## 2 Related Work
An efficient and scalable Advanced Encryption Standard (AES) cryptosystem was presented by the authors in [47] to ensure enhanced defence against known assaults and the security of the medical record, successfully before transmission, especially medical imaging. The main contribution of the study was creating a scalable, safe hardware-software co-design system; a flexible and adaptable medical imaging processing system that incorporates authentication-based methods of the AES cryptosystem on ZedBoard with the least amount of overhead, including PUF and TRNG3. This system addressed security issues, while the issue of privacy was not considered. Although various searchable SE techniques address the issue of privacy preservation of data in a cloud setting, various implementations of these techniques have been found to have one issue or the other. SEs based on symmetric key encryption techniques such as [48] were found leak important information about the documents when analysed by statistical techniques. The approach was also found to be useful only for words of the same length. The SE technique employed by [49; 50] are not efficient because they only support exact match queries. The drawback of the existing searchable SE techniques which support only exact keyword searches is that the system efficiency reduces as the number of distinct keywords in the document increases. In order to solve the problem of searchable SE, researchers introduced Fuzzy Searchable Encryption-based (FSE) systems. FSE returns both exact matching or closest possible matching files based on keyword similarity semantics, as fuzzy keyword search can tolerate minor typos and formatting inconsistencies [51]. [PERSON] [52] presented a technique solving the issue of preserving privacy in a biometric identification system based on a fuzzy search scheme. However, the technique is unsuitable for many applications when data are regularly updated or streaming. Other FSE-based techniques such as [53; 54; 55] are based on symmetric key encryption techniques which are vulnerable to Man-in-the-Middle Attack (MIMA). As a measure to solve the problem of MIMA faced by SE and FSE that are based on symmetric encryption techniques, a searchable encryption technique that is based on public key encryption (PkSE) was introduced. PKSE addresses cases such as when the outsourced data (e.g., medical data, stock quotes, emails, etc.) are public and uploaded by different owners and the user is not aware of it; at the same time, the user wishes to retrieve certain files without revealing to the server which file they want. The first PKSE developed by [56] failed to protect keyword privacy in the public settings. The PKSE proposed by [57] attached a tag, which can be computed by the client to form a particular query F(pk, x1), and by the server from a ciphertext that encrypts it G(pk, c) with a plaintext. Although the scheme was adjudged to be secure, it was left without solution to the problem of finding a standard model scheme approach, and the scheme only provided privacy to text drawn from a space of large min-entropy. A modified lightweight algorithm based on Somewhat Homomorphic Encryption-Ring Learning with Error was proposed by [58]. The new technique was presented as an approach to securely encrypt IoT sensor signal value based on the frequency of transmitting the signal to the edge environment. The proposed work provides a secure key that the patient can only authorize to decrypt the original raw data from the sensor attached to the patient. A summary of the related works is given in Table 1. From the review works, it is clear that the existing IoMT models are suffering from deficiency ranging from vulnerability to security attacks to a lack of privacy preservation of data and a high demand of memory and computation complexity. Evidently, an IoMT model that is less computationally and memory-intensive, which is capable of handling security and privacy issues when information is kept on the cloud, is a desirable project.