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 Knight Tour for Image Steganography Technique

2019 ◽  
Vol 9 (1) ◽  
pp. 1610-1613
Keyword(s):  
Growth Rate ◽  
Data Hiding ◽  
Information Hiding ◽  
High Capacity ◽  
Image Steganography ◽  
Cover Image ◽  
The Internet ◽  
Sensitive Information ◽  
Image File ◽  
Ascii Code

The growth rate of the Internet is exceeding that of any previous technology. As the Internet has become the major medium for transferring sensitive information, the security of the transferred message has now become the utmost priority. To ensure the security of the transmitted data, Image steganography has emerged out as an eminent tool of information hiding. The frequency of availability of image file is high and provides high capacity. In this paper, a method of secure data hiding in image is proposed that uses knight tour positions and further 8-queen positions in 8*8 pixel blocks.The cover image is divided into 8*8 pixel blocks and pixels are selected from each block corresponding to the positions of Knight in 8*8 chessboard starting from different pixel positions. 8-pixel values are selected from alternate knight position. Selected pixels values converted to 8-bit ASCII code and result in 8* 8 bit matrix. 8-Queen’s solution on 8*8 chessboard is applied on 8*8 bit matrix. The bits selected from 8-Queens positions and compared with 8-bit ASCII code of message characters. The proposed algorithm changes the LSB of only some of the pixels based on the above comparison. Based on parameters like PSNR and MSE the efficiency of the method is checked after implementation. Then the comparison done with some already proposed techniques. This is how, image steganography showed interesting and promising results when compared with other techniques.

Secure Data Transfer Using Image Steganography

2021 ◽  
Vol 9 (VIII) ◽  
pp. 175-180
Author(s):  
Nisha Manral
Keyword(s):  
Data Transfer ◽  
Digital Images ◽  
Image Steganography ◽  
Secret Message ◽  
The Internet ◽  
Secret Information ◽  
File Formats ◽  
Secure Data ◽  
Other Information ◽  
Weak Points

Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the Internet. For hiding secret information in images, there exists a large variety of steganographic techniques some are more complex than others and all of them have respective strong and weak points. Different applications have different requirements of the steganography technique used. For example, some applications may require absolute invisibility of the secret information, while others require a larger secret message to be hidden. This paper intends to give an overview of image steganography, its uses and techniques. It also attempts to identify the requirements of a good steganographic algorithm and briefly reflects on which steganographic techniques are more suitable for which applications.

scholarly journals High-Capacity Image Steganography Based on Improved Xception

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7253
Author(s):  
Xintao Duan ◽  
Mengxiao Gou ◽  
Nao Liu ◽  
Wenxin Wang ◽  
Chuan Qin
Keyword(s):  
Network Architecture ◽  
Signal To Noise Ratio ◽  
Load Capacity ◽  
High Capacity ◽  
Structural Similarity ◽  
Image Steganography ◽  
Cover Image ◽  
Secret Image ◽  
Multi Scale ◽  
High Load Capacity

The traditional cover modification steganography method only has low steganography ability. We propose a steganography method based on the convolutional neural network architecture (Xception) of deep separable convolutional layers in order to solve this problem. The Xception architecture is used for image steganography for the first time, which not only increases the width of the network, but also improves the adaptability of network expansion, and adds different receiving fields to carry out multi-scale information in it. By introducing jump connections, we solved the problems of gradient dissipation and gradient descent in the Xception architecture. After cascading the secret image and the mask image, high-quality images can be reconstructed through the network, which greatly improves the speed of steganography. When hiding, only the secret image and the cover image are cascaded, and then the secret image can be embedded in the cover image through the hidden network in order to obtain the secret image. After extraction, the secret image can be reconstructed by bypassing the secret image through the extraction network. The results show that the results that are obtained by our model have high peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), and the average high load capacity is 23.96 bpp (bit per pixel), thus realizing large-capacity image steganography surgery.

scholarly journals Studying Audio Capacity as Carrier of Secret Images in Steganographic System

2021 ◽  
Vol 19 (49) ◽  
pp. 53-61
Author(s):  
Ahlam Majead Kadhim ◽  
Huda Muhamed Jawad
Keyword(s):  
High Capacity ◽  
Secret Message ◽  
Hiding Capacity ◽  
Audio File ◽  
Audio Steganography ◽  
Secret Image ◽  
Secret Information

Steganography art is a technique for hiding information where the unsuspicious cover signal carrying the secret information. Good steganography technique must be includes the important criterions robustness, security, imperceptibility and capacity. The improving each one of these criterions is affects on the others, because of these criterions are overlapped each other.  In this work, a good high capacity audio steganography safely method has been proposed based on LSB random replacing of encrypted cover with encrypted message bits at random positions. The research also included a capacity studying for the audio file, speech or music, by safely manner to carrying secret images, so it is difficult for unauthorized persons to suspect presence of hidden image. Measures calculations of SNR, SNR segmental, SNR spectral, MSE and correlation show that, audio music cover file (2channales) is the safest uses as arrier with replace the 9 number of LSB without noticeable noise. Bits of secret message can be hiding capacity reach up to 28 % of the total music cover audio size and the three type's measures of SNR are 32, 28 and 31 dB. For speech cover audio the replacing LSB is safely uses at LSB bits number 6, where the hiding capacity is reach up to 37 % of size speech cover audio at 37, 36 and 39 dB for three type's measures of SNR. Correlation of cover samples was did not effected as a result of hiding secret image, where its value is up to 0.99 for all hiding operations.

scholarly journals FPGA based Data Hiding through Steganography

2020 ◽  
Vol 9 (1) ◽  
pp. 2042-2045
Keyword(s):  
Data Hiding ◽  
Field Programmable Gate Array ◽  
High Capacity ◽  
Cover Image ◽  
Secret Message ◽  
Stego Image ◽  
Key Factor ◽  
Field Programmable ◽  
Shared Information ◽  
Hidden Data

Nowadays, the information security has been the key factor in communications, computer systems, electronic commerce and data sharing. One of the well-known methods for procuring the security of shared information using carrier files is steganography. The carrier file can be discrete such as image, text, audio and video etc. Digital images are the most commonly used format among those due to the high capacity and availability frequency. The hidden data is stored in an indistinct carrier in image steganography, i.e the digital image is used as a cover image to mask the secret message known as stego image. Cryptography can be then adapted for increasing the security of the stego image. A zig-zag MSB-LSB slicing based steganographic algorithm is proposed in this paper for concealing a secret image in a cover image. Power report and device utilization summary of the algorithm is calculated and the output is demonstrated on the VGA screen using BASYS3 Field Programmable Gate Array (FPGA).

scholarly journals Information Hiding Based on Histogram and Pixel Pattern

2017 ◽  
Author(s):  
Ari Moesriami Barmawi ◽  
Deden Pradeka
Keyword(s):  
Information Hiding ◽  
Information Exchange ◽  
High Capacity ◽  
Cover Image ◽  
Secret Message ◽  
Embedding Capacity ◽  
Stego Image ◽  
Image Histogram ◽  
Pixel Value ◽  
Value Changes

Recently, information exchange using internet is increasing, such that information security is necessary for securing confidential information because it is possible to eavesdrop the information. There are several methods for securing the exchanged information such as was proposed by Rejani et al. Rejani’s method can be noiseless in low capacity but noisy in high capacity. In the case of high capacity, it will raise suspicion. This research proposed a method based on histogram and pixel pattern for keeping the stego image noiseless while still keeping the capacity high. Secret information can be embedded into the cover by evaluating the histogram and map the characters used in the secret message to the consecutive intensity in the cover image histogram. The map of the characters is sent to the recipient securely. Using the proposed method there is no pixel value changes during the embedding process. Based on the result of the experiments, it is shown that in noiseless condition, the proposed method has higher embedding capacity than Rejani’s especially when using cover image with sizes larger than 128 × 128. Thus, in noiseless condition the embedding capacity using the proposed method is higher than Rejani’s method in noiseless condition.  

scholarly journals Deep Multi-Image Steganography with Private Keys

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1906
Author(s):  
Hyeokjoon Kweon ◽  
Jinsun Park ◽  
Sanghyun Woo ◽  
Donghyeon Cho
Keyword(s):  
Image Steganography ◽  
The Other ◽  
Cover Image ◽  
Hidden Information ◽  
Secret Image ◽  
Secret Information ◽  
Private Key ◽  
Deep Cnn ◽  
High Level ◽  
Multiple Secret Images

In this paper, we propose deep multi-image steganography with private keys. Recently, several deep CNN-based algorithms have been proposed to hide multiple secret images in a single cover image. However, conventional methods are prone to the leakage of secret information because they do not provide access to an individual secret image and often decrypt the entire hidden information all at once. To tackle the problem, we introduce the concept of private keys for secret images. Our method conceals multiple secret images in a single cover image and generates a visually similar container image containing encrypted secret information inside. In addition, private keys corresponding to each secret image are generated simultaneously. Each private key provides access to only a single secret image while keeping the other hidden images and private keys unrevealed. In specific, our model consists of deep hiding and revealing networks. The hiding network takes a cover image and secret images as inputs and extracts high-level features of the cover image and generates private keys. After that, the extracted features and private keys are concatenated and used to generate a container image. On the other hand, the revealing network extracts high-level features of the container image and decrypts a secret image using the extracted feature and a corresponding private key. Experimental results demonstrate that the proposed algorithm effectively hides and reveals multiple secret images while achieving high security.

Novel Multifold Secured System by Combining Multimodal Mask Steganography and Naive Based Random Visual Cryptography System for Digital Communication

2020 ◽  
Vol 17 (12) ◽  
pp. 5279-5295
Author(s):  
S. Jahnavi ◽  
C. Nandini
Keyword(s):  
Visual Cryptography ◽  
Complete Information ◽  
Cover Image ◽  
Secret Message ◽  
The Internet ◽  
Next Generation ◽  
Least Significant Bit ◽  
Secret Data ◽  
Stego Image ◽  
Digital World

With increase in growth of data and digital threat, demand of securing the data communicated over the internet is an essential play in the digital world. In the vision of digitalizing services with the next generation of security to the sensitive data transmitted over the internet by hiding the existence of the data using next generation cryptography by fusing cryptography techniques is one the major technique adopted. With this the aim in traditional Least Significant Bit (LSB) is one of the widely used technique. Where the secret message or image are placed in the cover image in the least significant bits of RGB Channels resulting in a stego image. But the drawback is, on suspecting the differences in the pixels of original and stegoimage in the secret data embedded can be guessed and extracted by attacker. The Proposed visual crypto-mask steganography method overcomes this drawback and support good payload capacity with multi modal approach of embedding biometrics, resulting in ∞ PSNR. The authenticated person face and fingerprint information is transmitted in a cover image and mask image (magic sheet) using proposed steganography and is combined with Random Visual Crypto Technique. Which results in enhanced and advance visual crypto steganography secured model in communicating sensitive (biometric features) information over the internet. Where the complete information cannot be extracted using only cover image. Mask image (magic sheet) is used along with cover image that reveals the secret data in the receiving end.

scholarly journals An Image Style Transfer Network Using Multilevel Noise Encoding and Its Application in Coverless Steganography

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1152
Author(s):  
Shanqing Zhang ◽  
Shengqi Su ◽  
Li Li ◽  
Qili Zhou ◽  
Jianfeng Lu ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Color Image ◽  
Image Data ◽  
Cover Image ◽  
Stego Image ◽  
Style Transfer ◽  
Secret Information ◽  
Residual Learning ◽  
Short Period

Most of the existing image steganographic approaches embed the secret information imperceptibly into a cover image by slightly modifying its content. However, the modification traces will cause some distortion in the stego-image, especially when embedding color image data that usually contain thousands of bits, which makes successful steganalysis possible. A coverless steganographic approach without any modification for transmitting secret color image is proposed. We propose a diversity image style transfer network using multilevel noise encoding. The network consists of a generator and a loss network. A multilevel noise to encode matching the subsequent convolutional neural network scale is used in the generator. The diversity loss is increased in the loss network so that the network can generate diverse image style transfer results. Residual learning is introduced so that the training speed of network is significantly improved. Experiments show that the network can generate stable results with uniform texture distribution in a short period of time. These image style transfer results can be integrated into our coverless steganography scheme. The performance of our steganography scheme is good in steganographic capacity, anti-steganalysis, security, and robustness.

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.

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