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.

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 An Adaptive Image Steganography Technique Using LSB and MSB

2013 ◽  
Vol 3 (1) ◽  
Author(s):  
Lakkshmanan Ajanthaa ◽  
Puja Dharia ◽  
Fairy Gandhi
Keyword(s):  
Statistical Analysis ◽  
Secure Communication ◽  
The Other ◽  
Cover Image ◽  
Least Significant Bit ◽  
Hidden Information ◽  
Media Image ◽  
Secret Information ◽  
Naked Eye ◽  
Essential Properties

IN modern years Steganography is playing a significant role in secure communication. It is a technique of embedding secret information into cover media (image, video, audio and text) such that only the sender and the authoritative receiver can detect the occurrence of hidden information. The two essential properties of Steganography are good visual imperceptibility of the payload which is crucial for security of hidden communication and payload is essential for conveying huge quantity of secret information. Steganography has to satisfy two requirements, one is capability and the other is transparency. Capability means embedding large payload into media. Transparency means an ability to prevent distinction between stego and cover image by statistical analysis. Earlier they have used least significant bit (LSB), the simplest form of Steganography. In LSB method, data is inserted in the least significant bit which leads to a negligible change on the cover image that is not visible to the naked eye. Since this method can be easily cracked, it is more exposed to attacks. In the proposed system we propose Spatial Domain Steganography using 1-Bit Most Significant Bit (MSB) with confused manner.

ANALYSIS OF DATA HIDING ALGORITHMS FOR IMAGE SECURITY

2015 ◽  
Vol 3 (5) ◽  
pp. 350-354
Author(s):  
Swati B. Singh ◽  
Ameya K. Naik ◽  
Pragati Dwivedi ◽  
Swapna Patil
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Stream Cipher ◽  
Haar Wavelet ◽  
Image Steganography ◽  
Cover Image ◽  
Wavelet Compression ◽  
Image Security ◽  
Secret Image ◽  
Secret Information

The main goal of reversible data hiding algorithms is to embed the secret information in cover image and recover it back successfully. So we have implemented two methods. In first method, cover image is encrypted using stream cipher and pseudo randomly generated key and compressed using haar wavelet compression. The encrypted compressed image acts as a media for hiding secret image. And in second method, secret image is encrypted using randomly generated key and it is hidden in cover image. In both the method data hiding is done using LSB based image steganography. At the receiver, reverse process is done to extract secret image and recover cover image. At the end, we conclude that second method gives better security of image compared to method one.

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 On Max-Plus Algebra and Its Application on Image Steganography

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Kiswara Agung Santoso ◽  
Fatmawati ◽  
Herry Suprajitno
Keyword(s):  
Operating Systems ◽  
Matrix Multiplication ◽  
Previous Method ◽  
Image Steganography ◽  
Cover Image ◽  
The Matrix ◽  
High Level

We propose a new steganography method to hide an image into another image using matrix multiplication operations on max-plus algebra. This is especially interesting because the matrix used in encoding or information disguises generally has an inverse, whereas matrix multiplication operations in max-plus algebra do not have an inverse. The advantages of this method are the size of the image that can be hidden into the cover image, larger than the previous method. The proposed method has been tested on many secret images, and the results are satisfactory which have a high level of strength and a high level of security and can be used in various operating systems.

scholarly journals A Survey of Different Steganography Technique using Cryptographic Algorithm

2018 ◽  
Vol 7 (2) ◽  
pp. 40-43
Author(s):  
Prakhar Agrawal ◽  
Arvind Upadhyay
Keyword(s):  
Data Security ◽  
Image Steganography ◽  
The Other ◽  
Sensitive Information ◽  
Hidden Information ◽  
Cipher Text ◽  
Other Hand ◽  
Cryptographic Algorithm ◽  
Secure Data ◽  
Hide Data

Steganography and cryptography are two major aspects of data security . In this paper we are going to provide the survey of different techniques of LSB based Steganography that used cryptography algorithms to secure sensitive information. Steganography is used to hide data and Cryptography is used to encrypt the data. Although cryptography and steganography individually can provide data security, every of them has a drawback. Drawback associated with Cryptography is that, the cipher text looks meaningless, so the unintended user can interrupt the transmission or make more careful checks on the information from the sender to the receiver. Drawback associated with Steganography is that when the presence of hidden information is revealed or even suspected, the message is become known[1].By combining these two methods we can solve both of the above problem. First we encrypt the data using any cryptography technique and then embed the encrypted text into the image. Steganography is the process which hides the presence of secure data during communication. On the other hand cryptography is encrypting and decrypting of secure data and information with a secrete key so that no one can be understand the message directly.

scholarly journals Optimal Image Steganography Content Destruction Techniques

2021 ◽  
Vol 15 ◽  
pp. 84-88
Author(s):  
Siddeeq Y. Ameen ◽  
Muthana R. Al-Badrany
Keyword(s):  
Discrete Cosine Transform ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Hidden Information ◽  
Random Data ◽  
Cosine Transform ◽  
Wavelet Techniques ◽  
Lsb Technique

The paper presents two approaches for destroying steganogrphy content in an image. The first is the overwriting approach where a random data can be written again over steganographic images whereas the second approach is the denoising approach. With the second approach two kinds of destruction techniques have been adopted these are filtering and discrete wavelet techniques. These two approaches have been simulated and evaluated over two types of hiding techniques, Least Significant Bit LSB technique and Discrete Cosine Transform DCT technique. The results of the simulation show the capability of both approaches to destroy the hidden information without any alteration to the cover image except the denoising approach enhance the PSNR in any received image even without hidden information by an average of 4dB.

scholarly journals Design and Implementation of Lifting Based Wavelet and Adaptive LSB Steganography to Secret Data Sharing Through Image on FPGA

2018 ◽  
Vol 8 (03) ◽  
Author(s):  
Kokila B. Padeppagol ◽  
Sandhya Rani M H
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Image Data ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Secret Data ◽  
Secret Image ◽  
Design And Implementation

Image steganography is an art of hiding images secretly within another image. There are several ways of performing image steganography; one among them is the spatial approach.The most popular spatial domain approach of image steganography is the Least Significant Bit (LSB) method, which hides the secret image pixel information in the LSB of the cover image pixel information. In this paper a LSB based steganography approach is used to design hardware architecture for the Image steganography. The Discrete Wavelet Transform (DWT) is used here to transform the cover image into higher and lower wavelet coefficients and use these coefficients in hiding the secret image. the design also includes encryption of secret image data, to provide a higher level of security to the secret image. The steganography system involving the stegno module and a decode module is designed here. The design was simulated, synthesized and implemented on Artix -7 FPGA. The operation hiding and retrieving images was successfully verified through simulations.

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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