Hidden Secret Image Research Articles

Patient Data Hiding and Transmitting during COVID-19 for Telemedicine Application using Image Steganography.

After the COVID-19 pandemic, every individual needs to be more aware of their health. The condition of the human body is ged based on various health reports like X-rays, CT scan, and MRI scans. Moreover, due to misplacement or loss of medical reports, there is a high probabaility of improper diagnosis. In order to avoid improper diagnosis, a novel data-hiding technique is proposed in this work. In the proposed method, the patient's health records are hidden using polynomial theory in the patient photograph. This is used by doctors in telemedicine for better treatment at the right time. Image steganography is useful for hiding secret images and also for generating secret keys. This enables only the authorized people (patient and corresponding doctor) to access the reports using secret keys. Four secret images (medical reports of the patient) are successfully embedded onto a single cover image (patient photo) with good quality. After embedding, the stego images look like cover images so that unauthorized persons will not be able to access the data, and hence, safe transmission is being carried out. A patient's medical report plays an important role in proper medical treatment. Particularly in telemedicine, the safe transmission of patient reports without any loss or damage is necessary. The proposed method embeds reports of a patient in his/her photo and transmitsthem to the destination safely with a quality of 45.5 dB. This hiding method is helpful to avoid cyber crimes, illegal transactions, malpractices etc.

Lossless image steganography: Regard steganography as super-resolution

Image steganography attempts to imperceptibly hide the secret image within the cover image. Most of the existing deep learning-based steganography approaches have excelled in payload capacity, visual quality, and steganographic security. However, they are difficult to losslessly reconstruct secret images from stego images with relatively large payload capacity. Recently, although some studies have introduced invertible neural networks (INNs) to achieve large-capacity image steganography, these methods still cannot reconstruct the secret image losslessly due to the existence of lost information on the output side of the concealing network. We present an INN-based framework in this paper for lossless image steganography. Specifically, we regard image steganography as an image super-resolution task that converts low-resolution cover images to high-resolution stego images while hiding secret images. The feature dimension of the generated stego image matches the total dimension of the input secret and cover images, thereby eliminating the lost information. Besides, a bijective secret projection module is designed to transform various secret images into a latent variable that follows a simple distribution, improving the imperceptibility of the secret image. Comprehensive experiments indicate that the proposed framework achieves secure hiding and lossless extraction of the secret image.

DUIANet: A double layer U-Net image hiding method based on improved Inception module and attention mechanism

Image hiding is the process of hiding secret image into cover image, and revealing secret image from steganographic image. However, the quality of generated images and the ability to resist steganalysis detection of steganographic image can be further improved. We propose a novel double-layer U-Net image hiding method based on improved Inception and attention mechanism. The secret image undergoes Haar wavelet transform, hiding network hides the wavelet sub-band of secret image into cover image. We use improved Inception while cascading convolution and attention mechanisms to better extract and fuse information, resulting in high-quality steganographic image. In the revealing stage, Attention mechanism can help networks extract more features about secret image, then we using inverse Haar wavelet transform to revealing high-quality secret image. The experimental results show that the method can obtain high quality images and have good security. When hiding multiple images, the method still has good performance.

Advanced Image Steganography Using a U-Net-Based Architecture with Multi-Scale Fusion and Perceptual Loss

Image-to-image steganography refers to the practice of hiding secret image within a cover image, serving as a crucial technique for secure communication and data protection. Existing image-to-image generative adversarial network-based steganographic methods for image hiding demonstrate a high embedding capacity. However, there is still significant room for improvement in terms of the quality of the stego images and the extracted secret images. In this study, we propose an architecture for inconspicuously hiding an image within the Y channel of another image, leveraging a U-Net network and a multi-scale fusion ExtractionBlock. The network is jointly trained using a loss function combining Perceptual Path Length (PPL) and Mean Square Error (MSE). The proposed network is trained and tested on two datasets, Labeled Faces in the Wild and Pascal visual object classes. Experimental results demonstrate that the model not only achieves high invisibility and significant hiding capacity (8 bits per pixel) without altering the color information of the cover image but also exhibits strong generalization ability. Additionally, we introduce the Modified Multi-Image Similarity Metric (MMISM), which integrates the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM) values of images, to comprehensively evaluate the network’s hiding and extraction capabilities.

Joint adjustment image steganography networks

Image steganography aims to achieve covert communication between two partners utilizing stego images generated by hiding secret images within cover images. Existing deep image steganography methods have been rapidly developed in this area. Such methods, however, usually generate the stego images and reveal the secret images using one-process networks, lacking sufficient refinement in these methods. Thus, the security and quality of stego and revealed secret images still have much room for promotion, especially for large-capacity image steganography. This paper proposes Joint Adjustment Image Steganography Networks (JAIS-Nets), containing a series of coarse-to-fine iterative adjustment processes, for image steganography. Our JAIS-Nets first proposes Cross-Process Contrastive Refinement (CPCR) adjustment method, using the cross-process contrastive information from cover-stego and secret-revealed secret image pairs, to iteratively refine the generated stego and revealed secret images, respectively. In addition, our JAIS-Nets further proposes Cross-Process Multi-Scale (CPMS) adjustment method, using the cross-process multi-scale information from different scales cover-stego and secret-revealed secret image pairs, to directly adjust and enhance the intermediate representations of the proposed JAIS-Nets. Integrating the proposed CPCR with CPMS methods, the proposed JAIS-Nets can jointly adjust the quality of the stego and revealed secret images at both the learning process and image scale levels. Extensive experiments demonstrate that our JAIS-Nets can achieve state-of-the-art performances on the security and quality of the stego and revealed secret images on both the regular and large capacity image steganography.

Hybrid and Invisible Digital Image Watermarking Technique Using IWT-DCT and Hopfield Neural Network

According to the characteristic of HVS (Human Visual System) and the association memory ability of the neural network, an adaptive image watermarking algorithm based on a neural network is proposed invisible image watermarking is a secret embedding scheme for hiding secret images into a cover image file and the purpose of invisible watermarking is copyrights protection. Wavelet transformation-based image watermarking techniques provide better robustness for statistical attacks in comparison to Discrete Cosine Transform domain-based image watermarking. The joined method of IWT (Integer Wavelet Transform) and DCT (Discrete Cosine Transform) gives benefits to the two procedures. The IWT has an impediment of portion misfortune in embedding which increments the mean square estimate as SIM and results in diminishing PSNR. The capacity of drawing in is improved by pretreatment and re-treatment of image scrambling and Hopfield neural network. The proposed algorithm presents a hybrid integer wavelet transform and discrete cosine transform-based watermarking technique to obtain increased imperceptibility and robustness compared to the IWT-DCT-based watermarking technique. The proposed watermarking technique reduces the fractional loss compared to DWT-based watermarking.

Studying Audio Capacity as Carrier of Secret Images in Steganographic System

Steganography art is a technique for hiding information where the unsuspicious cover signal carrying the secret information. Good steganography technique must be includes the important criterions robustness, security, imperceptibility and capacity. The improving each one of these criterions is affects on the others, because of these criterions are overlapped each other. In this work, a good high capacity audio steganography safely method has been proposed based on LSB random replacing of encrypted cover with encrypted message bits at random positions. The research also included a capacity studying for the audio file, speech or music, by safely manner to carrying secret images, so it is difficult for unauthorized persons to suspect presence of hidden image. Measures calculations of SNR, SNR segmental, SNR spectral, MSE and correlation show that, audio music cover file (2channales) is the safest uses as arrier with replace the 9 number of LSB without noticeable noise. Bits of secret message can be hiding capacity reach up to 28 % of the total music cover audio size and the three type's measures of SNR are 32, 28 and 31 dB. For speech cover audio the replacing LSB is safely uses at LSB bits number 6, where the hiding capacity is reach up to 37 % of size speech cover audio at 37, 36 and 39 dB for three type's measures of SNR. Correlation of cover samples was did not effected as a result of hiding secret image, where its value is up to 0.99 for all hiding operations.

Visually Meaningful Image Encryption Scheme Based on DWT and Schur Decomposition

A visually meaningful image encryption scheme with an asymmetric structure based on the discrete wavelet transform (DWT) and Schur decomposition is proposed in this study. First, the RSA algorithm is used to generate the initial values for the chaotic system to produce the random sequence. Then, both scrambling and diffusion operations are performed on the plain image to obtain the preencrypted image. Moreover, the Schur decomposition is applied on the preencrypted plain image to obtain the upper triangular and orthogonal matrices. Second, the cover image is scrambled followed by a DWT operation. Four subbands are then formed, namely, LL, HL, LH, and HH. Finally, the former upper triangular matrix and orthogonal matrix are embedded into subbands LH and HH produced by the cover image. After the application of the inverse DWT and inverse scrambling operation, the final visually meaningful cover image embedded with a secret plain image can be obtained. No one can identify any useful information about the plain image from the final embedded cover image, nor can anybody know that there is any hidden secret image. Experimental simulations show that the normalized correlation values between the original cover image and the final visually meaningful cover image are approximately 0.9997. Therefore, the proposed encryption scheme is imperceptible for secret image communications.

WITHDRAWN: Secure medical image transmission using modified leading diagonal sorting with probabilistic visual cryptography

Informations are being sent through open channels and the security of those informations has been primary considerations. Aside from numerous regular cryptographic techniques, Visual Cryptographic (VC) methods have likewise been being used for information and data security. VC is a secret sharing method as it breaks the original image into share images in order, when the shares are stacked on each other a hidden secret image is uncovered. The VC technique is a secure technique that encodes a secret file or image by breaking it into share images. Cloud computing is a progression model for large scale systems. Security for medical image transmission has been an ongoing computational problem from image recovery to its processing, storage, and retrieval with the advancement of data in the medical sector and health care systems into the cloud. However, the role of Cloud Computing is applied only if security is assured. Modified Leading Diagonal Sorting with Probabilistic Visual Cryptography (MLDS-PVC) is proposed in this research. Breast cancer mammography images from the MIAS dataset are used in this work for medical images. The proposed model could support the transmission of medical images using cloud storage between medical organizations, diagnostics centers, and other health centers.

Encryption-based steganography of images by multiobjective whale optimal pixel selection

ABSTRACT Information security involves hiding secret images, text, audio or video files within any other files that can be used to preserve the secret data from being theft by the third party. Recent works of the literature in steganography have the threat of secret information being retrieved by an anonymous user. Some techniques do not support some image formats for embedding. To overcome the disadvantages associated with the existing algorithms, we proposed encryption-based steganography. Encryption algorithms play vital roles to protect original data from unauthorized access. In this paper, the cover image is separated into RGB components separately. Multilevel discrete wavelet transform (DWT) transformation is applied over the transformed image components. Optimal pixels are selected using Multiobjective Whale Optimization. The secret image is split into RGB components. Encryption using Data Encryption Standard, Advanced Encryption Standard and Signcryption algorithms is performed over R, G and B separated components, respectively. The encrypted image is embedded into the selected pixel point of cover image. Inverse DWT is applied to retrieve the stego image. The results are analyzed to prove low error rate with high secured secret image.

Fractional-Order Spatial Steganography and Blind Steganalysis for Printed Matter: Anti-Counterfeiting for Product External Packing in Internet-of-Things

This paper advocates a novel conceptual formulation of the fractional-order spatial steganography (FSS) and blind steganalysis for printed matter, which can be efficiently employed in the anti-counterfeiting for product external packing in Internet-of-Things (IoT). Traditional digital steganography is not printable. Within the limits of our knowledge, until now, there are not a well-established steganography and a corresponding steganalysis for printed matter in IoT, which should receive desired attention. Fractional calculus has potentially received prominence in applications in the domain of image processing mainly because of its strengths like long-term memory, nonlocality, and weak singularity. Therefore, in an attempt to overcome the aforementioned technical limitation of traditional digital steganography, this paper has studied here, as an interesting theoretical problem, would it be possible to apply the capability of preserving the edges and textural details of fractional calculus to the achievement of the steganography and steganalysis for printed matter in IoT. Motivated by this inspiration, in this work, this paper introduces a novel conceptual formulation of an FSS and a fractional-order blind steganalysis (FBS) for printed matter. At first, according to the opponent process theory of color vision, to better achieve the imperceptibility of the hidden secret information, this paper uses both the self-similar complex textures in a neighborhood and the opponent channel of blue versus yellow to implement FSS for printed matter. Second, without requiring a priori knowledge regarding the characteristics of the original carrier image, hidden secret image, and steganography, an FBS, a fractional-order multimodal function optimization algorithm, is proposed. Finally, the efficient capability of hiding secret information of FSS and that of detecting secret information of FBS are analyzed in detail experimentally, respectively. These two important advantages lead to the superiority of the proposed approach for defending against statistics attack, rotation and distortion attack, cropping attack, scaling attack, noise attack, and color copy attack. The main contribution of this paper is the first preliminary attempt of a feasible achievement of a spatial steganography and a blind steganalysis for printed matter.

Image security based on iterative random phase encoding in expanded fractional Fourier transform domains

A novel image encryption method is proposed by using the expanded fractional Fourier transform, which is implemented with a pair of lenses. Here the centers of two lenses are separated at the cross section of axis in optical system. The encryption system is addressed with Fresnel diffraction and phase modulation for the calculation of information transmission. The iterative process with the transform unit is utilized for hiding secret image. The structure parameters of a battery of lenses can be used for additional keys. The performance of encryption method is analyzed theoretically and digitally. The results show that the security of this algorithm is enhanced markedly by the added keys.

ANALYSIS OF DATA HIDING ALGORITHMS FOR IMAGE SECURITY

The main goal of reversible data hiding algorithms is to embed the secret information in cover image and recover it back successfully. So we have implemented two methods. In first method, cover image is encrypted using stream cipher and pseudo randomly generated key and compressed using haar wavelet compression. The encrypted compressed image acts as a media for hiding secret image. And in second method, secret image is encrypted using randomly generated key and it is hidden in cover image. In both the method data hiding is done using LSB based image steganography. At the receiver, reverse process is done to extract secret image and recover cover image. At the end, we conclude that second method gives better security of image compared to method one.

Feed Forward Networks in Color Extended Visual Cryptography to Generate Meaningful Shares

Conventional visual secret sharing schemes generate noise-like random pixels on shares to hide secret images. It suffers a management problem, because of which dealers cannot visually identify each share. This problem is solved by the Extended Visual Cryptography Scheme (EVCS), which adds a meaningful cover image in each share. However, the previous approaches involving the EVCS for color images suffer from a pixel expansion problem. In this paper, we propose a general approach to solve the abovementioned problem; the approach can be used for color images in non computer-aided decryption environments. The proposed approach uses Feed Forward Network to construct the shares. The experimental results indicate that a solution to the pixel expansion problem of the EVCS is achieved. Moreover, the display quality of the recovered image is better than that obtained using other VC schemes.

Analysis of Secret Image Sharing using Shared Image

secret image sharing scheme with steganography lacks to provide the authentication, quality of stego-image and more cheating done by the dishonest participants. So, a secret image sharing using shared image technique is proposed to prevent the participants from the subsidiary stipulation of a false stego-image (an image containing the hidden secret image). A secret image is first processed into n shares which are then hidden in n user-selected suppression images. It is recommended to select these suppression images to contain well-known stuffing to increase the steganographic effect for the security protection. Additionally, an image watermarking technique is engaged to embed fragile watermark signals into the suppression images by the use of parity-bit checking, thus providing the ability of authenticating the reliability of each processed suppression image. During the secret image recovery process, each stego- image carry by a participant is first verified for its reliability by checking the uniformity of the parity conditions found in the image pixels. This facilitates to avert the participant from subsidiary stipulation of a false stego-image. Some effective techniques for handling large images as well as for enhancing security protection are employed. As a result, the secret image sharing using shared image scheme offers a high secure and effective mechanism for secret image sharing that is not found in existing secret image sharing methods. High-class experimental results proving the authentication capability, secret hiding effectiveness and quality of the proposed approach are included. Keywordsecret image sharing, Steganography, Authentication, suppression image, Data hiding, Stego-image, Fragile watermarking.

A COMPARATIVELY STUDY ON VISUAL CRYPTOGRAPHY

The effective and secure protections of sensitive iare primary concerns in commercial, medi cal and military systems. To address the reliability problems for secret images, a visual cryptography scheme is a good alternative to remedy the vulnerabilities. Visual cryptography is a very secure and unique way to protect secrets. Visual cryptography is an encr yption technique which is used to hide information which is present in an image. U nliketraditional cryptographic schemes, it uses hum an eyes to recover the secret without any complex decryption algorithms and the f acilitate of computers. It is a secret sharing sche me which uses images distributed as shares such that, when the shares ar e superimposed, a hidden secret image is revealed.I n this paper we represent various cryptography technique and research work do ne in this field.

An EVCS for Color Images with Real Size Image Recovery and Ideal Contrast Using Bit Plane Encoding

Conventional visual secret sharing schemes generate noise-like random pixels on shares to hide secret images. It suffers a management problem, because of which dealers cannot visually identify each share. This problem is solved by the Extended Visual Cryptography scheme (EVCS). However, the previous approaches involving the EVCS for general access structures suffer from a low contrast problem. This paper proposes a new (k,n)-threshold image sharing scheme using extended visual cryptography scheme for color images based on bit plane encoding that encrypts a color image in such a way that results of encryption is in the form of shares. Shares do not reflect any information directly, information is scrambled instead. The traditional binary EVCS is used to get the sharing images at every bit level of each principle component of a color image. This scheme provides a more efficient way to hide natural images in different shares. Furthermore, the size of the hidden secret can be recovered by inspecting the blocks in the shares. This new scheme for color images gives the ideal contrast in the recovered image.

Novel Visual Cryptography Schemes Without Pixel Expansion for Halftone Images

Visual cryptography (VC) is a secret-sharing scheme which uses images distributed as shares such that, when the shares are superimposed, a hidden secret image is revealed. While VC was developed for application to binary images, and is inherently based on binary logical operations, it can be applied to grayscale images through their halftone representations. In this paper, we present a new method for processing halftone images that improves the quality of recovered secret images in a VC scheme. Notably, our approach mitigates the two traditional problems in VC of pixel expansion and loss of contrast. Based on this processing stage, this paper proposes and demonstrates the results of two applications of VC on halftone images, one application in multiple VC, and the second in extended VC. Both applications function without pixel expansion, with enhanced visual quality of the recovered secret image over earlier approaches in the literature, while also maintaining perfect security of the original VC approach.

Wavelet bit-plane based data hiding for compressed images

In this paper, a wavelet bit-plane based data hiding for compressed images is proposed. Image compression not only reduces storage but also benefits transmission. Currently, image encoders including JPEG2000, SPIHT, EZW, etc. also provide multi-stage encoding/decoding. In this paper, the bit-planes of DWT coefficients are selected to carry the secret image according to the multi-stage encoding. The hidden secret image can be extracted progressively from multi-stage decoded images.Experimental results showed that the secret image was embedded and extracted in multi-stage coded images. Furthermore, the structure of secret image could be identified in earlier decoding stages and then refined in later stages. Accordingly, the progressive secret revealing is achieved. In comparison with the other similar schemes, the proposed method achieves the better quality of stego-image than the other two when the hiding capacity is the same.

Eliminating Cover Image Requirement in Discrete Wavelet Transform based Digital Image Steganography

steganography is the art and science of hiding secret image into digital media such that no one apart from the intended recipient is able to detect the existence of the information. There are many different carriers that can be used to hide the information such as digital images, videos, sound files and other computer files but digital images are the most popular. In this paper, a method has been proposed using which a large size secret image can be hidden into small size cover image securely. The main aim here is the absolute invisibility of the large size secret image. The secret image is first scrambled by using Arnold transformation. Haar Discrete Wavelet Transformation (DWT) is then applied on cover image and Arnold transformed secret image, followed by Alpha Blending operation. Then the Haar Inverse Discrete Wavelet Transformation (IDWT) is applied to obtain the stego image. At the receiver side, first the cover image is obtained from the stego image. Then Haar DWT is applied on the cover image and the stego image followed by the alpha blending operation. Haar IDWT is applied on the resulting image. Then by applying Arnold transformation, the secret image is obtained. The proposed method does not require the sender to send the cover image to the receiver for obtaining the secret image. The performance of the proposed method is investigated by comparing the cover image and the stego image in terms of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Normalized Cross Correlation (NCC). Experimental results demonstrate the effectiveness and accuracy of the proposed method.