scholarly journals Adaptive Matrix Pattern Steganography on RGB Images

2021 ◽  
Author(s):  
Amirfarhad Nilizadeh ◽  
Shirin Nilizadeh ◽  
Wojciech Mazurczyk ◽  
Cliff Zou ◽  
Gary T. Leavens
Keyword(s):  
Digital Media ◽  
Signal To Noise Ratio ◽  
Spatial Domain ◽  
Image Steganography ◽  
Image Block ◽  
Hiding Capacity ◽  
Ascii Character ◽  
Blue Channel ◽  
Rgb Images ◽  
Almost All

Almost all spatial domain image steganography methods rely on modifying the Least Significant Bits (LSB) of each pixel to minimize the visual distortions. However, these methods are susceptible to LSB blind attacks and quantitative steganalyses. This paper presents an adaptive spatial domain image steganography algorithm for hiding digital media based on matrix patterns, named “Adaptive Matrix Pattern” (AMP). The AMP method increases the security of the steganography scheme of largely hidden messages since it adaptively generates a unique codebook matrix pattern for each ASCII character in each image block. Therefore, each ASCII character gets a different codebook matrix pattern even in different regions of the same image. Moreover, it uses a preprocessing algorithm to identify the most suitable image blocks for hiding purposes. The resulting stego-images are robust against LSB blind attacks since the middle bits of green and blue channels generate matrix patterns and hiding secrets, respectively. Experimental results show that AMP is robust against quantitative steganalyses. Additionally, the quality of stego-images, based on the peak signal-to-noise ratio metric, remains high in both stego-RGB-image and in the stego-blue-channel. Finally, the AMP method provides a high hiding capacity, up to 1.33 bits per pixel.

Secret Communication Techniques

2019 ◽  
pp. 1-19
Keyword(s):  
Digital Media ◽  
Quality Parameters ◽  
Image Steganography ◽  
Hiding Capacity ◽  
Video Steganography ◽  
Communication Techniques ◽  
Secret Communication ◽  
Text Steganography ◽  
Distortion Measure

This chapter introduces the reader to cryptography, steganography, watermarking, and quality parameters of image steganography techniques. Cryptography is a technique for secret communication. Steganography is a technique for secret and unnoticeable communication. The watermarking techniques hide watermarks inside the digital media. There are four types of steganography techniques: (1) image steganography, (2) audio steganography, (3) video steganography, and (4) text steganography. The quality of image steganographic algorithms can be measured by three parameters like (1) hiding capacity, (2) distortion measure, and (3) security check.

scholarly journals Digital Image Steganography Using Bit Flipping

2018 ◽  
Vol 18 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Aditya Kumar Sahu ◽  
Gandharba Swain ◽  
E. Suresh Babu
Keyword(s):  
Digital Image ◽  
Quality Index ◽  
Signal To Noise Ratio ◽  
The State ◽  
Image Steganography ◽  
Original Image ◽  
Signal To Noise ◽  
Secret Data ◽  
Hiding Capacity ◽  
State Of Art

Abstract This article proposes bit flipping method to conceal secret data in the original image. Here a block consists of 2 pixels and thereby flipping one or two LSBs of the pixels to hide secret information in it. It exists in two variants. Variant-1 and Variant-2 both use 7th and 8th bit of a pixel to conceal the secret data. Variant-1 hides 3 bits per a pair of pixels and the Variant-2 hides 4 bits per a pair of pixels. Our proposed method notably raises the capacity as well as bits per pixel that can be hidden in the image compared to existing bit flipping method. The image steganographic parameters such as, Peak Signal to Noise Ratio (PSNR), hiding capacity, and the Quality Index (Q.I) of the proposed techniques has been compared with the results of the existing bit flipping technique and some of the state of art article.

Improved Capacity Image Steganography Algorithm using 16-Pixel Differencing with n-bit LSB Substitution for RGB Images

2016 ◽  
Vol 6 (6) ◽  
pp. 2735 ◽  
Author(s):  
Meenakshi S Arya ◽  
Meenu Rani ◽  
Charndeep Singh Bedi
Keyword(s):  
Digital Media ◽  
Daily Basis ◽  
Image Steganography ◽  
The Internet ◽  
Least Significant Bit ◽  
Content Protection ◽  
Hiding Capacity ◽  
Pixel Value ◽  
Four Levels ◽  
Lsb Substitution

<p>With the intrusion of internet into the lives of every household and terabytes of data being transmitted over the internet on daily basis, the protection of content being transmitted over the internet has become an extremely serious concern. Various measures and methods are being researched and devised everyday to ensure content protection of digital media. To address this issue of content protection, this paper proposes an RGB image steganography based on sixteen-pixel differencing with n-bit Least Significant Bit (LSB) substitution. The proposed technique provides higher embedding capacity without sacrificing the imperceptibility of the host data. The image is divided into 4×4 non overlapping blocks and in each block the average difference value is calculated. Based on this value the block is classified to fall into one of four levels such as, lower, lower-middle, higher-middle and higher. If block belongs to lower level then 2-bit LSB substitution is used in it. Similarly, for lower-middle, higher-middle and higher level blocks 3, 4, and 5 bit LSB substitution is used. In our proposed method there is no need of pixel value readjustment for minimizing distortion. The experimental results show that stego-images are imperceptible and have huge hiding capacity.</p>

scholarly journals Improved Capacity Image Steganography Algorithm using 16-Pixel Differencing with n-bit LSB Substitution for RGB Images

2016 ◽  
Vol 6 (6) ◽  
pp. 2735
Author(s):  
Meenakshi S Arya ◽  
Meenu Rani ◽  
Charndeep Singh Bedi
Keyword(s):  
Digital Media ◽  
Daily Basis ◽  
Image Steganography ◽  
The Internet ◽  
Least Significant Bit ◽  
Content Protection ◽  
Hiding Capacity ◽  
Pixel Value ◽  
Four Levels ◽  
Lsb Substitution

<p>With the intrusion of internet into the lives of every household and terabytes of data being transmitted over the internet on daily basis, the protection of content being transmitted over the internet has become an extremely serious concern. Various measures and methods are being researched and devised everyday to ensure content protection of digital media. To address this issue of content protection, this paper proposes an RGB image steganography based on sixteen-pixel differencing with n-bit Least Significant Bit (LSB) substitution. The proposed technique provides higher embedding capacity without sacrificing the imperceptibility of the host data. The image is divided into 4×4 non overlapping blocks and in each block the average difference value is calculated. Based on this value the block is classified to fall into one of four levels such as, lower, lower-middle, higher-middle and higher. If block belongs to lower level then 2-bit LSB substitution is used in it. Similarly, for lower-middle, higher-middle and higher level blocks 3, 4, and 5 bit LSB substitution is used. In our proposed method there is no need of pixel value readjustment for minimizing distortion. The experimental results show that stego-images are imperceptible and have huge hiding capacity.</p>

scholarly journals Binary  Image  Steganography  based  on  Permutation

2021 ◽  
Author(s):  
Juvet Karnel Sadié ◽  
Stéphane Gael Raymond Ekodeck ◽  
Rene Ndoundam
Keyword(s):  
Binary Image ◽  
Image Steganography ◽  
Image Block ◽  
Hiding Capacity ◽  
Binary Images ◽  
Embedding Technique

Abstract We propose a steganographic scheme based on permutations, which improves the capacity of embedding information in a series of p host binary images. Given a host binary image block of size m x n bits and any embedding technique T, where T can hide Q(m, n) bits of data in the image; given p images, T can hide p x Q(m, n) bits of data in these images. Our scheme improves the capacity of embedding information in p images such that, instead of p x Q(m, n) bits, it can hide p x log2(p) + p x Q(m, n)bits. The results which have been obtained by experiments, show that our model performs a better hiding process in terms of hiding capacity.

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 Steganografi QR Code pada Dual Carrier Image dengan Metode Least Significant Bit

2019 ◽  
Vol 5 (3) ◽  
pp. 261
Author(s):  
Yahya Risqi ◽  
Rudy Dwi Nyoto ◽  
Hafiz Muhardi
Keyword(s):  
Image Steganography ◽  
Qr Code ◽  
Least Significant Bit ◽  
Hiding Capacity ◽  
Blue Channel ◽  
Carrier Image ◽  
Salt And Pepper

Image Steganography adalah teknik untuk menyisipkan pesan rahasia ke dalam suatu citra digital, sehingga secara kasat mata manusia tidak akan mengetahui keberadaan dari pesan rahasia tersebut. Tujuan dari penetilian ini adalah menggunakan citra QR Code sebagai secret yang diubah ke dalam mode bitonal dengan 1 bit pada tiap pikselnya kemudian dipecah menjadi dua bagian dan disisipkan kedalam blue channel di dual carrier image sehingga kapasitas dari pesan yang akan disisipkan dapat meningkat. Penyisipan pada dual carrier image juga dapat meningkatkan keamanan karena pesan dapat dikirim secara terpisah. Penyisipan pesan dilakukan dengan metode substitusi Least Significant Bit (LSB). Untuk mengevaluasi model steganography yang diteliti, digunakan pengujian MSE and PSNR, Hiding Capacity (HC), Histogram, recovery dan noise. Hasil pengujian menunjukkan dengan menggunakan citra PNG dan TIFF pada HC hingga 95% nilai PSNR tetap tinggi yaitu sebesar 56 dB, dengan tingkat recovery 100% dan tahan terhadap jenis noise salt and pepper.

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.

A New Data Hiding Scheme Using Laplace Transformation in Frequency Domain Steganography

2020 ◽  
Vol 4 (1) ◽  
pp. 1-12
Author(s):  
Ayan Chatterjee ◽  
Nikhilesh Barik
Keyword(s):  
Frequency Domain ◽  
Laplace Transformation ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Spatial Domain ◽  
Image Steganography ◽  
Secret Information ◽  
Wireless Communication Network ◽  
Communication Technique ◽  
Efficiency And Effectiveness

Today, in the age of wireless communication, network security is an important issue. Image steganography is a popular approach to make communication secure. Among two categories (spatial domain and frequency domain) of image steganography, frequency domain is more secured than the spatial domain. The proposed scheme develops a secret communication technique in frequency domain steganography. In steganography, the concept of Laplace transformation is used during embedding and extraction procedures of secret information in image files. As a result, all the conditions of information security are developed in high density. The efficiency and effectiveness of the scheme is evaluated by measuring the hacking chance from different statistical attacks by RS steganalysis and originality of actual cover image after inserting secret information by Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR).

scholarly journals High Security and Capacity of Image Steganography for Hiding Human Speech Based on Spatial and Cepstral Domains

2020 ◽  
Vol 8 (1) ◽  
pp. 95
Author(s):  
Yazen A. Khaleel
Keyword(s):  
Speech Signal ◽  
Vocal Tract ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Mel Frequency Cepstral Coefficients ◽  
Secret Data ◽  
Stego Image ◽  
Hiding Capacity ◽  
Original Speech

A new technique of hiding a speech signal clip inside a digital color image is proposed in this paper to improve steganography security and loading capacity. The suggested technique of image steganography is achieved using both spatial and cepstral domains, where the Mel-frequency cepstral coefficients (MFCCs) are adopted, as very efficient features of the speech signal. The presented technique in this paper contributes to improving the image steganography features through two approaches. First is to support the hiding capacity by the usage of the extracted MFCCs features and pitches extracted from the speech signal and embed them inside the cover color image rather than directly hiding the whole samples of the digitized speech signal. Second is to improve the data security by hiding the secret data (MFCCs features) anywhere in the host image rather than directly using the least significant bits substitution of the cover image. At the recovering side, the proposed approach recovers these hidden features and using them to reconstruct the speech waveform again by inverting the steps of MFCCs extraction to recover an approximated vocal tract response and combine it with recovered pitch based excitation signal. The results show a peak signal to noise ratio of 52.4 dB of the stego-image, which reflect a very good quality and a reduction ratio of embedded data to about (6%–25%). In addition, the results show a speech reconstruction degree of about 94.24% correlation with the original speech signal.

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