scholarly journals A New Digital Image Steganography Based on Center Embedded Pixel Positioning

2021 ◽  
Vol 21 (2) ◽  
pp. 89-104
Author(s):  
Dedi Darwis ◽  
Akmal Junaidi ◽  
Dewi Asiah Shofiana ◽  
Wamiliana
Keyword(s):  
Digital Image ◽  
Image Steganography ◽  
Cover Image ◽  
Least Significant Bit ◽  
Bottom Part ◽  
New Approach ◽  
Secret Image ◽  
Lsb Matching ◽  
Two Sides ◽  
Sequential Cropping

Abstract In this study we propose a new approach to tackle the cropping problem in steganography which is called Center Embedded Pixel Positioning (CEPP) which is based on Least Significant Bit (LSB) Matching by setting the secret image in the center of the cover image. The evaluation of the experiment indicated that the secret image can be retrieved by a maximum of total 40% sequential cropping on the left, right, up, and bottom of the cover image. The secret image also can be retrieved if the total asymmetric cropping area is 25% that covered two sides (either left-right, left-up or right-up). In addition, the secret image can also be retrieved if the total asymmetric cropping area is 70% if the bottom part is included. If asymmetric cropping area included three sides, then the algorithm fails to retrieve the secret image. For cropping in the botom the secret image can be extracted up to 70%.

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 Modified Lsb For Hiding Encrypted Kurdish Text Into Digital Image

2019 ◽  
Vol 7 (4) ◽  
pp. 254
Author(s):  
Nada E. Tawfiq
Keyword(s):  
Digital Image ◽  
Text Message ◽  
Cover Image ◽  
Second Phase ◽  
Original Image ◽  
Text File ◽  
Least Significant Bit ◽  
Text Information ◽  
Embedded Technique ◽  
Lsb Substitution

Image files can hide text without their size being affected too much. This process called steganography which allows hiding text in images without any suspicions from intruders. This paper addresses an improved LSB substitution algorithm for hiding Kurdish text information written in text file into digital image as steganography technique. The algorithm consists of two main phases, the first phase holds the encryption of the Kurdish text message and the embedded technique while the second phase hold the message extraction followed by decryption to get the original code of each character. The algorithm contains many procedures to enhance this process. Least Significant Bit method is used to hide the Kurdish text, in order to keep the features and characteristics of the original image. Applying the proposed approach shows that it seems work in a best case by hiding and retrieving text from the digital image which is used as a carrier of this text. Delphi 2010 was used to simulate both encrypt-embedded phase and extract-decrypt phase, and the results were obtained with high and security which proved the efficiency of the algorithm, where the hidden Kurdish text didn’t make any distortion or change over the cover image.

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.

Combining Digital Signature with Local Binary Pattern-Least Significant Bit Steganography Techniques for Securing Medical Images

2020 ◽  
Vol 10 (6) ◽  
pp. 1288-1293
Author(s):  
K. N. Madhusudhan ◽  
P. Sakthivel
Keyword(s):  
Digital Signature ◽  
Local Binary Pattern ◽  
Medical Images ◽  
Image Authentication ◽  
Reversible Watermarking ◽  
Cover Image ◽  
Least Significant Bit ◽  
New Approach ◽  
Different Types ◽  
Separate File

The image authentication is generally based on two different types of techniques: watermarking and digital signature. In watermarking methods, embedded watermarking is often imperceptible and it contains either a specific ID of producer or codes related to content that are used for authentication. Normally a separate file is stored, digital signature is a non-repudiation and encrypted version of the information extracted from the data. A digital signature can be attached to the data to prove the originality and integrity. The proposed work presents a new approach to steganography of medical images that uses modified Least Significant Bit (LSB) based on the Local Binary Pattern (LBP) pattern. As a first step, cover image has been divided as blocks of 3×3 non overlapping masks. Then, the pixel embedding position (clock wise or anti-clock wise) has to be identified using LBP operator. The value of the LBP operator determines how and where to embed secret image pixel. Later, using LSB method, pixel values will be embedded in the cover image pixel. In order to provide the integrity of the data, the proposed work also presents Reversible Watermarking (RW), a Digital Signature (DS) technique. The proposed algorithm of steganography experimented on few medical images and achieved better efficiency with respect to MSE and PSNR values and same is reported in this paper.

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 ANALISA PERBANDINGAN LSB STEGANOGRAFI ANTARA SHIFTING DAN RANDOM COLOR

Repositor ◽  
2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Agus Eko Minarno
Keyword(s):  
Cover Image ◽  
Least Significant Bit ◽  
Secret Image

Steganografi merupakan teknik untuk menyembunyikan keberadaan data ke dalam data lain sehingga keberadaannya tidak diketahui. Sehingga selain pengirim dan penerima tidak ada yang mengetahui isi dari pesan tersebut dan tidak mudah untuk dicurigai. Beberapa algoritma yang cocok dengan teknik steganography, salah satunya yaitu algoritma LSB (Least Significant Bit). Algoritma LSB sendiri sudah dikembangkan oleh beberapa penelitian sebelumnya, yaitu menjadi algoritma LSB Random Color dan algoritma LSB Shifting. Dua algoritma tersebut merupakan algoritma yang terbaru dari algoritma LSB. Beberapa penelitian sebelumnya melakukan pengujian algoritma LSB random color dan algoritma LSB shifting dengan menggunakan data yang berbeda, dan hasil penelitian sebelumnya tidak melakukan perbandingan mana yang lebih baik dari dua algoritma tersebut. Dalam penelitian ini penulis membuat penelitian dengan judul analisa perbandingan LSB steganografi antara shifting dan random color. Pengujian diukur dengan menghitung nilai MSE dan PSNR pada file stegano image. Penelitian ini menggunakan 2 jenis file cover image yaitu berwarna dan hitam putih dengan jumlah masing-masing 3 file yang berbeda, dan menggunakan 1 file secret image yang sama. Sehingga diperoleh hasil perbandingan bahwasannya algoritma LSB random color memiliki performa lebih baik, meskipun mengunakan jenis file berwarna atau hitam putih

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 PENGAMANAN DATA TEKS DENGAN KOMBINASI CIPHER BLOCK CHAINING DAN LSB-1

2018 ◽  
Author(s):  
Taronisokhi Zebua
Keyword(s):  
Digital Image ◽  
Feedback Mechanism ◽  
Cover Image ◽  
Least Significant Bit ◽  
Text Data ◽  
Current Block ◽  
Cryptographic Techniques ◽  
True Color ◽  
Block Chaining

There are several approaches to secure a data techniques that are still used by some circles among them by applying cryptographic techniques, steganography techniques, watermarks and other techniques. One technique that can be done to optimize the security of text data is to combine cryptographic techniques with steganography techniques. Cryptographic techniques serve to encrypt the text data is concealed through the process of encryption, while steganography techniques serve to hide (embedded) encrypted text data into a media such as images, video or audio. The algorithm of cryptographic techniques used in this case is the Cipher Block Chaining (CBC) algorithm invented by IBM in 1976 that implements a feedback mechanism on a block wherein the previous block will be fed back with the current block. The method used to hide encrypted messages on a medium is one of the modifications to the Least Significant Bit method, Least Significant Bit-1 (LSB-1). The LSB-1 algorithm works by replacing each of the 7th bits of the container medium with encrypted text bits. The collecting media (cover image) used in this case is a true color digital image.

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 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.

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