Adaptive Least Significant Bit Research Articles

Enhanced adaptive data hiding method using LSB and pixel value differencing

High embedding capacity is considered as one of the significant challenges in information hiding. In the spatial domain, most of the high capacity based strategies employed the least significant bit (LSB) and pixel value differencing (PVD) techniques. However, these are suffered from the incorrect recovery of secret data, inefficient utilization of pixel intensities, and limited usage of pixel difference range table. In this paper, a new solution is proposed to alleviate the shortcoming by exploiting the pixel intensities ranges for high embedding rates while achieving the 100% recovery of secret data in the extraction phase. The proposed method divides the pixels into non-overlapping pixels block; further, compute the pixels differences along with respective ranges to determine the size of secret bits for the underlined adaptive LSB embedding process. In the extensive experiments, the proposed scheme outperforms the embedding capacity and maintains acceptable visual imperceptibility at various embedding rates, and also shows successfully the resistance against RS analysis and machine learning-based detection attacks.

An efficient reversible ECG steganography by adaptive LSB approach based on 1D FDCT domain

Based on the processing of one-dimensional fast discrete cosine transform (1D FDCT) coefficients, we present an efficient reversible data hiding method for electrocardiogram (ECG) signal. The proposed method is implemented in two phases. The purpose of phase-I is to classify the FDCT (host) bundles, where each input bundle will be attributed to one of four different bundles. The aim of phase-II is to embed data bits in the selected coefficients of the classified bundles according to a predetermined bit-index table (which generated from phase-I) via adaptive least significant bit (LSB) technique. Simulations confirmed that hidden bits were extracted without distortion and the original ECG signal can be completely recovered. Furthermore, a good perceived quality and a hiding capacity superior to existing techniques were achieved. Moreover, our method is robust against attacks such as noise addition, inversion, truncation, translations, and so on. Notice that the robustness is rarely seen in conventional reversible ECG steganography methods. Since this method has a fast computation speed, it is feasible for real-time applications and can be installed in the health care devices such as the wearable ECG measure equipment.

Image steganography based on LSB substitution and encryption method: adaptive LSB+3

The goals of image steganography are to simultaneously reach maximum embedding capacity, enhanced embedding efficiency, better image quality, and more security. We present a two-step data hiding method that improves image quality, capacity, and embedding efficiency, and also provides stego security. In the first step of the proposed method, the hidden data are encrypted with the key words and shifting method to provide security. In the second stage, we propose adaptive least-significant-bit (LSB)+3 type I and adaptive LSB+3 type II methods to hide encrypted data in the cover image. The image quality of the stego image obtained from the proposed adaptive LSB+3 method is better than the traditional three-bit LSB methods. When maximum data are embedded in the cover image, a peak signal-to-noise ratio (PSNR) greater than 41 dB is reached. Experimental studies show that adaptive LSB+3 type I and adaptive LSB+3 type II methods are higher PSNR values (3.48% and 5.73%) than the standard three-bit LSB substitution methods.

Data hiding using adaptive LSB and PVD technique resisting PDH and RS analysis

This paper proposes an improved data hiding technique using the principle of least significant bit (LSB) substitution and pixel value differencing (PVD). It addresses two issues: 1) the error block problem (EBP); 2) the fall of boundary problem (FOBP). The image is divided into non-overlapping blocks of two consecutive pixels. The blocks are divided into three levels depending upon the pixel value difference. The level of the block and the pixel difference range decides the hiding capacity of a block. The proposed technique has been compared with related existing techniques in terms of parameters like peak signal to noise ratio (PSNR), quality index (Q), hiding capacity, bits per pixel (BPP), and the count of the blocks suffering from FOBP. The experimental results prove that the proposed technique offers better PSNR and hiding capacity as compared to the related existing techniques. Furthermore, the proposed technique is resistant to pixel difference histogram (PDH) analysis and RS analysis.

Design and Implementation of Lifting Based Wavelet and Adaptive LSB Steganography to Secret Data Sharing Through Image on FPGA

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.

Hybrid Data Hiding Scheme Using Right-Most Digit Replacement and Adaptive Least Significant Bit for Digital Images

The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR) with an adaptive least significant bit (ALSB) is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns) and higher texture (asymmetry patterns) areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS) steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images) are conducted with recent least significant bit (LSB)-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits) while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR)).

Improved LSB based Steganography Techniques for Color Images in Spatial Domain

This research paper aims to propose a new improved approach for Information Security in RGB Color Images using a Hybrid Feature detection technique; Two Component based Least Significant Bit (LSB) Substitution Technique and Adaptive LSB substitution technique for data hiding. Advanced Encryption Standard (AES) is used to provide Two Tier Security; Random Pixel Embedding imparts resistant to attacks and Hybrid Filtering makes it immune to various disturbances like noise. An image is combination of edge and smooth areas which gives an ample opportunity to hide information in it. The proposed work is direct implementation of the principle that edge areas being high in contrast, color, density and frequency can tolerate more changes in their pixel values than smooth areas, so can be embedded with a large number of secret data while retaining the original characteristics of image. The proposed approach achieved Improved Imperceptibility, Capacity than the various existing techniques along with Better Resistance to various Steganalysis attacks like Histogram Analysis, Chi-Square and RS Analysis as proven experimentally.

Chaos-based Spatial Steganography System for Images

In this paper, we propose a chaos-based enhancement of two spatial steganographic algorithms; the AE-LSB and the EA-LSBMR and our objective is to study their performances. The first algorithm is an adaptive LSB (Least Significant Bit) steganographic method using pixel value difference that provides a large embedding capacity and imperceptible stego images. The second method is an edge adaptive scheme which can select the embedding region according to the size of secret message and the difference between two adjacent pixels in the cover image. The two methods suffer from low security against attacks that try to recover secret data.To overcome this weakness, we propose to enhance the message security of these methods. The enhancement consists of using an efficient chaotic system in order to choose in a pseudo-chaotic manner the pixels in the cover image where the bits of the secret message will be embedded. In this way, the inserted message becomes secure against message recovery attacks and becomes as well spread over the whole image in a uniform manner. Experiments show that the security of the algorithms is increased.

A New Approach for Information Security using an Improved Steganography Technique

This research paper proposes a secured, robust approach of information security using steganography. It presents two component based LSB (Least Significant Bit) steganography methods for embedding secret data in the least significant bits of blue components and partial green components of random pixel locations in the edges of images. An adaptive LSB based steganography is proposed for embedding data based on the data available in MSB's (Most Significant Bits) of red, green, and blue components of randomly selected pixels across smooth areas. A hybrid feature detection filter is also proposed that performs better to predict edge areas even in noisy conditions. AES (Advanced Encryption Standard) and random pixel embedding is incorporated to provide two-tier security. The experimental results of the proposed approach are better in terms of PSNR and capacity. The comparison analysis of output results with other existing techniques is giving the proposed approach an edge over others. It has been thoroughly tested for various steganalysis attacks like visual analysis, histogram analysis, chi-square, and RS analysis and could sustain all these attacks very well.

A chaotic mapbased adaptive variable-size LSB method with pixel-value differencing and modulus function

In this paper, we present a least significant bit (LSB) hiding scheme that can embed variable-size secrets in LSB planes using the block-based chaotic map, adaptive difference range division, pixel-value differencing and modulus function. In particular, the block-based chaotic map in our framework is used to rearrange the locations of image blocks such that the transformed image can have more complex content than the original image; more precisely, the transformed image's inter-blocks have the low correlations while its intra-blocks have the high correlations. In addition, the adaptive division for difference range and pixel-value differencing are applied to separate smooth areas from edge areas for hiding different amounts of secrets in the pixels with the modulus function. The result of the proposed scheme is that the pixels located in the inter-blocks hide more secrets to enlarge the embedding capacity, and those located in the intra-blocks have fewer embedded secrets to maintain good visual quality. The effectiveness of our scheme is provided in experiments. The experimental results demonstrate that the proposed scheme is superior to the previous methods in providing a better embedding capacity with a good visual quality of the stego-image.

High Capacity Data Hiding in JPEG‐Compressed Images

The JPEG image is the most popular file format in relation to digital images. However, up to the present time, there seems to have been very few data hiding techniques taking the JPEG image into account. In this paper, we shall propose a novel high capacity data hiding method based on JPEG. The proposed method employs a capacity table to estimate the number of bits that can be hidden in each DCT component so that significant distortions in the stego-image can be avoided. The capacity table is derived from the JPEG default quantization table and the Human Visual System (HVS). Then, the adaptive least-significant bit (LSB) substitution technique is employed to process each quantized DCT coefficient. The proposed data hiding method enables us to control the level of embedding capacity by using a capacity factor. According to our experimental results, our new scheme can achieve an impressively high embedding capacity of around 20% of the compressed image size with little noticeable degradation of image quality.