A Novel Image Steganographic Method Based on Enhanced PIWT and Modified Optimal Pixel Adjustment Process

Steganography plays a vital role in the field of covert communication. This paper proposes a novel embedding scheme which embeds secret data adaptively. The proposed scheme employs integer to integer Lifting Wavelet Transforms (LWT) and pixel strength to specify suitable locations for data embedding. The integer LWT eliminates distortions, which is produced because of rounding process in the convolutional wavelet transforms. The performance of the proposed scheme is addressed using image quality metrics based on Peak Signal To Noise Ratio (PSNR) versus embedding ratio. Moreover, Bit Error Rate (BER) is utilized to assess robustness of the scheme. The experimental results show that the proposed is superior over several embedding techniques such as embedding based convolutional wavelet transforms and Lest Significant Bits (LSBs). The range of PSNR is gained between 51.52 and 22.15dB for range of embedding rate between 5% and 35%. Furthermore, the technique results error free for retrieving of secret data. In addition to the above features, the proposed technique increases security level of embedded data due to adaptive embedding process that increases randomly of embedding locations. The proposed scheme can be used in several important applications such as bank tag for authentication, military communications. Also, it can be implemented easily as a hardware chip and combine with covert imaging systems.

Image watermarking plays an important role in the field of medical image security and also provides a safe pathway for transfer of medical information through public networks such as internet. In this work, variable pixel and variable bit -medical image watermarking scheme has been proposed to protect the Electronic Patient Record (EPR). The proposed algorithm uses a Linear Feedback Shift Registers (LFSR) to generate pseudo random sequences for randomly selecting the image pixels of 16 bit Digital Imaging and Communications in Medicine (DICOM) image and modified logistic map has been utilized for selecting the bits to achieve adaptive Least Significant Bit (LSB) embedding. Integer Wavelet Transform (IWT) has been applied on original image to decompose it to its sub – bands where EPR has been embedded. The algorithm comprises four phases namely, pixel separation, random pixel selection, variable bit selection and LSB embedding. Proposed watermarking scheme has been achieved a near zero Mean Square Error (MSE) and histogram analysis confirms the imperceptibility of the algorithm. The algorithm requires only 0.235542 S to perform LSB embedding on 512 × 512 DICOM images. Peak Signal to Noise Ratio (PSNR), Normalized Cross Correlation (NCC) and Structural Similarity Index (SSIM) analyses also have been performed to evaluate the efficiency of the watermarking scheme.

Steganography is a technique for hiding secret data within digital media such as images, audio, and video without causing noticeable visual changes. In video media, this technique offers advantages because each frame can be utilized dynamically, resulting in a larger data embedding capacity. However, conventional methods such as fixed-number Least Significant Bit (LSB) embedding still face limitations in balancing visual quality, embedding capacity, and resistance to compression or noise. To address these challenges, this study proposes an Adaptive Video Steganography Method based on Multi-Bit LSB that employs brightness, texture, and motion analysis for each frame to determine the number of embedding bits adaptively. The system adjusts the embedding capacity according to the local characteristics of the video: areas with high texture or rapid motion are assigned more bits, while static or low-texture areas use fewer bits to preserve visual quality. After the embedding process, the video quality is evaluated using PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measurement) to assess its similarity to the original video. Experimental results show a PSNR value of 45.86 dB and an SSIM value of 0.9441, Thus, the proposed adaptive method proves to be efficient, robust against disturbances, and capable of maintaining data security without compromising visual quality, making it highly suitable for implementation in multimedia-based information security systems.

Watermarking is crucial for protecting medical images, guaranteeing data integrity and authenticity in telemedicine, especially for rural healthcare facilities with limited computational power. This paper introduces a lightweight watermarking scheme that performs a comparative study of Lifting Wavelet Transform (LWT) versus Discrete Wavelet Transform (DWT), both combined with Discrete Cosine Transform (DCT), to achieve optimal imperceptibility, robustness, and computational efficiency. The comparison of LWT and DWT is essential because LWT has lower computational complexity and memory usage, hence more appropriate for resource-limited environments than DWT, and without the use of Singular Value Decomposition (SVD) to further reduce processing requirements and improve compatibility with low-power devices. The suggested approach adopts adaptive embedding against texture complexity, secure synchronization patterns with m-sequences and Barker codes, and geometric correction utilizing ORB for guaranteed watermark extraction under attacks from JPEG compression, Gaussian noise attack, rotation attack, median filter attack, and Gaussian blur. A new error correction code interleaved with majority voting is employed to increase the watermark’s strength. Tested at various embedding strengths, the scheme attains Peak Signal to Noise Ratio (PSNR) values over 40 dB and Structural Similarity Index (SSIM) values above 0.95, signifying extremely little visual degradation. Low Bit Error Rates (BER) and high Normalized Correlation (NC) in various attack scenarios validate its success. This computational-friendly solution is designed to arm remote healthcare organizations with limited computer ability to reliably authenticate and attest to medical images, meeting severe telemedicine demands.

Many steganographic schemes based on popular least significant bit (LSB) embedding have been proposed. The embedding procedure is totally independent of pixel values due to the fact that only the LSB has to be altered. Other methods either randomly increment/decrement the pixel value or use a function to do so. Because of this, the maximum embedding capacity cannot exceed 1 bit per pixel (bpp). State-of-the-art steganographic schemes, such as edge adaptive (EA) and highly undetectable stego (HUGO), aim at such LSB-based approaches with the help of LSB-matching algorithms and, unlike classical steganography, are more concerned about the undetectability level of the stego image rather than the peak signal-to-noise ratio (PSNR) of the stego images. There is a trade-off between detectability and the embedding rate of the stego images. The larger the embedding rate, the higher the chance of detectability, and the opposite is also true. On the other hand, classical steganographic approaches aim for maximum embedding capacity (say 4 bpp) while their main ability is to provide greater PSNR values rather than undetectability. In this work, a novel modular steganographic scheme is proposed in a spatial domain that takes advantage of error images resulting from applying an image quality factor (the same as the ones used in JPEG compression) in order to find the pixels where the secret data could be embedded. We show that our proposed method is less detectable compared to the EA method. The proposed method is almost as undetectable as HUGO. The detectability level is evaluated by the most recent state-of-the-art steganalysis attack, called ensemble classifiers, with second-order subtractive pixel adjacency model features given as their input. In addition, the proposed method can embed up to 4 bpp, yet maintain a high PSNR value.

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)).

A secure image steganography algorithm based on least significant bit and integer wavelet transform

For any type of watermarking techniques imperceptibility, robustness, embedding capacity, security of hidden watermark data and good visual recovery of both cover, as well as watermark secret data, are the major issues. To solve these issues the selected frames of video and the secret data is divided into the equal number of parts and every part is mapped using adaptive pixel location mapping (APLM) algorithm to get watermarked video, hence the embedding capacity and security of hidden watermark data are increased. Furthermore, the proposed system also calculates the key security parameters like peak signal to noise ratio (PSNR), mean square error (MSE), histogram, structural similarity index module (SSIM) and cross-correlation factor (CCF) before watermarking, after watermarking and after recovering the secret data from watermarked video which are found to be identical, hence the proposed system is more insusceptible to any type of attack as compared to existing watermarking approaches.

As today’s world are switching to the digital media through the Internet and multimedia tools like Facebook, YouTube, Twitter and WhatsApp which consists of a number of videos, hence it always better to take urgent problems of such digitally transmitted video in terms of information security. The current video steganography approach is not so effective for imperceptibility, robustness, security of hidden secret data, embedding capacity and very good visual recovery of a secret as well as original data. Hence, to maintain the balance between these issues is another big challenge. This work employs a novel and efficient Field Programmable Gate Array (FPGA) implementation of audio, video crypto steganography using General Modified Secured Diamond Encoding (GMSDE) scheme. The new proposed scheme is based on Diamond Encoding (DE), Exploiting Modification Direction (EMD) and Adaptive Pixel Pairing Matching (APPM) algorithms called as General Modified Secured Diamond Encoding (GMSDE). The DE method is always used for k > 1 which produces distortion, less embedding capacity and security of hidden data. The GMSDE scheme changed the Diamond Characteristic Value (DCV) to conceal more than one secret bit vertically and horizontally to create a modified diamond shape of secret data which is equal to log2(2x2 + 6x + 5) - ary and produces the conceal capacity of 1.16 to 4.82 bpp for the values of x = 0 to 25 where x is the embedding parameter. Experimental results confirm that the conceal capacity measured by bit per pixel (bpp), security of hidden secret data, very good visual recovery of both original and secret data, Cross-Correlation (CC) and Peak Signal to Noise Ratio (PSNR) values are better than existing approaches. Further through many attacks on stego video during transmission using forensic detection approach, the imperceptibility, security of hidden data and robustness is increased for secure communication.

Reversible image watermarking schemes are used to protect ownership and copyrights of digital images. This paper proposes a novel reversible image watermarking scheme based on adaptive image interpolation, segmentation and additive prediction error expansion (PEE). Proposed interpolation comprises of weighted average of neighboring pixels by allocating higher and lower weights to less and more distant neighboring pixel values respectively. The proposed adaptive image interpolation focuses on detection of edges thus minimizing artifacts imposed by interpolation. The idea of embedding varying amount of watermark bits in different image segments has been explored. Simple linear iterative clustering (SLIC) based image segmentation is performed to separate very sharp, sharp, smooth and very smooth regions in image. Higher number of watermark bits are embedded in sharp regions by using additive prediction error expansion embedding technique. Simulations of proposed and existing techniques were performed on different images and compared using embedding capacity (EC), peak signal to noise ratio (PSNR), computational efficiency, image quality, mean square error (MSE), normalized cross correlation (NCC) and structural similarity index (SSIM). The experimental results show that proposed scheme achieves better results in terms of EC, PSNR, computational efficiency, image quality, MSE, NCC and SSIM as compared to existing techniques.

This paper introduces a best approach for Least Significant Bit (LSB) based on image steganography that enhances the existing LSB substitution techniques to improve the security level of hidden information. It is a new approach to substitute LSB of RGB true color image. The new security conception hides secret information within the LSB of image where a secret key encrypts the hidden information to protect it from unauthorized users. In general, in LSB methods, hidden information is stored into a specific position of LSB of image. For this reason, knowing the retrieval methods, anyone can extract the hidden information. In our paper, hidden information is stored into different position of LSB of image depending on the secret key. As a result, it is difficult to extract the hidden information knowing the retrieval methods. We have used the Peak Signal-to-Noise Ratio (PSNR) to measure the quality of the stego images. The value of PSNR gives better result because our proposed method changes very small number of bits of the image. The obtained results show that the proposed method results in LSB based image steganography using secret key which provides good security issue and PSNR value than general LSB based image steganography methods.

Background and Objective: The public and group communication carried out in the social, cloud, and mobile networks suffer from unauthorized users. The data security is required for secure authentication, monetary transactions and other sensitive information. The steganography methods empower the user with invulnerable communication in public domain. In this paper, a region secure and pattern based alternate 2B-3C (2Bit-3Channel) Steganography method is proposed to improve the content reliability and data security. Methods: In this method, the cover pixels are retrieved by applying the spiral rectangular pattern over the cover image. This spiral pattern also secures the core content region and the pixels from the core ROI (Region of Interest) is used as a cover only for larger size secret information. In this proposed steganography method, two channels are considered alternatively based on the defined rules. The LSB (Least Significant Bit) of both channels is XOR with input data bits and key to perform data hiding. The method is applied on real time color images taken from COREL and USC-SIPI-ID. The evaluation of proposed steganography approach is done using MSE (Mean Square Error), PSNR (Peak Signal-to-Noise Ratio), BER (Bit Error Rate), NCC (Normalized Cross Correlation) and SSIM (Structural Similarity Index Matrix). Result: The comparative results are generated for 50 real time images against the existing LSB (Least Significant Bit), LSBM (Least Significant Bit Modulation), LSBMR (Least Significant bit Matched Revisited), SCC (Stego Color Cycle), SHSI (Simple Hue-Saturation-Intensity), HIS-MLSB(Simple Hue-Saturation-Intensity-Modified LSB) and IMMEA(Iterative Magic Matrix Encryption Algorithm) methods. Conclusion: The experimentation results verified that the proposed 2B-3C approach improved the data hiding in qualitative and quantitative aspects.

Aim: This paper mainly focused on introducing a new framework for image and text hiding using a simple Least Significant Bit (LSB) substitution method.  Results: Six 24-bit images are used as reference images. XOR operation is used in the stego key to generate new bit planes of the stego images. An RGB color image is used as a secret cover image. The proposed method dramatically increases the embedding capacity without significantly decreasing the Peak Signal-to-Noise Ratio (PSNR) value.  Conclusion: This method increased the compression ratio, embedding ratio, PSNR and Space 24%, 53%, 36% and 47%, respectively. The result shows that the newly developed method improved the value of accuracy by 30% and sensitivity by 16% for the hidden images.  Keywords: LSB, PSNR, FNR (False Negative Rate), Sensitivity, MSE (Mean Square Error), Specificity HIGHLIGHTS: The newly developed method with simple Least Significant Bit (LSB) improved the accuracy value by 30%, and sensitivity by 16% for the hidden image. The improved LSB method increased security and preserved the quality of hidden images.

A significant data protection technique for a number of problems, the most prominent being identity authentication and copyright protection, is digital image watermarking. The rapid digital transformation of the world has given rise to a variety of vision modification techniques, which have significant consequences for picture data security. As a result, maintaining the validity and integrity of digital images is crucial, which is why researchers are focusing on creating effective watermarking techniques. This study proposes an optimized robust watermarking technique based on lifting wavelet transform (LWT) with singular value decomposition (SVD) using the particle swarm optimization (PSO) algorithm for achieving multiple scaling factors (MSF). To increase security and durability, cover images are exposed to numerous attacks. The evaluation criteria, which encompass normalized cross-correlation (NCC) and peak signal-to-noise ratio (PSNR), were used to compare our outcomes with those of leading watermarking methods. The comparison reveals that our proposed strategy surpasses existing methods in terms of both robustness and imperceptibility. The results suggest that this technique is suitable for tamper detection in various domains, including cryptography, medical imaging and multimedia transmission.

The secure communication of information is a major concern over the internet. The information must be protected before transmitting over a communication channel to avoid security violations. In this paper, a new hybrid method called compressed encrypted data embedding (CEDE) is proposed. In CEDE, the secret information is first compressed with Lempel Ziv Welch (LZW) compression algorithm. Then, the compressed secret information is encrypted using the Advanced Encryption Standard (AES) symmetric block cipher. In the last step, the encrypted information is embedded into an image of size 512 × 512 pixels by using image steganography. In the steganographic technique, the compressed and encrypted secret data bits are divided into pairs of two bits and pixels of the cover image are also arranged in four pairs. The four pairs of secret data are compared with the respective four pairs of each cover pixel which leads to sixteen possibilities of matching in between secret data pairs and pairs of cover pixels. The least significant bits (LSBs) of current and imminent pixels are modified according to the matching case number. The proposed technique provides double-folded security and the results show that stego image carries a high capacity of secret data with adequate peak signal to noise ratio (PSNR) and lower mean square error (MSE) when compared with existing methods in the literature.