Least Significant Bit Substitution Research Articles

Invertible Color-to-Grayscale Conversion Using Lossy Compression and High-Capacity Data Hiding

Invertible color-to-grayscale conversion is a research issue in grayscale image colorization, which is a complex problem resulting from information loss. This paper presents an innovative invertible color-to-grayscale conversion idea by independently compressing the chromaticity plane and hiding it into the corresponding luminance plane as a watermark. Since the chromaticity and luminance planes are orthogonal in the proposed method, they can be processed efficiently without mutual influence. By using an efficient lossy compression operation, we can save more chromatic information. By using two high-capacity data hiding techniques (reversible watermarking (RW) and least significant bit (LSB) substitution), we can embed the compressed chromatic information into the luminance plane perfectly. For the purpose of integrality authentication, the luminance plane is hashed as part of the embedded information before the embedding. Experimental results have shown that higher quality of reconstructed color images can be achieved by using RW, but the quality of the synthesized grayscale drops sharply. By using LSB substitution, we can obtain high-quality synthesized grayscale and reconstructed color images simultaneously. Furthermore, we have compared the proposed LSB-based scheme with several recently reported state-of-the-art methods to validate the superiority of the proposed approach.

An interpolation based steganographic technique with least-significant-bit and pixel value differencing in a pixel block

Over the <span lang="EN-US">past few years, in order to improve the hiding capacity and the peak signal-to-noise ratio (PSNR) value, several steganographic techniques have been developed. Steganography has become a popular technique to transmit secret data through any medium. In image steganography, the human eye cannot easily identify the hidden data which is embedded into the image. Small changes are also not detected by the human eye. High hidden capacity along with high visual quality is provided by the pixel value differencing (PVD) method. This paper first proposes the method of interpolation between the pixel blocks and then applies the least-significant-bit (LSB) substitution technique with the PVD method. At the starting phase, the original image is fixedto a 2x2 block, then the nearest neighbor interpolation (NNI) technique is implemented. In the next phase, the upper left pixel isembedded by the k-bit LSB substitution method along with hidden data. The newly generated neighbouring pixel value is measured. Thus, data is hidden from three directions. Through this paper using two different range tables, the new algorithm is proposed. We observed that in both cases, PSNR and the hiding capacity are improved.</span>

Hiding Secrets in Electrocardiogram Based on Integer Wavelet Transform with Coefficient Adjustment and LSB Substitution

In this paper, we present an efficient data hiding for electrocardiogram (ECG) hosts to solve the issues of existing ECG steganographic methods, which have less hiding capacity and insufficient signal-to-noise ratio (SNR)/ peak SNR (PSNR). Based on the integer wavelet transform (IWT), private (or sensitive) data such as patients’ diagnosis and personal information can be embedded in an ECG host via the IWT coefficient adjustment and the least significant bit (LSB) technique. Simulations indicated that the SNR (or PSNR), and payload of the proposed method outperform those of existing techniques. In addition, the proposed method is capable of resisting attacks, such as cropping, Gaussian noise-addition inversion, scaling, translation, and truncation attacks from third parties (or adversaries). Since the proposed method has low computational complexity, our method can be employed in portable biometric devices or wearable electronics.

A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method

Communication has become a lot easier in this era of technology, development of highspeed computer networks, and the inexpensive uses of Internet. Therefore, data transmission has become vulnerable to and unsafe from different external attacks. Every communication body wants to secure their data while communicating over the Internet. The internet has various benefits but the main demerit is the privacy and security and the transmission of data over insecure network or channel may happen. Various techniques used for secure communication in order to address these issues, steganography plays an important role. Steganography is the process of obfuscation that makes something incomprehensible and unclear. Different image steganography research methods are proposed recently but each has their advantages and disadvantages and still have necessity to develop some better image steganography mechanisms to achieve the reliability between the basics criteria of image steganography. Therefore, the proposed work, in this paper, is based on the Least Significant Bit (LSB) substitution method. The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. In this paper, we proposed a novel technique in steganography within the digital images such is RGB, Gray Scale, Texture, Aerial images to achieve higher security, imperceptibility, capacity, and robustness as compared with existing methods. The experimental outcomes of the suggested approach prove further developed strength and justify the feasibility of our research. Through numerical simulations, we observed that the proposed strategy outperformed the next-best current methodology by 5.561 percent in terms of PSNR Correlation score. Additionally, the proposed approach achieved a 6.43 percent better score in PSNR with a variable measure of code inserted in similar images with distinct dimensions. Furthermore, encrypting the same amount of information in images of varying sizes resulted in approximately 6.77 percent improvements. Embedding different sizes of a particular secret message in a different image (such as Gray, Texture, Aerial and RGB images) came out with about 5.466 percent of better score.

Scrambling Based Riffle Shift on Stego-Image to Channelize the Ensured Data

In recent years information hiding has got much attention as it acts as an alternate option for secured communication. The Secret content would get imbedded with the image using various possible image embodiment techniques, in which the Least Significant Bit (LSB) substitution is one of the preferred content embodiment strategy; however, asserting the quality and the originality of the content embedded image (stego) is yet a grievous concern in the field of Information Security. In this article, a proficient Scrambling Based Haar Wavelet Transform (SBHWT) approach has been sought to ensure the novelty of the stego-image that supports the safe transfer of data over the channel. In this process, the image is scrambled using a Sudoku pattern, and then streams of the secret content are embedded into the image blocks based on the proposals of the Bishop Traversal logic of chess. The content embodiment is attempted using normal LSB substitution and DNA pattern based substitution. Next, the image is descrambled to recover the original image, which is then subjected to Haar wavelet transformation for image resolution reduction. The resultant reduced image is channelized to the recipient and the inverse action of the SBHWT is made in order to get back the secret code stream. The experimental results demonstrate that the projected SBHWT approach is less predictable and exclusive in its pattern.

Data Hiding Technique for Color Images using Pixel Value Differencing and Chaotic Map

The huge advance in information technology and communication resulted in extreme usage of digital networks that makes information security playing an important role as never before. Steganography is the art of hiding secret message bits into different multimedia data using either spatial domain or frequency domain to provide security for the transferred information against unauthorized access. Most of the techniques that apply Pixel Value Differencing approach (PVD) depend on sequential embedding manner, which lacks security. In the proposed method, a complex chaotic map is used to randomly choose the coefficients pairs for embedding the secret message. First, the cover image is transformed using IWT. Then, the embedding process starts in the highest frequency band of IWT and continues to the next sub-bands. Adaptive embedding is performed according to intensity variation between pixel pairs using PVD and Least Significant Bit substitution (LSB). Non-sequential embedding performed by using chaotic map lets the method more secure. The experimental results show that the proposed technique achieves high PSNR with improved capacity compared to other techniques.

RSA Over-Encryption Employing RGB Channels through a Steganography Variant

This study aims to provide a solution for RSA over-encryption based on steganography variant to hide sensitive information that requires security. The current study describes a software program's implementation phases that allow technicians to re-encrypt a message, first encoded using RSA cryptosystems as an extra security layer. Subsequently, this text was converted into an array of bytes stored in Red, Green, and Blue (RGB) layers of one or more generated images, which will finally be sent to the receiver. The programming recursion technique was used to determine the number of images that need to be sent and the bytes corresponding to each of them. These images were created, reorganized, and encrypted according to pre-defined rules. The security of the proposed method relies heavily on the probability theory. Each of the possible patterns that can store data is equally likely to be chosen by an attacker. The program also uses as a conceptual base the Least Significant Bit Substitution (LSB) technique, with the difference that it directly stores bytes for the RGB values of the generated image(s). Our results indicate that the re-encryption is independent of a carrier image. The number of different ways to organize the pixels and the generated images suggests an acceptable security level. Moreover, it requires a not negligible computational power to decipher the pixels' original order and the channels containing relevant information.

Inverted LSB image steganography using adaptive pattern to improve imperceptibility

Various image steganography methods have been developed to improve the stego image quality, i.e. imperceptibility, capacity, and security. This research proposes an adaptive method that can select the most optimal pattern to minimize the error ratio due to message embedding. This adaptive pattern can optimize the performance of the inverted LSB substitution method, based on the two-bit + least-significant-bit (LSB) pattern in the container image. Before embedding, the message and container image bits are tested and the error ratio is calculated using the inverted LSB substitution method for various possible patterns. The pattern that has the least error rate is selected to embed the message. The use of this adaptive pattern in inverted LSB image steganography significantly increases imperceptibility. Based on the test results and by comparing it to previous studies, it is found increased results, the PSNR value ranges from 52.49 to 57.45, and the SSIM ranges from 0.9991 to 0.9999 with 1 BPP capacity.

A novel triple recovery information embedding approach for self-embedded digital image watermarking

Image tamper detection and recovery has become an important issue in recent years. In order to detect and recover high tampering rated images, this paper presents a novel self-embedded fragile watermarking method with triple recovery information embedding approach. In this proposed method host image is divided into sixteen main blocks. Four partner blocks are selected from main blocks as a partner group using Look-Up table which is constructed for recovery against high tampering rated images. Each partner block is divided into 4 × 4 blocks. Recovery data of each partner block is generated from the mean values of the 4 × 4 blocks. Then, triple recovery information for each partner block is constructed by combining recovery data of the three other partner blocks. After the generation of the recovery information, each partner block is divided into 16 × 16 blocks. Then, these blocks are divided into four 8 × 8 sub-blocks. Recovery bits for each partner block are embedded into the first and second least significant bits (LSBs) of the first three sub-blocks. It means that triple copies of recovery information for each partner block are embedded into three other blocks in the image, which provides triple chance for recovery of the tampered areas. On the other hand, authentication information is generated from the pixels of the 16 × 16 recovery information embedded image blocks by using MD5 hash function. This authentication information is embedded into the quarter part of each 16 × 16 block by using LSB substitution. The performance of the proposed method has been demonstrated by applying different size of cropping attacks to the different areas of the watermarked images. Experimental results show that the proposed method satisfactory recovers up to 75% tampering rated images.

Robust approach of video steganography using combined keypoints detection algorithm against geometrical and signal processing attacks

To secure the secret communication, a robust video steganography algorithm is proposed. The major objectives of the proposed method (PM) are: (1) perceiving the region of interest (ROI) keypoints’ locations in video frames for concealing the secret data and (2) determining the appropriate amount of data to be embedded into the perceived ROI keypoints’ region. In the PM, keypoints are initially extracted from each video frame using scale-invariant feature transform (SIFT) and a speeded-up robust features (SURF) descriptor against a set of predefined geometrical and signal processing attacks. Next, ROI keypoints are generated by comparing the SIFT and SURF keypoint descriptors of the original frame and attacked versions of the frame. Then ROI keypoints are divided into four least significant bit (LSB) groups to determine the embedding capacity of each ROI keypoint. Subsequently, the secret data are encrypted using a symmetric key-based shift cipher to provide an additional security layer for secret communication. Finally, the encrypted secret data have been embedded into the ROI keypoints using the LSB substitution method based on the four LSB groups’ values. The PM is tested on 22 standard benchmark videos. The efficiency of the PM is evaluated in terms of the perceptual invisibility, robustness, and concealing capacity. From experimental results, it is observed that the PM outperforms contemporary methods by attaining significant outcomes.

A Novel Image Steganographic Method based on Integer Wavelet Transformation and Particle Swarm Optimization

Image steganography is a technique of hiding secret data into a cover image and so as to prevent the intruders from accessing the secret data. The efficiency of image steganography techniques are usually evaluated based on perceptual transparency, payload capacity, security, temper resistance and computational costs. Though there has been significant improvement in related research over the decades, available steganographic techniques usually satisfy only a subset of these criteria. This paper presents a novel IWT (Integer Wavelet Transform) based steganography method using PSO (Particle Swarm Optimization) to find the optimal substitution matrix for converting secret data into their substituted forms. In the proposed method, optimal pixel adjustment process is used to improve perceptual transparency so that the obtained stego image has low distortion. The proposed method improves the security, imperceptibility, and robustness of the secret data by hiding them into the wavelet coefficients of an image. Thus, the paper provides a detailed study of the use of PSO in three different image steganographic methods based on (i) LSB (Least Significant Bit) substitution, (ii) DWT (Discrete Wavelet Transform), and (iii) IWT. Experiments are conducted using well-known benchmark images and results are comparatively analyzed. It is found that our proposed approach of PSO based IWT outperforms both PSO based LSB and PSO based DWT from the context of standard quality metrics, statistical analysis, security level estimation, payload capacity, imperceptibility etc. We have also provided a comparative overview of the existing data hiding methods including the proposed approach.

Adaptive PVD and LSB based high capacity data hiding scheme

In this paper, a new data hiding scheme using a mixture of adaptive pixel value differencing (PVD) and least significant bit substitution (LSB) is proposed for increasing the data hiding capacity. The scheme is a generalization of Jung (J Real-Time Image Proc. 14:127–36, 2018) which is the first work to use PVD and LSB methods simultaneously on a single image. However, the PVD used by Jung (J Real-Time Image Proc. 14:127–36, 2018) is not an adaptive method means it does not consider the vertical and diagonal edges of the image for hiding the secret data. In the proposed scheme, the vertical and diagonal edges in addition to horizontal edges are used for hiding the secret data so that a large amount of secret data is hidden without any perceived change. Experimental results show that the performance of the proposed scheme is superior to the existing schemes in terms of both data hiding capacity and image quality. Moreover, it is very simple as it does not require much computation for embedding the secret data.

Steganography Using Quotient Value Differencing and LSB Substitution for AMBTC Compressed Images

In this paper, we apply quotient value differencing (QVD) and least significant bits (LSBs) substitution to hide secret data in an absolute moment block truncation coded (AMBTC) image. An AMBTC compressed image block consists of a high mean, low mean, and bitmap matrix. Based on the data structure of an AMBTC block, the proposed method includes three phases of embedding. In the first phase, QVD and LSB substitution are applied to embed secret digits into the low mean and high mean values. In the second phase, an additional bit is embedded by alternating the order of the low mean and high mean or not. Secret digits are embedded in the third phase by substituting the bitmap of smooth blocks. By leveraging the entire data structure of the AMBTC compressed code, the proposed method outperforms related works in embedding capacity.

Homomorphic Encryption-Based LSB Substitution for High Capacity Data Hiding in the Encrypted Domain

During the last few decades, multimedia security over the cloud has become a major issue. Public-key homomorphism is an efficient approach for data hiding in encrypted images (DHEI). An original image is encrypted using a public key and sent across a network and then processed to embed a secret message directly in the encrypted domain. During the decoding step, a private key is used to obtain a marked reconstructed image, where the secret message can be extracted. In this paper, we propose an efficient method of DHEI based on the Paillier cryptosystem. Using its homomorphic properties, pixel blocks and bits of the message are multiplied in the encrypted domain resulting in an addition in the clear domain. By applying a pre-processing step on the original image before encryption, this addition becomes a least significant bits (LSB) substitution. Experimental results show that using our proposed scheme, we obtain a high payload value ( $1~bpp$ ) without expanding a lot the original image size contrary to current state-of-the-art methods. Indeed, whatever the key size, the expansion rate is always equal to 2. In addition, the original image and the marked reconstructed image are very similar.

High Embedding Capacity Data Hiding Technique Based on EMSD and LSB Substitution Algorithms

Data hiding called steganography is a security technique to protect secret data throughout the transmission from malicious attackers. The purposes of steganography are to obtain good stego-image quality, high embedding-capacity, low computational complexity, visual imperceptibility, undetectability, and more security. In this paper, we offer a new hybrid image steganography technique based on least significant bit (LSB) substitution and enhanced modified signed digit (EMSD) algorithms. The proposed algorithm utilizes n adjacent cover image pixels to hide the secret data with EMSD algorithm, and least significant k-bit for LSB substitution algorithm. Hence, it has more embedding capacity than the EMSD algorithm and exploiting modification direction (EMD) based algorithms. We obtain that the stego-image quality is better than 43 dB when the payload is 2.404 bpp. The results of experiment represent that this algorithm ensures high embedding-capacity while preserving acceptable visual stego image quality that can be undetectable by human eyes. Also, the hybrid of the EMSD and LSB substitution algorithms is to difficult for malicious people to consolidate data by scrambling secret data bits.

Enhanced payload and trade-off for image steganography via a novel pixel digits alteration

Many high capacity image steganography algorithms have been proposed but at the cost of lower imperceptibility. To fill the gap, this paper proposes a novel RGB image steganography technique that not only enhances the hiding capacity but also largely improves the trade-off between capacity and imperceptibility on maximum embedding rate. The technique encrypts the secret data (text, grayscale or a color image) into a sequence of two-digit decimal values. A digit in the sequence is hidden in a cover pixel by altering the pixel’s digits to the nearest pixel value possible. Most common spatial hiding techniques are the Least Significant Bit (LSB) substitution and Pixel Value Differencing (PVD) which hide data in the form of bits. The proposed linear time digit based hiding technique outperforms LSB substitution, PVD or their variants in terms of both capacity and imperceptibility. It also outperforms the existing digit hiding methods in color images. Moreover, the method is secure against the two detection schemes of Weighted Stego-Image steganalysis.

An efficient steganographic technique for hiding data

Steganography is the technique for hiding data and aims to hide data in such a way that any eavesdropper cannot observe any changes in the original media. The least significant bit (LSB) is one of the most public techniques in steganography. The classical technique is LSB substitution. The main idea of this technique is to directly alter some LSB of the cover image with the secret data. The essential drawback of the available LSB techniques is that increasing the capacity of the stego image leads to decreasing its quality. Therefore, the goal of the proposed method is to enhance the capacity taking high visual quality into consideration. To achieve this goal, some LSB of the cover image are inverted depending on the secret data for embedding instead of replacing LSB with the secret data. First, the maximum and minimum values in the secret data are determined then subtract all values of the secret data from this maximum value. Finally, make a division for the results and embed the new results into the cover image to obtain the stego image. The results show that the proposed method gives high capacity and good imperceptibility in comparison with the previous methods.

Steganography Technique with Huffman Code

The growth of modern communication technologies imposes a particular means of security mechanisms in particular in case of data networks. In order to protect sensitive data while these are en route, applications call up different methods. Here we are trying to code the message by Huffman coding technique and applying the Steganography using differencing and substitution mechanisms with encryption to the original message which can give multi label security. Here we are trying to communicate in two phases such as (1) Encrypt the message by Huffman code and (2) applying the In Steganography. We divide the image into multiple blocks which are non-overlapped in nature and the block size is 3×3 pixel that will consider as matrix. For every value from the matrix can be represented in eight bit where two bit will use as least significant bit (LSB) substitution and quotient value differencing (QVD) is applied for other bits. We are trying to process in three levels: (i) Huffman tree through message is encrypted which is secret (ii) LSB substitution at lower bit planes and (iii) QVD at higher bit planes.

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.

Adaptive LSB quantum watermarking method using tri-way pixel value differencing

As an important way to protect copyright by embedding watermark in digital images, quantum watermarking catches more and more attentions. In this study, a novel quantum watermarking method on the basis of tri-way pixel value differencing and modified least significant bit (LSB) substitution is proposed. A quantum cover image using the novel-enhanced quantum image representation is partitioned into non-overlapping 2 × 2 blocks with four pixels firstly. To classify the block as a smooth area or an edge area, the tri-way pixel value differences are calculated and compared with a predefined threshold. The quantum watermark image, which is expanded and scrambled, is then embedded into a quantum cover image by the k-bit LSB substitution method, where k is decided by the level of each block. The embedded quantum watermark can be extracted from the quantum stego-image without the assistance of original quantum cover image. Theoretical analysis and simulation-based experiments demonstrate both the feasibility and capabilities of the proposed quantum watermarking method, which has good visual quality, better robustness, and higher security.