation and simulation of the proposed IGHFHE scheme shows that it is more resistant to well‐known attacks for preventing authentication breaches. Also, the proposed IGHFHE scheme reduced computational and storage overhead by 4.98% and 5.78% respectively on average in comparison to other prevailing schemes.