SLT based watermarking system for secure telemedicine

Eswaraiah, R.; Tirumalasetty, Sudhir; Prathipati, Silpa Chaitanya

doi:10.1007/s10586-020-03078-2

Cited by 22 publications

(16 citation statements)

References 16 publications

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“…Rayachoti et al [24] presented a watermarking approach using the Slantlet transform (SLT) and SVD. They began by dividing the entire image into ROI and NROI and selecting the NROI for watermark placement.…”

Section: Literature Reviewmentioning

confidence: 99%

Secure NIfTI Image Authentication Scheme for Modern Healthcare System

et al. 2023

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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.

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Section: Literature Reviewmentioning

confidence: 99%

Secure NIfTI Image Authentication Scheme for Modern Healthcare System

et al. 2023

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“…According to the National Laboratories WHO scientific guidelines, real-time polymerase chain reaction (RT-PCR) testing is the gold standard for validating the diagnosis of COVID-19. However, the RT-PCR test became inadequate, and showed high levels of false-negative results to confirm cases that were positive for COVID-19 [ 1 – 5 ]. In addition RT-PCR is a very time-consuming, complex manual process, and kits are currently lacking.…”

Section: Introductionmentioning

confidence: 99%

Time Efficient Image Encryption-Decryption for Visible and COVID-19 X-ray Images Using Modified Chaos-Based Logistic Map

Bhattacharjee

Gupta

Chatterjee

2022

Appl Biochem Biotechnol

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In this pandemic situation, radiological images are the biggest source of information in healthcare and, at the same time, one of the foremost troublesome sources to analyze. Clinicians now-a-days must depend to a great extent on therapeutic image investigation performed by exhausted radiologists and some of the time analyzed and filtered themselves. Due to an overflow of patients, transmission of these medical data becomes frequent and maintaining confidentiality turns out to be one of the most important aspects of security along with integrity and availability. Chaos-based cryptography has proven a useful technique in the process of medical image encryption. The specialty of using chaotic maps in image security is its capability to increase the unpredictability and this causes the encryption robust. There are large number of literature available with chaotic map; however, most of these are not useful in low-precision devices due to their time-consuming nature. Taking into consideration of all these facts, a modified encryption technique is proposed for 2D COVID-19 images without compromising security. The novelty of the encryption procedure lies in the proposed design which is split into mainly three parts. In the first part, a variable length gray level code is used to generate the secret key to confuse the intruder and subsequently it is used as the initial parameter of both the chaotic maps. In the second part, one-stage image pixels are shuffled using the address code obtained from the sorting transformation of the first logistic map. In the final stage, a complete diffusion is applied for the whole image using the second chaotic map to counter differential and statistical attack. Algorithm validation is done by experimentation with visual image and COVID-19 X-ray images. In addition, a quantitative analysis is carried out to ensure a negligible data loss between the original and the decrypted image. The strength of the proposed method is tested by calculating the various security parameters like correlation coefficient, NPCR, UACI, and key sensitivity. Comparison analysis shows the effectiveness for the proposed method. Implementation statistics shows time efficiency and proves more security with better unpredictability.

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“…X-ray, MRI, CT-scan, and ultrasound images are all examples of diagnostic procedures that routinely make use of digital imaging technology. De-noising [4], segmenting [5], and compressing [6] medical images such that textures [7] may be extracted. Therefore, these medical images are widely disseminated [8], [9], [10] both within the hospital intranet and online.…”

Section: Introductionmentioning

confidence: 99%

ROI-Fuzzy Based Medical Data Authentication Scheme for Smart Healthcare System

et al. 2022

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During the current pandemic, telemedicine applications encourage radiologists to consult patients remotely. Medical images are typically sent over the internet for easy access when diagnosing a patient. Intruders can manipulate these images during communication. Therefore, we require a method of authentication for these images that is capable of authenticating these images before diagnosis. To address these issues, a watermarking scheme has been developed within the scope of this paper. The foundation of anticipated watermarking system is Regions of Interest (ROI), using FRT to RONI, and converted into blocks; afterward, Hessenberg decomposition is applied on blocks selected by means of fuzzy logic. The binary watermark is quantized into the medical image. It has made the watermarking system non-fragil and secure.The proposed scheme's performance is evaluated on various attack situations, including noise and scale assaults. Watermarked pictures with enhanced PSNR ranging from 56.9902 to 57.2356 have been produced using the proposed technique. In particular, we achieved high NC values of 0.9801 on applying image processing attacks. A series of tests are performed on the system to determine its sensitivity, and the results are compared to protocols. The simulation results demonstrate that the suggested solution offers a high level of security while being imperceptible and robust to various attacks.

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SLT based watermarking system for secure telemedicine

Cited by 22 publications

References 16 publications

Secure NIfTI Image Authentication Scheme for Modern Healthcare System

Secure NIfTI Image Authentication Scheme for Modern Healthcare System

Time Efficient Image Encryption-Decryption for Visible and COVID-19 X-ray Images Using Modified Chaos-Based Logistic Map

ROI-Fuzzy Based Medical Data Authentication Scheme for Smart Healthcare System

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