Steganographic Algorithm Based on Adapting Secret Message to the Cover Image

2019 ◽  
pp. 753-771
Author(s):  
Youssef Taouil ◽  
El Bachir Ameur
Keyword(s):  
Cover Image ◽  
Secret Message

scholarly journals A n-out-of-n Sharing Digital Image Scheme by Using Color Palette

Electronics ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 802
Author(s):  
Ching-Nung Yang ◽  
Qin-Dong Sun ◽  
Yan-Xiao Liu ◽  
Ci-Ming Wu
Keyword(s):  
Digital Image ◽  
Shadow Image ◽  
Cover Image ◽  
Secret Message ◽  
Secret Image Sharing ◽  
Color Palette ◽  
Secret Image ◽  
Image Sharing

A secret image sharing (SIS) scheme inserts a secret message into shadow images in a way that if shadow images are combined in a specific way, the secret image can be recovered. A 2-out-of-2 sharing digital image scheme (SDIS) adopts a color palette to share a digital color secret image into two shadow images, and the secret image can be recovered from two shadow images, while any one shadow image has no information about the secret image. This 2-out-of-2 SDIS may keep the shadow size small because by using a color palette, and thus has advantage of reducing storage. However, the previous works on SDIS are just 2-out-of-2 scheme and have limited functions. In this paper, we take the lead to study a general n-out-of-n SDIS which can be applied on more than two shadow. The proposed SDIS is implemented on the basis of 2-out-of-2 SDIS. Our main contribution has the higher contrast of binary meaningful shadow and the larger region in color shadows revealing cover image when compared with previous 2-out-of-2 SDISs. Meanwhile, our SDIS is resistant to colluder attack.

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 Embedding information into JPEG images with distortion masking in frequency domain

2020 ◽  
Vol 23 (4) ◽  
pp. 45-50
Author(s):  
A. S. Melman ◽  
◽  
P. O. Petrov ◽  
A. A. Shelupanov ◽  
A. V. Aristov ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Data Transmission ◽  
Experimental Results ◽  
Cover Image ◽  
Secret Message ◽  
Security Level ◽  
Information Protection ◽  
Quantization Step ◽  
Jpeg Images ◽  
Statistical Steganalysis

Steganography allows to ensure the confidentiality of information by organizing covert data transmission channels. However, the effectiveness of steganographic information protection directly depends on the invisibility of a secret message, both for the human eye and for steganalysis methods. The paper proposes an approach that allows solving the problem of vulnerability of the popular QIM embedding method to statistical steganalysis. For this, it is proposed to use a variable quantization step, which is adaptively selected for each block of the JPEG cover image. The experimental results demonstrate an increase in the security level of steganographic embedding due to the application of the proposed approach.

scholarly journals Hiding Data in Color Image Using Least Significant Bits of Blue Sector

2018 ◽  
Vol 31 (2) ◽  
pp. 193 ◽  
Author(s):  
Hussein L. Hussein
Keyword(s):  
Color Image ◽  
Cover Image ◽  
Secret Message ◽  
Mapping Technique ◽  
Least Significant Bit ◽  
Blue Sector ◽  
Powerful Technique ◽  
Secret Communication ◽  
Least Significant Bits

Concealing the existence of secret hidden message inside a cover object is known as steganography, which is a powerful technique. We can provide a secret communication between sender and receiver using Steganography. In this paper, the main goal is for hiding secret message into the pixels using Least Significant Bit (LSB) of blue sector of the cover image. Therefore, the objective is by mapping technique presenting a model for hiding text in an image. In the model for proposing the secret message, convert text to binary also the covering (image) is divided into its three original colors, Red, Green and Blue (RGB) , use the Blue sector convert it to binary,  hide two bits from the message in  two bits of the least significant bits of blue sector of the image.

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 Keamanan Pesan Rahasia Menggunakan Steganografi DCT (Discrete Cosine Transform) pada Citra JPEG

2019 ◽  
Vol 9 (2) ◽  
Author(s):  
Dian Hafidh Zulfikar
Keyword(s):  
Discrete Cosine Transform ◽  
Spatial Domain ◽  
Cover Image ◽  
Secret Message ◽  
Least Significant Bit ◽  
Cosine Transform ◽  
Secret Information ◽  
Dct Coefficients ◽  
Lsb Technique ◽  
Dct Coefficient

<p class="SammaryHeader" align="center"><strong><em>Abstract</em></strong><em></em></p><p><em> </em>The  least significant-bit (LSB) based techniques are very popular for steganography in spatial domain. The simplest LSB technique simply replaces the LSB in the cover image with the  bits from secret information. Further advanced techniques use some criteria to identify the pixels in which LSB(s) can be replaced with the bits of secret information. In Discrete Cosine Transform (DCT) based technique insertion of secret information in carrier depends on the DCT coefficients. Any DCT coefficient value above proper threshold is a potential place for insertion of secret information.</p><p class="Abstrak"><strong> </strong><strong>Keywords :</strong> Discrete Cosine Transform (DCT), steganography, secret message</p><p><strong><em> </em><em>Abstra</em><em>k</em></strong></p><p>Pada steganografi domain spasial, teknik least significant-bit (LSB) merupakan teknik yang paling banyak digunakan pada steganografi. Teknik yang sederhana yang hanya mengubah nilai LSB pada cover image dengan nilai bit pesan rahasia, atau dengan teknik yang lebih baik lagi yaitu dengan menentukan bit-bit LSB mana yang akan dilakukan pergantian nilai bit. Lain halnya dengan metode Discrete Cosine Transform (DCT), teknik steganografi ini akan menyembunyikan informasi rahasia tergantung dari nilai Koefisien DCT.</p><p class="Abstrak"> </p><p class="Abstrak"><strong>Kata Kunci :</strong> Steganografi, DCT, Citra, JPEG, Pesan Rahasia</p>

scholarly journals Image and Text Steganography Using Convolutional Neural Network

2021 ◽  
Vol 65 (1) ◽  
pp. 26-32
Author(s):  
Vijay Kumar ◽  
Saloni Laddha ◽  
Aniket ◽  
Nitin Dogra
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Learning Algorithm ◽  
Cover Image ◽  
Secret Message ◽  
Main Aspect ◽  
Learning Modules ◽  
Deep Learning Algorithm ◽  
Minimal Distortion ◽  
Text Steganography

Steganography has been used since centuries for concealment of messages in a cover media where messages were physically hidden. The goal in our project is to hide digital messages using modern steganography techniques. An N * N RGB pixel secret message (either text or image) is to be transmitted in another N * N RGB container image with minimum changes in its contents. The cover image also called the carrier can be publicly visible. In this project, along with LSB encoding, deep learning modules using the Adam algorithm are used to train the model that comprises a hiding network and a reveal network. The encoder neural network determines where and how to place the message, dispersing it throughout the bits of cover image. The decoder network on the receiving side, which is simultaneously trained with the encoder, reveals the secret image. The main aspect of this work is it produces minimal distortion to the secret message. Thus, preserving its integrity. Also, other steganography softwares cannot be used to reveal the message since the model is trained using a deep learning algorithm which complicates its steganalysis. The network is only trained once, irrespective of the different container images and secret messages given as inputs. Thus, this work has wide and secure applications in many fields.

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 Multiple Image Based Dual Steganography Using Arnold Transform and Block Code Encoding

2021 ◽  
Vol 9 (10) ◽  
pp. 1299-1304
Keyword(s):  
Digital Media ◽  
Cyber Security ◽  
Data Communication ◽  
Block Code ◽  
Cover Image ◽  
Secret Message ◽  
Least Significant Bit ◽  
Arnold Transform ◽  
Cyber Crimes ◽  
Multiple Secret Images

Security plays a crucial role in the field of Social media network. Securing the data become one among the largest challenges in the present scenario. Whenever we expect concerning the cyber security, the primary issue that involves our mind is ‘cyber crimes’ that are increasing vastly day by day. Embedding secret message into the image (Steganography) is associated with art and science of secure data communication wherever the key information or confidential information is hidden in host file. It's employed incompletely different helpful applications like secure electronic communication, health care and military. Confidential information’s are unremarkably keep in digital media and transmitted via network cause of rapid growth of internet. In this paper, steganography techniques which might be used to safeguard the information from intruders. Here, Steganographic technique is used to hide multiple secret images into a single 24-bit cover image using Least Significant Bit (LSB) and dual steganography method. Multiple secret images are scrambled and encoded before hiding into cover image using Arnold Transform and Block Code Encoding. The Proposed technique is Block Code Encoding to convert Secret message to binary and bit pairs to form safer information. The main goals of proposed work offers security and high limit based steganography plan of concealing a massive size secret image into a bit size cover image, to enhance security using dual steganography, image quality and to reduce error.

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.  

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