Optimal Pixel Adjustment Process Research Articles

Highly Secured Hybrid Image Steganography with an Improved Key Generation and Exchange for One-Time-Pad Encryption Method

Steganography is a subject of study that has been used to hide information throughout history. In cryptology science, the information to be hidden is encrypted. Both study subjects are widely used in information security and protection. In our study, digital image steganography, which is one of the application areas of steganography, was developed and applied to hide text in the selected images. While doing this, the low bands that will hide the data using the discrete Haar wavelet transform of the images obtained first. The text to be hidden is encrypted with the one-time-pad algorithm. The key used for the encryption is transmitted to the receiver using a transmission layer based on a Highly Secured Information Exchange Algorithm. The algorithms use a randomly generated key pool maintained by both the transmitter and the receiver. A key is selected from the pool randomly by generating a random key start point for every message. The pool size and the randomness are critical factors in guaranteeing no key repetition, which is a requirement for a one-time-pad. The ciphertext and the key starting point indicator are hidden in the low bands of the pictures by utilizing the least significant bit method. The optimal pixel adjustment process was applied to the pre-stego-images, this resulted in an improvement in the results. The results obtained in this study are compared against the pre-optimal pixel adjustment process results and the results obtained through peer studies. The test results show that the proposed method outperformed all the methods in terms of peak signal-to-noise ratio, structural similarity index metric, mean absolute error, mean consequential error and the encryption key security.

Modified Multiway Pixel-Value Differencing Methods Based on General Quantization Ranges for Image Steganography

A modified multiway pixel-value differencing method for image steganography using general quantization ranges of pixel pairs&#x2019; difference values is proposed, where the widths of the quantization ranges are not limited to be powers of two. The method can be employed to embed a secret message into a cover image with a higher embedding rate. The cover image is partitioned into non-overlapping complete or incomplete blocks using <inline-formula> <tex-math notation="LaTeX">$1 \times 3$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$2 \times 2$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$2 \times 3$ </tex-math></inline-formula>, or <inline-formula> <tex-math notation="LaTeX">$3 \times 3$ </tex-math></inline-formula> block templates. The message bitstream, whose bit positions are randomized in advance by use of a random number generator, can be embedded in the resulting blocks. More specifically, one pixel in each block is set as a shared pixel, and the least-significant-bit substitution method with the optimal pixel adjustment process is employed to embed message bits into the shared pixel. Next, the shared pixel in the block is combined with each remaining pixel to form a pixel pair, which is then utilized to embed message bits by a new pixel-value differencing method. Also, the use of non-power-of-two range widths is accomplished by a multiple-based number conversion mechanism, and the shared pixel in each block, as well as each related pixel pair whose two grayscale values pass a falling-off-boundary check, are used to embed the digits of the resulting multiple-based number. The experimental results show that the embedding rates yielded by the proposed method are higher than those yielded by existing multiway pixel-value differencing methods. The stego-images resulting from embedding secret messages retain good image quality, and the RS steganalysis process cannot detect the presence of the embedded secret messages.

Data Hiding Method for Color AMBTC Compressed Images Using Color Difference

Image compression technology and copyright protection are certainly the important technologies for free exchange of multimedia. For compression of an image, we propose a color Absolute Moment Block Trucation Coding (AMBTC) method using a common bit-plane created by k-means. In addition, a data hiding method based on a color AMBTC using Optimal Pixel Adjustment Process (OPAP) was proposed for copyright protection and confidential secret communication. The number of quantization levels of the proposed color AMBTC is nine per block. Therefore, the edge of the compressed color image can be expressed more delicately. As a result of the simulation, it can be seen that the edge of the image of the color AMBTC is close to the original image. Moreover, the data hiding performance of the proposed method also obtained excellent results. For the experiment, we measured the quality of the image using the Color Difference (CD) we proposed, and the measurement result was very satisfactory.

Hybrid data encryption model integrating multi-objective adaptive genetic algorithm for secure medical data communication over cloud-based healthcare systems

The exponential rise in the development of cloud computing environments in the healthcare field, the protection and confidentiality of the medical records become a primary concern for healthcare services applications. Today, health data stored in the cloud is highly confidential information concealed to avoid unauthorized access to protect the patient’s information. As cloud-based medical data transmission becomes more common, it receives growing attention from researchers and academics. Despite the potential for misuse, medical data transmitted through unreliable networks can be manipulated or compromised. The current cryptosystems alone are not sufficient to deal with these issues, and hence this paper introduces a new hybridization of data encryption model to shelter the diagnosis data in medical images. The proposed model is developed by combining either 2D Discrete Wavelet Transform 1 Level (2D-DWT-1 L) or 2D Discrete Wavelet Transform 2 Level (2D-DWT-2 L) steganography with the proposed hybrid encryption scheme. The hybrid encryption scheme is built by strategically applying Advanced Encryption Standard (AES) and Rivest–Shamir–Adleman (RSA) algorithms to secure diagnosis data to be embedded with the RGB channels of medical cover image. One of the key novelties is the use of an Adaptive Genetic Algorithm for Optimal Pixel Adjustment Process (AGA-OPAP) that enriches data hiding ability as well as imperceptibility features. To evaluate the efficiency of the proposed model, numerical tests are performed. The results show that the proposed algorithm is capable of safely transmitting medical data. Comparison of results is carried out concerning the datasets with the state-of-the-art algorithm. In terms of various statistical measures, the results showed the superiority of the proposed algorithm, such as peak signal to noise ratio (PSNR), correlation, structural content (SC), structure similarity (SSIM), entropy, histogram, NPCR, UACI and embedding capacity. The proposed model can also prevent attacks, such as steganalysis or RS attacks.

Self-Embedding Fragile Watermarking Scheme to Detect Image Tampering Using AMBTC and OPAP Approaches

Research on self-embedding watermarks is being actively conducted to solve personal privacy and copyright problems by image attack. In this paper, we propose a self-embedded watermarking technique based on Absolute Moment Block Truncation Coding (AMBTC) for reconstructing tampered images by cropping attacks and forgery. AMBTC is suitable as a recovery bit (watermark) for the tampered image. This is because AMBTC has excellent compression performance and image quality. Moreover, to improve the quality of the marked image, the Optimal Pixel Adjustment Process (OPAP) method is used in the process of hiding AMBTC in the cover image. To find a damaged block in a marked image, the authentication data along with the watermark must be hidden in the block. We employ a checksum for authentication. The watermark is embedded in the pixels of the cover image using 3LSB and 2LSB, and the checksum is hidden in the LSB. Through the recovering procedure, it is possible to recover the original marked image from the tampered marked image. In addition, when the tampering ratio was 45%, the image (Lena) could be recovered at 36 dB. The proposed self-embedding method was verified through an experiment, and the result was the recovered image showed superior perceptual quality compared to the previous methods.

Efficient reversible data hiding multimedia technique based on smart image interpolation

Reversible data hiding (RDH) within images is the process of securing data into cover images without degradation. Its challenge is to hide a large payload while taking into account the human visual system so that the distortion of the stego-image is negligible. It is highly desired for the images that have special requirements like the ones in the medical and military fields where the original images are required to be regenerated with no loss after extracting the data. In this paper, we propose an interpolation-based RDH (IRDH) scheme that improves Lee and Huang’s scheme and Malik et al.’s scheme by combining their embedding techniques along with the optimal pixel adjustment process (OPAP) in a way that increases the embedding capacity and the visual quality of both the schemes. In this presented scheme, we start by stretching the size of the original image using the existing enhanced neighbor mean interpolation (ENMI) interpolation technique then the data is embedded into the interpolated pixels using our novel embedding method that depends on the intensity of the pixels and the maximized difference values. This innovative scheme presented all steps covering generation of the interpolated image, data embedding, data extraction and image recovery, making it in testing situation to be compared fairly with others. The experimental results demonstrate that the achieved embedding capacity by our hiding technique is more than 537 Kb for all the test images. Also, the experiments show that our proposed scheme has the highest embedding capacity among five current schemes which are Jung and Yoo’s scheme, Lee and Huang’s scheme, Chang et al.’s scheme, Zhang et al.’s scheme and Malik et al.’s scheme with attractive image security quality.

High-Capacity Data Hiding for ABTC-EQ Based Compressed Image

We present a new data hiding method based on Adaptive BTC Edge Quantization (ABTC-EQ) using an optimal pixel adjustment process (OPAP) to optimize two quantization levels. The reason we choose ABTC-EQ as a cover media is that it is superior to AMBTC in maintaining a high-quality image after encoding is executed. ABTC-EQ is represented by a form of t r i o ( Q 1 , Q 2 , [ Q 3 ] , BM) where Q is quantization levels ( Q 1 ≤ Q 2 ≤ Q 3 ) , and BM is a bitmap). The number of quantization levels are two or three, depending on whether the cover image has an edge or not. Before embedding secret bits in every block, we categorize every block into smooth block or complex block by a threshold. In case a block size is 4x4, the sixteen secret bits are replaced by a bitmap of the smooth block for embedding a message directly. On the other hand, OPAP method conceals 1 bit into LSB and 2LSB respectively, and maintains the quality of an image as a way of minimizing the errors which occur in the embedding procedure. The sufficient experimental results demonsrate that the performance of our proposed scheme is satisfactory in terms of the embedding capacity and quality of an image.

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.

Efficient quantum steganography scheme using inverted pattern approach

Capacity and invisibility are two targets of the methods for quantum image steganography. To hide large messages into the quantum cover image and remain invisible is still a challenge. In this paper, we propose an efficient quantum image steganography scheme, which can be finalized by applying an optimal pixel adjustment process to the quantum secret image (constructed by k binary images) before it is embedded. In particular, each pixel of quantum secret image will be inverted or not inverted before it is embedded. The decisions are recorded by a quantum key image for extracting data. Then, it is accomplished by embedding the quantum secret image into the k least significant bits of the quantum cover image using the basic quantum gates and composite quantum modules. Because all quantum operations are invertible, the extraction procedure is the inverse of the embedding procedure. Obviously, since the value of k can be changed, the proposed quantum steganography scheme can provide variable embedding capacity. Numerical simulation and theoretical analysis have shown that our method has outperformed other similar schemes in terms of the visual quality and embedding capacity. In addition, it also provides a lower computational complexity than its classical counterpart and other quantum steganography schemes.

Generalizing Hamming+k data hiding by overlapped pixels

Matrix coding based data hiding (MCDH) using linear codes (syndrome coding) is an efficient coding method for steganographic schemes to improve their embedding efficiency. Hamming code data hiding (HDH) is a well-known MCDH using a covering function COV (1, n = 2k − 1, k). Afterwards, Hamming+ 1 DH (H1DH) was proposed with good embedding efficiency. However, these two previous approaches, HDH and H1DH, are not efficient for a large amount of messages. To tackle this problem, Yang et al.’s proposed Hamming+ k DH (Hk DH), which enhance the extra one embedded bit in H1DH to k embedded bits in the Hk DH. In this paper, we extended the Hk DH to the Hamming+ k with m overlapped pixels (Hk_mDH). The proposed Hk_mDH adopted pixel overlapping approach, optimal pixel adjustment process (OPAP), and Least Significant Bit (LSB) substitution. Experimental results demonstrate that our Hk_mDH has better embedding rate (ER) compared with previous schemes. In addition, we have proved that our Hk_mDH has excellent theoretical estimation of average mean square error.

OOPAP and OPVD: Two Innovative Improvements for Hiding Secret Data Into Images

Information hiding methods are currently deployed by many security developers for various applications, hence the remarkable value of proposing an efficient and feasible information hiding method is essential. In this paper, two new implementations and algorithms are presented and compared with classic and related ones. First, a new implementation for the optimal pixel adjustment process (OPAP) algorithm has been developed entitled optimal OPAP (OOPAP). This new implementation improves upon the OPAP algorithm by using optimal least significant bit (LSB) substitution. Results of the new implementation demonstrate the efficiency of the new algorithm compared to previously implemented algorithms. Second, the optimal least significant bit LSB method is used to improve the pixel-value differencing (PVD) algorithm, called optimal PVD. Results show the efficiency of the new algorithm in comparison with classic PVD.

İdeal Steganografi Senaryosu: Taşıyıcı Resimlerin Kapasitelerinin Hesaplanması, Frekans Tabanlı Steganografide OPA Yöntemi

In this study, digital image steganography, a branch of steganography, and DCT (Discrete Cosine Transform) and DWT (Discrete Wavelet Transform), frequency-based steganography methods that are a sub-branch of it, are mentioned. Methods such as MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio) which are performance calculation parameters of steganographic methods are explained and the methods of calculating image capacity like Kullback-Leibler Divergence, Jensen-Shannon Divergence and QTS (Quard Tree Segmentation) for increasing the values of these parameters are mentioned. This study explains the OPAP (Optimal Pixel Adjustment Process) method, which allows the existing capacity in the pictures to be further increased, in detail and provides an ideal steganography scenario. Additionally, this scenario has been tried and consequently reached the result that the images with higher data concealment capacity than QTS have higher PSNR values.&nbsp;

An evolutionary computing enriched RS attack resilient medical image steganography model for telemedicine applications

The recent advancement in computing technologies and resulting vision based applications have gives rise to a novel practice called telemedicine that requires patient diagnosis images or allied information to recommend or even perform diagnosis practices being located remotely. However, to ensure accurate and optimal telemedicine there is the requirement of seamless or flawless biomedical information about patient. On the contrary, medical data transmitted over insecure channel often remains prone to get manipulated or corrupted by attackers. The existing cryptosystems alone are not sufficient to deal with these issues and hence in this paper a highly robust reversible image steganography model has been developed for secret information hiding. Unlike traditional wavelet transform techniques, we incorporated Discrete Ripplet Transformation (DRT) technique for message embedding in the medical cover images. In addition, to assure seamless communication over insecure channel, a dual cryptosystem model containing proposed steganography scheme and RSA cryptosystem has been developed. One of the key novelties of the proposed research work is the use of adaptive genetic algorithm (AGA) for optimal pixel adjustment process (OPAP) that enriches data hiding capacity as well as imperceptibility features. The performance assessment reveals that the proposed steganography model outperforms other wavelet transformation based approaches in terms of high PSNR, embedding capacity, imperceptibility etc.

Embedded FPGA Design for Optimal Pixel Adjustment Process of Image Steganography

We propose a prototype of field programmable gate array (FPGA) implementation for optimal pixel adjustment process (OPAP) algorithm of image steganography. In the proposed scheme, the cover image and the secret message are transmitted from a personal computer (PC) to an FPGA board using RS232 interface for hardware processing. We firstly embed k-bit secret message into each pixel of the cover image by the last-significant-bit (LSB) substitution method, followed by executing associated OPAP calculations to construct a stego pixel. After all pixels of the cover image have been embedded, a stego image is created and transmitted from FPGA back to the PC and stored in the PC. Moreover, we have extended the basic pixel-wise structure to a parallel structure which can fully use the hardware devices to speed up the embedding process and embed several bits of secret message at the same time. Through parallel mechanism of the hardware based design, the data hiding process can be completed in few clock cycles to produce steganography outcome. Experimental results show the effectiveness and correctness of the proposed scheme.

Secure medical images based on data hiding using a hybrid scheme with the Hamming code, LSB, and OPAP

Some medical accidents in hospitals are related to mismanagement of medical images X-ray and computer tomography (CT). A counterfeit medical image leads to medical accidents. Thus, security of medical images is important for patient safety. Data hiding can help patients avoid mistakes of doctors or nurses who confuse patient X-rays or CT scans. A hybrid data hiding scheme was applied that combined the Hamming code and LSB with an optimal pixel adjustment process algorithm for encoding to conceal hidden patient information. In addition, quality and capacity of stego-images were improved. Experimental results confirmed that the hiding capacity provided by this strategy is greater than for other schemes. Moreover, the image quality of stego-images with the proposed scheme remained more than 50 dB for most medical test images. In this experiment, we verified the proposed steganographic data hiding scheme as RS steganalysis.

Improving stego image quality in image interpolation based data hiding

Jung and Yoo proposed a new image interpolation method, neighbor mean interpolation, on which they first constructed image interpolation based data hiding (IIDH) scheme. However, the authors only adopted a simple method by adding the decimal value of secret into pixels in cover image. Therefore, even though neighbor mean interpolation method is very cost effective, Jung and Yoo's IIDH scheme does not have very high-resolution stego image. In this paper, we still use neighbor mean interpolation (NMI) to generate cover image, but adopt least significant (LSB) substitution and optimal pixel adjustment process (OPAP) instead of simple addition to improve visual quality of stego image. The main contribution of this paper is to prove theoretically that our IIDH schemes have the better stego image quality than Jung and Yoo's IIDH scheme.

An Adjustable Interpolation-based Data Hiding Algorithm Based on LSB Substitution and Histogram Shifting

Data hiding can be regarded as a type of image processing techniques. Other image processing operations are usually integrated to increase the embedding capacity or decrease the visual distortion. Interpolation is an example of this type of operation. However, previous interpolation-based data hiding algorithms suffered from low and fixed embedding capacity and high visual distortion. This study proposes a more effective two-stage data hiding algorithm based on interpolation, LSB substitution, and histogram shifting. First, the authors modify the formula for embedding capacity calculation and make some adjustments on the sample pixels determination. A threshold is used to obtain the block complexity and each embeddable pixel has a different amount of message embedded. Second, an LSB substitution method and an optimal pixel adjustment process are adopted to raise the image quality. Finally, the authors' proposed algorithm can support adjustable embedding capacity. Compared to the previous algorithm, the experimental results demonstrate the feasibility of the proposed method.

An Image Steganography Algorithm for Hiding Data Based on HDWT, LZW and OPAP

Image steganography is the art of information hiding, which embeds a secret data into a cover image. However, high capacity of secret data and high quality of stego image are key issues in image steganography. In this paper, an image steganography technique based on Haar Discrete Wavelet Transform (HDWT), Lempel Ziv Welch (LZW) algorithm and Optimal Pixel Adjustment Process (OPAP) is proposed. The HDWT is used to increase the robustness of stego image against attacks. To increase the hidden capacity, LZW algorithm is performed on the secret message. The OPAP is then applied to reduce the embedding error between the cover image and stego image. The experimental results are evaluated by four standard images as covers, and with two types of secret messages. The results demonstrate high visual quality of stego image with large Hidden Capacity (HC) of secret data compared with recent techniques

An Image Steganography Algorithm for Hiding Data Based on HDWT, LZW and OPAP

Image steganography is the art of information hiding, which embeds a secret data into a cover image. However, high capacity of secret data and high quality of stego image are key issues in image steganography. In this paper, an image steganography technique based on Haar Discrete Wavelet Transform (HDWT), Lempel Ziv Welch (LZW) algorithm and Optimal Pixel Adjustment Process (OPAP) is proposed. The HDWT is used to increase the robustness of stego image against attacks. To increase the hidden capacity, LZW algorithm is performed on the secret message. The OPAP is then applied to reduce the embedding error between the cover image and stego image. The experimental results are evaluated by four standard images as covers, and with two types of secret messages. The results demonstrate high visual quality of stego image with large Hidden Capacity (HC) of secret data compared with recent techniques

Steganography Technique for JPEG2000 Compressed Images Using Histogram in Wavelet Domain

In this work, a steganography technique using histogram shifting for JPEG2000 compressed images is proposed. Histogram of the wavelet coefficients of each wavelet subband is calculated and shifted to embed secret image data. This embedding is performed on the peak wavelet coefficients during wavelet decomposition process of JPEG2000 encoder using Lifting scheme. Optimal Pixel Adjustment Process (OPAP) is performed on stego images to enrich their visual quality. The results given in this work show that proposed technique provide large embedding capacity and better visual quality of stego images than existing steganography techniques for JPEG2000 compressed images. Extracted secret image using proposed technique is similar to its original secret image.