scholarly journals Statistical feature-based steganalysis for pixel-value differencing steganography

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Wen-Bin Lin ◽  
Tai-Hung Lai ◽  
Ko-Chin Chang
Keyword(s):  
Security Analysis ◽  
Least Significant Bit ◽  
Stego Image ◽  
Statistical Feature ◽  
Accuracy And Precision ◽  
Rs Analysis ◽  
Feature Based ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Difference Histogram

AbstractPixel-value differencing (PVD) steganography is a popular spatial domain technology. Several PVD-based studies have proposed extended PVD steganography methods. The majority of these studies have verified their security against the regular-singular (RS) analysis. However, RS analysis is aimed at the feature of the least significant bit substitution method, which is relatively less significant for PVD steganography. The pixel difference histogram (PDH) is generally utilized to attack PVD steganography. If the embedding capacity is high, then the features on the PDH are evident; otherwise, the features are less obvious. In this paper, we propose a statistical feature-based steganalysis technique for the original PVD steganography. Experimental results demonstrate that, compared with existing steganalysis technique with weighted stego-image (WS) method, the proposed method effectively detects PVD steganography at low embedding ratios, such that there is no need of using the original embedding parameters. Furthermore, the accuracy and precision of the method are better than those of existing PVD steganalysis techniques. Therefore, the proposed method contributes to the security analysis of the original PVD steganography as an alternative to the commonly used RS, PDH and WS attack techniques.

Statistical Feature–Based Steganalysis for Pixel-Value Differencing Steganography

2021 ◽  
Author(s):  
Wen-Bin Lin ◽  
Tai-Hung Lai ◽  
Ko-Chin Chang
Keyword(s):  
Least Significant Bit ◽  
Stego Image ◽  
Image Steganalysis ◽  
Detection Analysis ◽  
Suitable Parameter ◽  
Feature Based ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Difference Histogram ◽  
Advance Knowledge

Abstract The security and embedding capacity of pixel-value differencing (PVD) steganography is superior to that of least significant bit replacement steganography. Several studies have proposed extended PVD steganography methods that use the original concept of PVD steganography. The majority of the studies have verified their security against regular-singular detection analysis or pixel difference histogram attacks. Weighted stego image steganalysis is the state-of-the-art technology for PVD steganography. This study proposed a suitable parameter for the estimator based on different relative embedding ratios and the size of normal embedding blocks. The experimental results revealed that the proposed technology does not require advance knowledge of the original image. In addition, the proposed method is accurate and precise at any embedding ratio. In the future, this method may be utilized to analyze the security of extended PVD steganography.

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.

scholarly journals Digital Image Steganography Using Eight-Directional PVD against RS Analysis and PDH Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Gandharba Swain
Keyword(s):  
Least Significant Bit ◽  
Hiding Capacity ◽  
Central Pixel ◽  
Rs Analysis ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Difference Histogram ◽  
Lsb Substitution

The least significant bit (LSB) substitution techniques are detected by RS analysis and the traditional pixel value differencing (PVD) approaches are detected by pixel difference histogram (PDH) analysis. The PVD steganography can escape from PDH analysis by using the edges in multiple directions. This paper proposes a steganography technique by exploiting the edges in eight directions and also using LSB substitution to resist from both RS analysis and PDH analysis. For every 3×3 pixel block the central pixel is embedded with 3 or 4 bits of data by modified LSB substitution technique. Then this new value of the central pixel is utilized to calculate eight difference values with eight neighboring pixels. These eight difference values are used to hide the data. There are two types with regard to two different range tables. Type 1 uses 3 bit modified LSB substitution and range table 1. Type 2 uses 4 bit modified LSB substitution and range table 2. Type 1 and type 2 are also known as variant 1 and variant 2, respectively. Type 1 possesses higher PSNR and type 2 possesses higher hiding capacity.

Steganography Using LSB Substitution and Pixel Value Differencing

2019 ◽  
pp. 108-135
Keyword(s):  
Block Size ◽  
Experimental Results ◽  
Value Differences ◽  
Central Pixel ◽  
Rs Analysis ◽  
Pixel Value ◽  
Addition And Subtraction ◽  
Pixel Value Differencing ◽  
Difference Histogram ◽  
Lsb Substitution

This chapter describes four techniques that use both the principles of LSB substitution and pixel value differencing (PVD). These techniques use 1×3, 2×2, 2×3, and 3×3 size pixel blocks. In a block, LSB substitution is applied on one of the pixels, which is designated as the central pixel. Using the new value of this central pixel, pixel differences are computed with all its neighboring pixels. Based on these pixel value differences, embedding capacity is decided, and embedding is performed by addition and subtraction operations. The experimental results reveal that when the block size increases, the tolerance to RS analysis and pixel difference histogram (PDH) analysis also increases.

Steganography Techniques Based on Modulus Function and PVD Against PDH Analysis and FOBP

2019 ◽  
pp. 157-184
Keyword(s):  
Signal To Noise Ratio ◽  
Experimental Results ◽  
Modulus Function ◽  
Evaluation Function ◽  
Embedding Capacity ◽  
Least Significant Bit ◽  
Rs Analysis ◽  
Block Data ◽  
Pixel Value ◽  
Pixel Value Differencing

This chapter proposes two improved steganography techniques by addressing two problems in the existing literature. The first proposed technique is modulus function-based steganography and it addresses pixel difference histogram (PDH) analysis. The modulus function is used to calculate an evaluation function and based on the value of the evaluation function embedding decision is taken. There are two variants of this technique: (1) modulus 9 steganography and (2) modulus 16 steganography. In modulus 9 steganography, the embedding capacity in a pair of pixels is 3 bits, and in modulus 16 steganography the embedding capacity in a pair of pixels is 4 bits. Both the variants possess higher PSNR values. The experimental results prove that the PDH analysis cannot detect this technique. The second proposed technique is based on pixel value differencing with modified least significant bit (MLSB) substitution and it addresses fall off boundary problem (FOBP). This technique operates on 2×2 pixel blocks. In one of the pixels of a block data hiding is performed using MLSB substitution. Based on the new value of this pixel, three difference values with three neighboring pixels are calculated. Using these difference values, PVD approach is applied. Experimental results prove that the PDH analysis and RS analysis is unable to detect this proposed technique. The recorded values of bit rate and peak signal-to-noise ratio are also satisfactory.

scholarly journals Image Steganography Using Pixel Value Differencing (PVD) Technique Based on Firefly Algorithm

2021 ◽  
pp. 80-86
Author(s):  
Oluwaseun M. Alade ◽  
Elizabeth A. Amusan ◽  
Oluyinka T. Adedeji ◽  
Oluwaseun O. Alo
Keyword(s):  
Firefly Algorithm ◽  
Promising Result ◽  
Signal To Noise Ratio ◽  
Text Message ◽  
Image Steganography ◽  
Cover Image ◽  
Experimental Result ◽  
Stego Image ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography deals with the ways of hiding communicated data in such a way that it remains confidential. Finding best position inside cover image to embed text message, maintaining a reasonable trade-off between security, robustness, higher bit embedding rate and imperceptibility are some of the challenges of steganography system. Hence, this paper presents firefly algorithm for finding best positions inside cover image in order to embed text message into cover image using Pixel Value Differencing (PVD) technique. Four different cover image was used. Experimental result showed the cover image with selected location using firefly algorithm as well as the stego image using PVD technique. The stego image was evaluated using Peak Signal to Noise Ratio (PSNR) and Mean square Error (MSE).  Firefly Algorithm with PVD technique produced a promising result for image steganography.

A Review on LSB Substitution and PVD Based Image Steganography Techniques

2016 ◽  
Vol 2 (3) ◽  
pp. 712 ◽  
Author(s):  
Aditya Kumar Sahu ◽  
Gandharba Swain
Keyword(s):  
Information And Communication Technologies ◽  
Data Communication ◽  
Communication Technologies ◽  
Least Significant Bit ◽  
Hiding Capacity ◽  
Information And Communication ◽  
Distortion Measure ◽  
Pixel Value ◽  
Pixel Value Differencing ◽  
Lsb Substitution

<p>There has been a tremendous growth in Information and Communication technologies during the last decade. Internet has become the dominant media for data communication. But the secrecy of the data is to be taken care. Steganography is a technique for achieving secrecy for the data communicated in Internet. This paper presents a review of the steganography techniques based on least significant bit (LSB) substitution and pixel value differencing (PVD). The various techniques proposed in the literature are discussed and possible comparison is done along with their respective merits. The comparison parameters considered are, (i) hiding capacity, (ii) distortion measure, (iii) security, and (iv) computational complexity.</p>

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.  

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,

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