# Secure NIfTI Image Authentication Scheme for Modern Healthcare System
###### Abstract
Encryption can help protect the watermark itself, as it can make it more difficult for attackers to detect and remove the watermark from the image. This can improve the overall robustness and reliability of the watermarking technique, making it more effective for a wide range of applications. Various medical image watermarking encryption techniques have been developed to secure the image via internet communication [7; 8; 9]. The two primary classifications utilized to categorize watermarking systems are the transform and spatial domains. The bits of the watermark are incorporated directly into the processes of spatial domain watermarking [10]. However, to begin the process of transforming domain watermarking, the host image must first be transformed into the frequency domain utilizing a number of different wavelet transformations, such as DCT, DFT, and DWT. Because robustness is the primary challenge that all digital watermarking techniques face, transform domain methods are more reliable than spatial domain schemes [11; 12]. As a consequence of this, the LWT is implemented in the proposed watermarking system. The majority of researchers have suggested watermarking techniques for medical images in the file formats.jpg,.png,.tiff, and.bmp [13; 14], and some have devised watermarking systems for DICOM images (.dcm file extension). Various pioneering medical imaging technologies have been developed in the current medical system. These technologies produce images in the NIfTI format (with an extension of. nii), as opposed to.bmp,.jpg, or DICOM (.dcm file extension). NIfTI images are produced when a lung CT scan is performed on a patient. These images contain extremely sensitive medical data regarding the lungs and are presented in a number of slices. Consequently, the medical system on a global scale requires a reliable watermarking mechanism to validate NIFTI images in advance of diagnosis. Suppose that the watermarking scheme successfully authenticates the medical image (successfully extracting the watermark before starting the diagnosis). In such a scenario, the radiologist will have to decide whether or not to proceed with the diagnosis. Thus, radiologists try to avoid squandering their valuable time on inaccurate medical images for diagnosis. This is accomplished by using the proposed watermarkingmethod, which could be used in the COVID-19 epidemic to certify these images for proper diagnosis. We first need to identify the appropriate slice from the NIfTI image to begin with this method. Generally, some first and last slices of each NIfTI image contain less medical information, so we select one slice from these slices for watermark insertion. This research is a hybrid watermarking method for NIfTI images that employs the SLT, LWT, and Arnold Cat Map. The proposed scheme is resistant to numerous noise assaults. The following are some of the significant contributions that the proposed watermarking scheme has made:  
* A unique watermarking approach for NIfTI images was developed, using LWT, SLT, and BSVD. The combination of LWT and SLT gave more robustness than previous methods. * The bit error rate was improved by SLT, resulting in a higher percentage of the original energy in the image or signal after compression. * LL sub-bands have the maximum energy of the signal, so watermark bits were added to the LL sub-band. The combination of SLT and LWT provides more security from several attacks. * To improve the watermark's level of security, the ACM was utilized to jumble the watermark. The remaining parts of this paper are divided into the following sections: The methods of image watermarking that are considered to be state of the art are discussed in Section 2; in Section 3, we discuss an overview of the theories that were used in the proposed scheme; in Section 4, we discuss the proposed approach of watermark embedding and extraction process; in Section 5, we conduct simulations and assess the simulation result; and in Section 6, we conclude the study.