A Blind Medical Image Watermarking for Secure E-Healthcare Application Using Crypto-Watermarking System

2019 ◽  
Vol 29 (1) ◽  
pp. 1558-1575
Author(s):  
Puvvadi Aparna ◽  
Polurie Venkata Vijay Kishore

Abstract A reliable medical image management must provide proper security for patient information. Protecting the medical information of the patients is a major concern in all hospitals. Digital watermarking is a procedure prevalently used to secure the confidentiality of medical information and maintain them, which upgrades patient health awareness. To protect the medical information, the robust and lossless patient medical information sharing system using crypto-watermarking method is proposed. The proposed system consists of two phases: (i) embedding and (ii) extraction. In this paper, we securely share three types of patient information, medical image, electronic health record (EHR), and face image from one hospital to another hospital. Initially, all the three inputs are encrypted and the information is concordant. In order to enhance the robustness of the crypto-watermarking system, the obtained bit stream is compressed, and the compressed bit streams are embedded into the cover image. The same process is repeated for the extraction process. The experimentation result is carried out using different medical images with EHR, and the effectiveness of the proposed algorithm is analyzed with the help of peak signal to noise ratio.

2018 ◽  
Vol 27 (1) ◽  
pp. 115-133 ◽  
Author(s):  
Puvvadi Aparna ◽  
Polurie Venkata Vijay Kishore

Abstract The main objective of this paper is to propose a medical image watermarking technique in E-healthcare application based on the hybridization of compression and cryptography algorithm. Basically, the proposed system consists of two stages: (i) watermark embedding process and (ii) watermark extraction process. In the embedding process, at first, we segment the tumor part separately using a region growing algorithm. Then, we encrypt the region of interest part using Secure Hash Algorithm-256 and encrypt the electronic health record (EHR) using the elliptical curve cryptography algorithm. Thereafter, we concatenate and compress the information using an arithmetic coding algorithm. Finally, we embed the compressed bit into the original image. The same process is repeated for the extraction process. The experimental results are shown for different medical images with EHR and the effectiveness of the proposed algorithm is analyzed with the help of the peak signal-to-noise ratio and normalized correlation.


2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Sondes Ajili ◽  
Mohamed Ali Hajjaji ◽  
Abdellatif Mtibaa

We propose a novel method for medical image watermarking in the DCT domain using the AES encryption algorithm. First, we decompose the original medical image into subblocks of 8 × 8. Besides, we apply the DCT and the quantization, respectively, to each subblock. However, in the DCT domain, an adequate choice of the DCT coefficients according to the quantization table in the middle frequencies band is performed. After that, we embed the patient’s data into the corresponding medical image. The insertion step is carried out just after the quantization phase. To increase the robustness, we encrypt the watermarked medical images by using the AES algorithm based on chaotic technique. Arnold’s cat map is used to shuffle the pixel values, and a chaotic Henon map is utilized to generate an aleatory sequence for the AES algorithm. The shuffled watermarked image is encrypted using the modified AES algorithm. The constant of Weber is used to choose the suitable visibility factor for embedding a watermark with high robustness. To control identification, after application of attacks, we use the serial turbo code for correction of the watermark to recover the data inserted. The average peak signal-to-noise ratio (PSNR) of the medical images obtained is 61,7769 dB. Experimental results demonstrate the robustness of the proposed schema against various types of attacks.


Author(s):  
Oladotun O. Okediran

Advances in computing and communication technologies have provided new methods to store and access medical data electronically and distribute them over open communication networks. Today, patients themselves can access their medical information themselves and medical information can be transmitted among medical institutions as well as stakeholders in the health sector.  Accompanying these benefits are concomitant risks for patient medical records in electronic formats and strictly personal medical documentations being transmitted and accessible over open communication channels such as the Internet. Thus it is common knowledge that there should be in place network-level security measures and protocols in medical information systems. Many security schemes that were based on cryptography, watermarking and steganography have been proposed and implemented to secure medical data. However, an apt review of relevant literature revealed that in many implementations robustness against attacks is not guaranteed. Issues bordering on low embedding capacity, low robustness, low imperceptibility and bad trade tradeoff between robustness and capacity are evident in many implementations. In this paper, a hybrid Rivest-Shamir-Adleman (RSA) algorithm, Rivest Cipher 4 (RC4) algorithm and Spread Spectrum techniques were proposed for securing medical image data over open communication networks. The performance of the proposed scheme was evaluated using Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Mean Square Error (MSE) and Bit Error Rate (BER). For the five sample medical images used to test the scheme, the BER value is zero while the PNSR and SNR are consistent and they returned desirable high values. The MSE values for the images were low. The average values of the PSNR, SNR and MSE are 51.88 dB, 43.38 dB and 0.113 respectively. Hence, the proposed scheme is utterly revertible, robust and highly imperceptible; the original images can be retrieved by the recipient without any deformation or alteration.


2018 ◽  
Vol 7 (3.12) ◽  
pp. 711
Author(s):  
S Priya ◽  
B Santhi ◽  
J Raja Mohan

In telemedicine, medical data are shared across the world among different specialists for various purposes through an unsecured medium. So there is a need to protect the medical data during transmission. With the help of image watermarking techniques, medical images are protected along with the electronic patient information (EPI). This paper proposes a medical image watermarking, by applying wavelet transform, using an interpolation technique. EPI data is embedded within the transformed medical image to generate a watermarked image. At the extraction side, EPI data are extracted and medical image is reconstructed without any loss. The performance of the proposed method is analyzed using a peak signal to noise ratio (PSNR), mean absolute error (MAE) and structural similarity index (SSIM).   The experimental result shows that the proposed method gives better results.


Author(s):  
M. N. Favorskaya ◽  
E. I. Savchina

Medical Image Watermarking (MIW) is a special field of a watermarking due to the requirements of the Digital Imaging and COmmunications in Medicine (DICOM) standard since 1993. All 20 parts of the DICOM standard are revised periodically. The main idea of the MIW is to embed various types of information including the doctor’s digital signature, fragile watermark, electronic patient record, and main watermark in a view of region of interest for the doctor into the host medical image. These four types of information are represented in different forms; some of them are encrypted according to the DICOM requirements. However, all types of information ought to be resulted into the generalized binary stream for embedding. The generalized binary stream may have a huge volume. Therefore, not all watermarking methods can be applied successfully. Recently, the digital shearlet transform had been introduced as a rigorous mathematical framework for the geometric representation of multi-dimensional data. Some modifications of the shearlet transform, particularly the non-subsampled shearlet transform, can be associated to a multi-resolution analysis that provides a fully shift-invariant, multi-scale, and multi-directional expansion. During experiments, a quality of the extracted watermarks under the JPEG compression and typical internet attacks was estimated using several metrics, including the peak signal to noise ratio, structural similarity index measure, and bit error rate.


2018 ◽  
Vol 7 (3.12) ◽  
pp. 1281
Author(s):  
Srinivasarao Gajula ◽  
Rajesh V

In order to get clear information regarding patient it is necessary to enhance medical images like MRI, CT scan, ultrasound etc.  For clinical diagnosis, we have to transmit it through the communication network. During this process information must be protected from malicious users. In this process these images are manipulated, so to protect these images we have to follow some security requirements. In this paper, we are increasing the quality of the image by using enhancement with clahe technique and that enhanced image is watermarked for security purpose by using DWT, SVD transforms with a scaling factor as uniform distribution function. The performance evaluation parameters will give better results for medical as well as under water images. The obtained results are very helpful for integrity of medical images. The technique will provide better response for medical images. This method will give good results in terms of improvement in output, Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE).  


2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Shaozhang Xiao ◽  
Zhengwei Zhang ◽  
Yue Zhang ◽  
Changhui Yu

Considering the existing medical image watermarking algorithms, a single function often has limitations, and a multipurpose watermarking algorithm for medical images is proposed. First, medical images are divided into regions of interest (ROIs) and regions of noninterest (RONIs). Then, the authentication watermark produced for each subblock of the ROI is embedded into the corresponding mapping subblock. The visible watermark is embedded into the RONI, and, finally, the watermark information and constructed authentication information in each subblock of the ROI are embedded into the corresponding RONI subblock. Simulation results show that the embedded visible watermark can protect and facilitate medical image management. In addition, the proposed algorithm has strong robustness and very good visual quality. It can simultaneously realize copyright protection and content authentication and also has high tamper localization capability.


Author(s):  
B. Ananthapraba ◽  
K. Thyagarajan

The amount of digital medical images has increased rapidly in the Internet. The necessity of fast and secure diagnosis is vital in the medical world. Nowadays, the transmission of images is a daily routine and it is necessary to find an efficient way to transmit them over the net. In this project we propose a new technique to cipher an image for safe and denoised transmission. The existing research deals with image cryptography, data hiding and steganography. There are several methods to encrypt binary or grey level images. Watermarking can be an answer to make secure image transmission. For applications dealing with images, the watermarking objective is to embed invisibly message inside the image. To embed the encrypted image in the patient information we have used watermarking technique. In this project, we concentrate to solve the privacy violation problem occurred when images are published on the medical applications without the permission. According to such images are always shared after uploading process. Therefore, the digital image watermarking based on DWT co-efficient. Watermark bits are embedded in uploaded images. Watermarked images are shared in user home page. So images can be difficult to misuse by other persons. In receiver side when the message is arrived then we apply the inverse methods in reverse order to get the original image and patient information and to remove watermark we extract the image before the decryption of message. We have applied and showed the results of our method to medical images.


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