scholarly journals A Comparative Analysis of LSB, MSB and PVD Based Image Steganography

2021 ◽  
Vol 8 (9) ◽  
pp. 373-377
Author(s):  
Alade Oluwaseun. Modupe ◽  
Amusan Elizabeth Adedoyin ◽  
Adedeji Oluyinka Titilayo
Keyword(s):  
Comparative Analysis ◽  
Performance Metrics ◽  
Similarity Index ◽  
Image Steganography ◽  
Secret Message ◽  
Future Research ◽  
Least Significant Bit ◽  
Comparative Performance ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography is the art and science of hiding information by embedding data into cover media. Numerous techniques are designed to provide the security for the communication of data over the Internet. A good steganographic algorithm is recognized by the performance of the techniques measured with the support of the performance metrics among which are PSNR, MSE, SSIM, robustness and capacity to hide the information in the cover image. In this paper a comparative analysis of Least Significant Bit (LSB), Most Significant Bit (MSB) and Pixel Value Differencing (PVD) image steganography in grayscale and colored images was performed. Three different cover images was used to hide secret message. A comparative performance analysis of LSB, MSB and PVD methods used in image steganography was performed using peak signal to noise ratio (PSNR), Mean square error (MSE) and Structural Similarity index (SSIM) as performance metrics. LSB technique gives higher PSNR and SSIM values than MSB and PVD method with lower MSE than the other two techniques. Future research can be geared towards investigating the embedding capacity, security, and computational complexity of each technique. Keywords: Least Significant Bit (LSB), Most Significant Bit (MSB), Pixel value differencing (PVD), PSNR, SSIM and MSE,

Pixel Prediction-Based Image Steganography by Support Vector Neural Network

2020 ◽  
Author(s):  
Reshma V K ◽  
Vinod Kumar R S
Keyword(s):  
Neural Network ◽  
Medical Image ◽  
Medical Information ◽  
Similarity Index ◽  
Image Steganography ◽  
Secret Message ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Prediction Scheme

Abstract Securing the privacy of the medical information through the image steganography process has gained more research interest nowadays to protect the privacy of the patient. In the existing works, least significant bit (LSB) replacement strategy was most popularly used to hide the sensitive contents. Here, every pixel was replaced for achieving higher privacy, but it increased the complexity. This work introduces a novel pixel prediction scheme-based image steganography to overcome the complexity issues prevailing in the existing works. In the proposed pixel prediction scheme, the support vector neural network (SVNN) classifier is utilized for the construction of a prediction map, which identifies the suitable pixels for the embedding process. Then, in the embedding phase, wavelet coefficients are extracted from the medical image based on discrete wavelet transform (DWT) and embedding strength, and the secret message is embedded into the HL wavelet band. Finally, the secret message is extracted from the medical image on applying the DWT. The experimentation of the proposed pixel prediction scheme is done by utilizing the medical images from the BRATS database. The proposed pixel prediction scheme has achieved high performance with the values of 48.558 dB, 0.50009 and 0.9879 for the peak signal to noise ratio (PSNR), Structural Similarity Index (SSIM) and correlation factor, respectively.

scholarly journals Information Trouncing Via Slightest Momentous Spot System Procedure

2018 ◽  
Vol 7 (3.27) ◽  
pp. 488
Author(s):  
D Saravanan ◽  
N Sivaprasad ◽  
Dennis Joseph
Keyword(s):  
Visual Quality ◽  
Secret Message ◽  
Pseudorandom Number Generator ◽  
Least Significant Bit ◽  
Pixel Value ◽  
The Difference ◽  
Pixel Value Differencing ◽  
The Relationship ◽  
Embedding Rate

The least-significant-bit based approach is a popular type of stenographic algorithms in the spatial domain. However, we find that in most existing approaches, the choice of embedding positions within a cover audio mainly depends on a pseudorandom number generator without considering the relationship between the audio content itself and the size of the secret message. In this paper, we expand the least significant bit matching revisited audio stegnography and propose an edge adaptive scheme which can select the embedding regions according to the size of secret message and the difference between two consecutive pixels in the cover audio. For lower embedding rates, only sharper edge regions are used while keeping the other smoother regions as they are. When the embedding rate increases, more edge regions can be released adaptively for data hiding by adjusting just a few parameters. New scheme can enhance the security significantly compared with typical least significant bit-based approaches as well as their edge adaptive ones, such as pixel-value-differencing-based approaches, while preserving higher visual quality of stegno audios at the same time.  

STEGANOGRAPHIC SCHEME FOR GRAY-LEVEL IMAGE USING PIXEL NEIGHBORHOOD AND LSB SUBSTITUTION

2010 ◽  
Vol 10 (04) ◽  
pp. 589-607 ◽  
Author(s):  
NAGARAJ V. DHARWADKAR ◽  
B. B. AMBERKER
Keyword(s):  
Image Processing ◽  
Secret Message ◽  
Gray Level ◽  
Embedding Capacity ◽  
Least Significant Bit ◽  
Secret Communication ◽  
Gray Level Image ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Lsb Substitution

The exchange of secret message using images has vital importance in secret communication. Steganographic scheme is employed to achieve the task of secret message communication using images. The existing scheme based on pixel value differencing (PVD) with least significant bit (LSB) sequential substitution suffer from low embedding capacity. The embedding capacity is increased by using the edge regions of image obtained by neighborhood connectivity of pixel. We propose an adaptive steganographic scheme for gray-level images. Our scheme relies on the neighborhood connectivity of pixels to estimate the embedding capacity and resolves the problem of sequential substitution by jumbling the bits of secret message. The effect of cropping and filtration attacks on stegoimage is minimized by embedding the copies of secret message into four different regions of the cover image. The performance of the scheme is analyzed for various types of image processing attacks like cropping, blurring, filtering, adding noise, and sharpening. The proposed scheme is found rigid to these attacks.

scholarly journals KAJIAN METODE METODE STEGANOGRAFI PADA DOMAIN SPASIAL

2020 ◽  
Vol 5 (2) ◽  
pp. 259-264
Author(s):  
Gunawan Wibisono ◽  
Tri Waluyo ◽  
Erik Iman Heri Ujianto
Keyword(s):  
Communication Technologies ◽  
Spatial Domain ◽  
Secret Message ◽  
Security Threats ◽  
Least Significant Bit ◽  
Spatial Domains ◽  
Pixel Value ◽  
Color Pixel ◽  
Pixel Value Differencing ◽  
Privacy Issues

This paper contains a review of the spatial domain steganographic literature. The purpose of this paper is to provide knowledge about techniques or methods that exist in the spatial domain of steganography. Steganography is the science or technique for hiding secret messages in other messages so that the existence of the secret message cannot be accessed by others who do not have authority. There are several popular spatial domains of steganographic techniques, namely LSB (Least Significant Bit), which is mapping secret message bits in the rightmost bit (LSB) of each color pixel and PVD (Pixel Value Differencing) which in this method offers a larger message storage capacity , with better image quality compared to other methods in the spatial domain. Because privacy issues continue to develop along with various digital communication technologies, and increasingly strong security threats, steganography can play a role in society to maintain the confidentiality of both picture, voice and video messages. For this reason it is important for us to be aware of steganographic technology and its implications.

scholarly journals High Capacity Image Steganography Using Modified LSB Substitution and PVD against Pixel Difference Histogram Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Gandharba Swain
Keyword(s):  
Boundary Problem ◽  
High Capacity ◽  
Experimental Results ◽  
Least Significant Bit ◽  
Rs Analysis ◽  
Distortion Measure ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Difference Histogram ◽  
Lsb Substitution

The combination of pixel value differencing (PVD) and least significant bit (LSB) substitution gives higher capacity and lesser distortion. However, there are three issues to be taken into account: (i) fall off boundary problem (FOBP), (ii) pixel difference histogram (PDH) analysis, and (iii) RS analysis. This paper proposes a steganography technique in two variants using combination of modified LSB substitution and PVD by taking care of these three issues. The first variant operates on 2 × 3 pixel blocks and the second technique operates on 3 × 3 pixel blocks. In one of the pixels of a block, embedding is performed using modified LSB substitution. Based on the new value of this pixel, difference values with other neighboring pixels are calculated. Using these differences, PVD approach is applied. The edges in multiple directions are exploited, so PDH analysis cannot detect this steganography. The LSB substitution is performed in only one pixel of the block, so RS analysis also cannot detect this steganography. To address the FOBP, suitable equations are used during embedding procedure. The experimental results such as bit rate and distortion measure are satisfactory.

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>

Sign in / Sign up

Export Citation Format

Share Document