Security of Medical Images Using a Key-Based Encryption Algorithm in the RDWT-RSVD Domain: SeMIE

Security of Medical Images Using a Key-Based Encryption Algorithm in the RDWT-RSVD Domain: SeMIE

Monu Singh, Amit Kumar Singh
Copyright: © 2023 |Pages: 20
DOI: 10.4018/JDM.318413
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Today, in the era of big data, an increasingly serious problem is the security of digital media in the healthcare domain. Encryption is a popular technique to resolve the security concern of medical data. In the paper, the authors propose a key-based encryption algorithm – namely, SeMIE, designed by RDWT and RSVD for healthcare applications – which can guarantee the security of the medical images. Initially, the image normalisation procedure along with RDWT-RSVD is followed to generate hash value. Here, image normalisation is used to ensure the high resistance against the geometric modifications. Then, a key expansion process is utilised with the hash value for generating the secure keys. Finally, the encryption process uses Feistel structure along with constant substitution-permutation functions to provide sufficient confusion and diffusion of cipher data. Experimental evaluation indicates that the SeMIE algorithm is secure against several attacks. From the simulation findings, it is inferred that the algorithm exhibits improved security compared to existing methods.
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1. 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 ‘JDM.318413.m01’ as original/plain image and ‘JDM.318413.m02’ 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).JDM.318413.m03 = JDM.318413.m04 …..(1)JDM.318413.m05 = JDM.318413.m06 …..(2) Where JDM.318413.m07 & ‘JDM.318413.m08’ are encryption and decryption functions along with key. In case of symmetric encryption (Roy et al., 2022), JDM.318413.m09 = JDM.318413.m10. However, JDM.318413.m11 ¹ JDM.318413.m12 in case of asymmetric encryption.

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