# Secure NIfTI Image Authentication Scheme for Modern Healthcare System
###### Abstract  
Advances in digital neuroimaging technologies, i.e., MRI and CT scan technology, have radically changed illness diagnosis in the global healthcare system. Digital imaging technologies produce NIfTI images after scanning the patient's body. COVID-19 spared on a worldwide effort to detect the lung infection. CT scans have been performed on billions of COVID-19 patients in recent years, resulting in a massive amount of NIfTI images being produced and communicated over the internet for diagnosis. The dissemination of these medical photographs over the internet has resulted in a significant problem for the healthcare system to maintain its integrity, protect its intellectual property rights, and address other ethical considerations. Another significant issue is how radiologists recognize tempered medical images, sometimes leading to the wrong diagnosis. Thus, the healthcare system requires a robust and reliable watermarking method for these images. Several image watermarking approaches for jpg,.dcm,.png,.bmp, and other image formats have been developed, but no substantial contribution to NIfTI images (.nii format) has been made. This research suggests a hybrid watermarking method for NIfTI images that employs Slantlet Transform (SLT), Lifting Wavelet Transform (LWT), and Arnold Cat Map. The suggested technique performed well against various attacks. Compared to earlier approaches, the results show that this method is more robust and invisible. NIfTI; watermarking; medical image; slantlet transform (SLT); lifting wavelet transform (LWT); Arnold cat map 2023  
2023/13/5308/10/05/2023/13/5308/10/0  
filmless because of expensive printing and transmission expenses. When a patient seeks advice from a doctor, it is beneficial to them [2]. COVID-19 has spread worldwide in recent years, negatively affecting the social lives of billions of people, posing a challenge for researchers to discover a solution by applying medical imaging technology to identify and estimate COVID-19's effect on the lungs. In the present COVID-19 scenario, hospitals have extensive patient data generated through these medical imaging technologies, such as CT scan and MRI image data from patients, communicated through the internet. It is now a frequent practice for various reasons, such as diagnosis, medical consultation, treatment, and remote learning purposes. The communication of these images has been increased recently, but the communication channel is not sufficiently secure. Radiologists and doctors do not take these problems seriously. Therefore, it might be purposefully or unintentionally distorted during the development or transmission of medical images, resulting in catastrophic consequences for patient diagnosis [3]. Therefore, the main concern is the security and authenticity of these medical imaging data from malicious individuals. Thus, the healthcare system requires a solution that addresses this issue of medical images in an unsecured communication network. Watermarking often confirms the image's validity and integrity [4; 5]. It is a method that inserts some information in the form of a watermark into the host image without affecting anything about the image, such as the image format or size [6]. If it becomes essential in the future, it will be possible to successfully recover this watermark from the image in order to verify its legitimacy. Faith is lost in the image's legitimacy if any medical image undergoes excessive modification during the watermarking process, and it must hamper the patient's diagnosis. A minor modification in the picture might lead to misdiagnosis, leading to disastrous consequences and legal ramifications. When developing a watermarking scheme for a medical image, remember that it must be reliable and not excessively degrade the image quality. The use of image encryption in watermarking can provide a powerful combination of security and authenticity, making it an essential technique for protecting and managing digital image data.