scholarly journals A secure cloud system for maintaining COVID-19 patient's data using image steganography

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Nandhini Subramanian ◽  
Somaya Al-Maadeed
Keyword(s):  
Deep Learning ◽  
Image Steganography ◽  
Cover Image ◽  
Main Concern ◽  
Stego Image ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Private Patient ◽  
Hiding Capacity ◽  
Smart Healthcare

Background: The COVID-19 pandemic has been life-threatening for many people and as such, a contactless medical system is necessary to prevent the spread of the virus. Smart healthcare systems collect data from patients at one end and process the acquired data at the other end. The cloud is the central point and the communication happens through insecure channels. The main concern, in this case, is the violation of privacy and security as the channel is untrusted. Traditional methods do not provide enough hiding capacity, security, and robustness. This work proposes an image steganography method using the deep learning method to hide the patient's medical images inside an innocent cover image in such a way that they are not visible to human eyes which reduces the suspicions of the presence of sensitive data. Methods: An auto encoder-decoder-based model is proposed with three components: the pre-processing module, the embedding network, and the extraction network. Features from the cover image and the secret images are extracted and fused to reconstruct the stego image. The stego image is then used to extract the ingrained secret image.shows the overall system workflow. Results: Peak Signal-to-Noise Ratio (PSNR) is the evaluation metrics used. The ImageNet dataset was used for training and testing the proposed model.shows the image results of the proposed method. Conclusion: During a COVID-19 screening test, private patient data such as mobile number and Qatari identity card are collected, transferred, and stored through untrusted channels. It is of paramount importance to preserve the privacy, security, and confidentiality of the collected patient records. A secure deep learning-based image steganography method is proposed to secure the sensitive data transferred through untrusted channels in a cloud-based system.

scholarly journals Stego-eHealth: An eHealth System for Secured Transfer of Medical Images using Image Steganography

2021 ◽  
Author(s):  
Nandhini Subramanian ◽  
, Jayakanth Kunhoth ◽  
Somaya Al-Maadeed ◽  
Ahmed Bouridane
Keyword(s):  
Medical Information ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Health Care Systems ◽  
Image Steganography ◽  
Cover Image ◽  
Stego Image ◽  
Hiding Capacity ◽  
Secret Image ◽  
Care Systems

COVID pandemic has necessitated the need for virtual and online health care systems to avoid contacts. The transfer of sensitive medical information including the chest and lung X-ray happens through untrusted channels making it prone to many possible attacks. This paper aims to secure the medical data of the patients using image steganography when transferring through untrusted channels. A deep learning method with three parts is proposed – preprocessing module, embedding network and the extraction network. Features from the cover image and the secret image are extracted by the preprocessing module. The merged features from the preprocessing module are used to output the stego image by the embedding network. The stego image is given as the input to the extraction network to extract the ingrained secret image. Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) are the evaluation metrics used. Higher PSNR value proves the higher security; robustness of the method and the image results show the higher imperceptibility. The hiding capacity of the proposed method is 100% since the cover image and the secret image are of the same size.

scholarly journals A Juxtaposition Between Integer Wavelet Transform and Discrete Wavelet Transform for Secure Image Steganography

2020 ◽  
Vol 9 (5) ◽  
pp. 1019-1023
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Integer Wavelet Transform ◽  
Stego Image ◽  
Hiding Capacity ◽  
Integer Wavelet

Image steganography is a technique that is used to hide information. The information can be of various types like image, video, or audio. Steganography is done so that no one apart from the correct receiver can retrieve the information. This paper consists of all advantages and highlights of the wavelet transform but with the additional features like randomness and some default values that are already built-in it. Various algorithms can be used in steganography and they provide good hiding capacity and low detectability. Here we have hidden the image into the cover image using Integer Wavelet Transform (IWT) and also using Discrete Wavelet Transform (DWT) and compared which technique gives better results. It is very difficult to predict the presence of a hidden image inside the stego image since it looks exactly like the cover image. There is no loss in quality from the secret image to the extracted image since the PSNR (Peak Signal to noise ratio) is high for both of them. This process was done using both DWT and IWT and the results prove that that the IWT technique is not only simpler but also more efficient than the DWT technique since it gives higher PSNR values. Through the proposed algorithm, an increase in the strength and imperceptibility is noticed and it can also maintain various transformations such as scaling, translation, and rotation with algorithms that already exist. The final results, after comparing both the transforms prove that the algorithm which is being proposed in IWT is indeed effective

scholarly journals High-Capacity Image Steganography Algorithm Based on Image Style Transfer

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xinliang Bi ◽  
Xiaoyuan Yang ◽  
Chao Wang ◽  
Jia Liu
Keyword(s):  
High Capacity ◽  
Image Features ◽  
Image Steganography ◽  
Cover Image ◽  
Secret Message ◽  
The Internet ◽  
Stego Image ◽  
Style Transfer ◽  
Secret Image ◽  
Secret Information

Steganography is a technique for publicly transmitting secret information through a cover. Most of the existing steganography algorithms are based on modifying the cover image, generating a stego image that is very similar to the cover image but has different pixel values, or establishing a mapping relationship between the stego image and the secret message. Attackers will discover the existence of secret communications from these modifications or differences. In order to solve this problem, we propose a steganography algorithm ISTNet based on image style transfer, which can convert a cover image into another stego image with a completely different style. We have improved the decoder so that the secret image features can be fused with style features in a variety of sizes to improve the accuracy of secret image extraction. The algorithm has the functions of image steganography and image style transfer at the same time, and the images it generates are both stego images and stylized images. Attackers will pay more attention to the style transfer side of the algorithm, but it is difficult to find the steganography side. Experiments show that our algorithm effectively increases the steganography capacity from 0.06 bpp to 8 bpp, and the generated stylized images are not significantly different from the stylized images on the Internet.

scholarly journals Image Steganography Using Pixel Value Differencing (PVD) Technique Based on Firefly Algorithm

2021 ◽  
pp. 80-86
Author(s):  
Oluwaseun M. Alade ◽  
Elizabeth A. Amusan ◽  
Oluyinka T. Adedeji ◽  
Oluwaseun O. Alo
Keyword(s):  
Firefly Algorithm ◽  
Promising Result ◽  
Signal To Noise Ratio ◽  
Text Message ◽  
Image Steganography ◽  
Cover Image ◽  
Experimental Result ◽  
Stego Image ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography deals with the ways of hiding communicated data in such a way that it remains confidential. Finding best position inside cover image to embed text message, maintaining a reasonable trade-off between security, robustness, higher bit embedding rate and imperceptibility are some of the challenges of steganography system. Hence, this paper presents firefly algorithm for finding best positions inside cover image in order to embed text message into cover image using Pixel Value Differencing (PVD) technique. Four different cover image was used. Experimental result showed the cover image with selected location using firefly algorithm as well as the stego image using PVD technique. The stego image was evaluated using Peak Signal to Noise Ratio (PSNR) and Mean square Error (MSE).  Firefly Algorithm with PVD technique produced a promising result for image steganography.

scholarly journals Coverless Image Steganography Based on Generative Adversarial Network

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1394 ◽  
Author(s):  
Jiaohua Qin ◽  
Jing Wang ◽  
Yun Tan ◽  
Huajun Huang ◽  
Xuyu Xiang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Poor Quality ◽  
Image Steganography ◽  
Cover Image ◽  
Secret Message ◽  
Generative Adversarial Network ◽  
Learning Framework ◽  
Adversarial Network ◽  
Traditional Image

Traditional image steganography needs to modify or be embedded into the cover image for transmitting secret messages. However, the distortion of the cover image can be easily detected by steganalysis tools which lead the leakage of the secret message. So coverless steganography has become a topic of research in recent years, which has the advantage of hiding secret messages without modification. But current coverless steganography still has problems such as low capacity and poor quality .To solve these problems, we use a generative adversarial network (GAN), an effective deep learning framework, to encode secret messages into the cover image and optimize the quality of the steganographic image by adversaring. Experiments show that our model not only achieves a payload of 2.36 bits per pixel, but also successfully escapes the detection of steganalysis tools.

scholarly journals Reversible difference expansion multi-layer data hiding technique for medical images

2021 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Pascal Maniriho ◽  
Leki Jovial Mahoro ◽  
Zephanie Bizimana ◽  
Ephrem Niyigaba ◽  
Tohari Ahmad
Keyword(s):  
Data Hiding ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Data Communication ◽  
Low Complexity ◽  
Difference Expansion ◽  
Stego Image ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Private Data

Maintaining the privacy and security of confidential information in data communication has always been a major concern. It is because the advancement of information technology is likely to be followed by an increase in cybercrime, such as illegal access to sensitive data. Several techniques were proposed to overcome that issue, for example, by hiding data in digital images. Reversible data hiding is an excellent approach for concealing private data due to its ability to be applied in various fields. However, it yields a limited payload and the quality of the image holding data (Stego image), and consequently, these two factors may not be addressed simultaneously. This paper addresses this problem by introducing a new non-complexity difference expansion (DE) and block-based reversible multi-layer data hiding technique constructed by exploring DE. Sensitive data are embedded into the difference values calculated between the original pixels in each block with relatively low complexity. To improve the payload capacity, confidential data are embedded in multiple layers of grayscale medical images while preserving their quality. The experiment results prove that the proposed technique has increased the payload with an average of 369999 bits and kept the peak signal to noise ratio (PSNR) to the average of 36.506 dB using medical images' adequate security the embedded private data. This proposed method has improved the performance, especially the secret size, without reducing much the quality. Therefore, it is suitable to use for relatively big payloads.

scholarly journals A new encrypted method in image steganography

2019 ◽  
Vol 14 (3) ◽  
pp. 1412 ◽  
Author(s):  
Sabyasachi Pramanik ◽  
R P Singh ◽  
Ramkrishna Ghosh
Keyword(s):  
Data Hiding ◽  
Image Steganography ◽  
Cover Image ◽  
Human Response ◽  
Stego Image ◽  
Response Test ◽  
Confidential Data

<p>Steganography is data hiding technique in internet. Here we send CAPTCHA codes within a cover image using Image steganography. CAPTCHA are the crazy codes. They are used in human response test. The word is actually an acronym for: "<strong>C</strong>ompletely <strong>A</strong>utomated <strong>P</strong>ublic <strong>T</strong>uring test to tell <strong>C</strong>omputers and <strong>H</strong>umans <strong>A</strong>part". It is a type of challenge–response test used in computing to determine whether or not the user is a human. Websites implement CAPTCHA codes into their registration processes due to spam. This is the utility of CAPTCHA codes. Here we generate CAPTCHA codes and later send them in an encrypted version. So, actually CAPTCHA codes are embedded into cover image with an encrypted form resulting stego image and thus attackers cannot fetch the actual CAPTCHA resulting in a secured transmission of confidential data using image steganography.</p>

scholarly journals Nested Two-Layer RGB Based Reversible Image Steganography Method

2021 ◽  
Vol 50 (2) ◽  
pp. 264-283
Author(s):  
Ali Durdu
Keyword(s):  
Secure Communication ◽  
Signal To Noise Ratio ◽  
Quality Criterion ◽  
Image Steganography ◽  
Cover Image ◽  
Signal To Noise ◽  
Chi Square ◽  
Hiding Capacity ◽  
Communication Environment ◽  
Steganalysis Method

In this study, a new reversible image steganography method based on Red-Green-Blue (RGB) which hides thecolored image into the colored images in two layers nested is proposed. The proposed method hides the 24-bitimage to be hidden by hiding two layers of data firstly in the resized version of the cover image with the LSBmethod, and then hides the resized cover image to the original cover image with the 4-bit method. The proposedmethod offers a secure communication environment as it hides the hidden image in two layers. When thirdparties extract data by using the LSB method, they only access the resized version of the cover image. The 4-bitmethod divides the image to be hidden into 8-bit segments. While the first 4 bits, which are the most importantbits of 8-bit data, are hidden directly, 4 bits that can be neglected with less significance are completed by roundingat approximate value through the method function. In this way, since the 8-bit data is reduced to 4-bits, themethod performs lossy hiding, but doubles the hiding capacity. Peak signal to noise ratio (PSNR), structuralsimilarity quality criterion (SSIM) and chi-square steganalysis method, which are frequently used in the literature,are used to measure the immunity level of the proposed method. When it is concealed at the same ratewith the LSB method and the proposed method, a higher measurement value is obtained in the PSNR imagecriterion, which is 1.2 dB, SSIM 0.0025, BER 0.0129 and NCC image criterion 0.00027. In additional, it wasshown that the proposed method achieved more successful results in chi-square steganalysis and histogramtests compared to the traditional LSB method.

scholarly journals Image Steganography using Improved Lsb-Mapping Technique with Enhanced Recovery Speed

2019 ◽  
Vol 8 (4) ◽  
pp. 11473-11478
Keyword(s):  
Data Hiding ◽  
Enhanced Recovery ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Cover Image ◽  
Mapping Technique ◽  
Secret Data ◽  
Logical Function ◽  
Hiding Capacity ◽  
Carrier Image

In recent days, for sending secret messages, we require secure internet. Image steganography is considered as the eminent tool for data hiding which provides better security for the data transmitted over internet. In the proposed work, the payload data is embedded using improved LSB-mapping technique. In this approach, two bits from each pixel of carrier image are considered for mapping and addition. Two bits of payload data can be embedded in one cover image pixel hence enhanced the hiding capacity. A logical function on addition is applied on 1st and 2nd bits of cover image pixel, and a mapping table is constructed which gives solution for data hiding and extraction. Simple addition function on stego pixel is performed to extract payload data hence increases the recovery speed. Here the secret data is not directly embedded but instead mapped and added with a number using modulo-4 strategy. Hence the payload data hidden using proposed approach provide more security and it can resist against regular LSB decoding approaches. The proposed work is implemented and tested for several gray scale as well as color images and compared with respect to parameters like peak signal to noise ratio and MSE. The proposed technique gives better results when compared and histogram of cover and stego images are also compared.

Image Steganography Using DWT and Semi Hexadecimal Code Based on PSNR

2018 ◽  
Vol 6 (8) ◽  
pp. 230
Author(s):  
Balkar Singh
Keyword(s):  
Visual Quality ◽  
Threshold Value ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Secret Data ◽  
Stego Image ◽  
Pixel Value ◽  
Better Than

In this paper, a novel image steganography approach is proposed to enhance the visual quality of stego image. The cover image is decomposed using Discrete Wavelet Transform (DWT) to produce wavelet subbands and threshold value is calculated for each higher frequency wavelet subbands. Wavelet coefficients having magnitude larger than the threshold of its subband are selected to embed the secret data. Semi Hexadecimal Code (SHC) is proposed to convert pixel value of secret image into smaller equivalent value so that it distorts stego image as less as possible. Experimental results shows that maximum PSNR between cover image and stego image is more than 75 dB .Proposed approach is also compared with the existing approaches and this comparison shows that the proposed approach is better than the existing approaches. 

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