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Top1. Introduction
With the proliferation of the internet of things (IoT), the healthcare industry has experienced significant growth in recent years (Bhuiyan et al., 2021). There is no doubt that the use of the IoT in healthcare not only improves operational efðciency for medical professionals and hospitals but also provides service convenience for supporting patients and their relatives. Especially after the COVID-19 pandemic, medical images serve as the information carrier for various purposes, such as medical diagnosis, telesurgery, defense, medical education, teleconsulting, research and business analytics (Singh et al., 2021; Khaldi et al., 2022; Sharma et al., 2021).
However, security of these images is a prerequisite for the application of the IoT in the healthcare industry (Li et al., 2021). Also, cloud-based healthcare is an important solution for the efficient storage, processing and continuous availability of medical data supplied by various sources. However, the protection of this externalised data and services in open environments is a big challenge (Haddad et al., 2020). Therefore, the protection of the medical information for smart healthcare is crucial (Wei et al., 2013). Encryption is a popular technique for protecting medical data from illegitimate access (Kaur & Kumar, 2020). The simplified procedure of an image encryption is depicted in Fig. 1.
Figure 1.
An image encryption process
Let us assume ‘
’ as original/plain image and ‘
’ as cipher image. The encryption and decryption process is carried out on plain and cipher image respectively as shown in equation (1) and equation (2).
= 
…..(1)
= 
…..(2) Where ‘
’ & ‘
’ are encryption and decryption functions along with key. In case of symmetric encryption (Roy et al., 2022), 
= 
. However, 
¹ 
in case of asymmetric encryption.