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In this paper, we describe the concept of a new data-hiding technique for steganography in RGB images where a secret message is embedded in the blue layer of specific bytes. For increasing security, bytes are chosen randomly using a random square Hermitian positive definite matrix, which is a stego-key. The proposed solution represents a very strong key since the number of variants of positive definite matrices of order 8 is huge. Implementing the proposed steganographic method consists of splitting a color image into its R, G, and B channels and implementing two segments, which take place in several phases. The first segment refers to embedding a secret message in the carrier (image or text) based on the unique absolute elements values of the Hermitian positive definite matrix. The second segment refers to extracting a hidden message based on a stego-key generated based on the Hermitian positive definite matrix elements. The objective of the data-hiding technique using a Hermitian positive definite matrix is to embed confidential or sensitive data within cover media (such as images, audio, or video) securely and imperceptibly; by doing so, the hidden data remain confidential and tamper-resistant while the cover media's visual or auditory quality is maintained. [ABSTRACT FROM AUTHOR]

The rapid development of AI-based facial manipulation techniques has made manipulated facial images highly deceptive. These techniques can be misused maliciously, which poses a severe threat to information security. Many effective detection methods have been developed to distinguish whether an image has been manipulated. However, malicious facial manipulation images or videos have been widely spread and had a harmful impact before detection. Thus protecting images from manipulation through proactive defense techniques has become the focus of current research. Currently, existing proactive defense methods disrupt the manipulation process through an adversarial attack on the facial manipulation network, which distorts or blurs parts of the manipulated facial image. Nevertheless, these methods are only slightly disruptive in defending against some facial manipulation methods, and the outputs are not only a stigmatized portrait but also that people still can not distinguish the real and fake. To overcome this issue, we propose a Multi-Teacher Universal Distillation based on information hiding for defense against facial manipulation. First, we propose a facial manipulation adversarial attacks network based on information hiding called IHA-Net. IHA-Net can hide the warning image in the protected image without affecting its visual quality and make the facial information disappear after manipulation to present the warning message. In this way, it prevents privacy leakage and stigmatization. Then to address the problem that the protected image cannot defend against multiple facial manipulations simultaneously, we propose the Multi-Teacher Universal Distillation framework. We use multiple trained teacher networks to co-direct the learning of the student network, allowing the student network to defend against multiple manipulation networks simultaneously. Specifically, we designed Multi-scale Discriminators for knowledge distillation at the feature map level to enable the student network to learn more rich knowledge from the teacher network. Furthermore, to balance the influence of multiple teacher networks on the student network during the training process, we designed a Dynamic Balancing Loss module that dynamically adjusts during the training process. Finally, extensive experiments on advanced facial manipulation systems demonstrate that the proposed method outperforms the state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Mobile communication is ubiquitous in everyday life. The fifth generation of mobile networks (5G) introduced 5G New Radio as a radio access technology that meets current bandwidth, quality, and application requirements. Network steganographic channels that hide secret message transfers in an innocent carrier communication are a particular threat in mobile communications as these channels are often used for malware, ransomware, and data leakage. We systematically analyze the protocol stack of the 5G–air interface for its susceptibility to network steganography, addressing both storage and timing channels. To ensure large coverage, we apply hiding patterns that collect the essential ideas used to create steganographic channels. Based on the results of this analysis, we design and implement a network covert storage channel, exploiting reserved bits in the header of the Packet Data Convergence Protocol (PDCP). the covert sender and receiver are located in a 5G base station and mobile device, respectively. Furthermore, we sketch a timing channel based on a recent overshadowing attack. We evaluate our steganographic storage channel both in simulation and real-world experiments with respect to steganographic bandwidth, robustness, and stealthiness. Moreover, we discuss countermeasures. Our implementation demonstrates the feasibility of a covert channel in 5G New Radio and the possibility of achieving large steganographic bandwidth for broadband transmissions. We also demonstrate that the detection of the channel by a network analyzer is possible, limiting its scope to application scenarios where operators are unaware or ignorant of this threat. [ABSTRACT FROM AUTHOR]

Protecting data transmission, which plays a capital importance for data confidentiality, has recently been recognized as significant attention. Several research works using the data hiding paradigm have tried to apply steganography in digital images to protect the secret bits of confidential data against unwanted access throughout the public network commonly used. Nevertheless, the existing steganography algorithm faces a common challenge of a significant distortion of the image transmitted through the public network after concealing the secret bits in its pixels. To address this steganography problem in digital images, this article presents a new algorithm to optimize embeddable pixels used to yield a quality stego image with fewer distortions. The proposed method transforms the secret bits into a simplified format by changing the base system and mathematical sorting to reduce the magnitude, making the payload size significantly minimal. The proposed method is experimentally tested using 256 x 256 grayscale images from the Signal and Image Processing Institute (SIPI) database as cover images and random bits generated from Lorem Ipsum text as secret data. The method's performance is compared to the recent Difference Expansion (DE) method, showing superior results with an average Peak Signal-to-Noise Ratio (PSNR) of 85 dB and a Structural Similarity Index Measure (SSIM) of 0.99, indicating higher stego image quality. [ABSTRACT FROM AUTHOR]

Recently, implicit neural representation (INR) has started to be applied in image steganography. However, the quality of stego and secret images represented by INR is generally low. In this paper, we propose an implicit neural representation steganography method by neuron pruning. Initially, we randomly deactivate a portion of neurons to train an INR function for implicitly representing the secret image. Subsequently, we prune the neurons that are deemed unimportant for representing the secret image in a unstructured manner to obtain a secret function, while marking the positions of neurons as the key. Finally, based on a partial optimization strategy, we reactivate the pruned neurons to construct a stego function for representing the cover image. The recipient only needs the shared key to recover the secret function from the stego function in order to reconstruct the secret image. Experimental results demonstrate that this method not only allows for lossless recovery of the secret image, but also performs well in terms of capacity, fidelity, and undetectability. The experiments conducted on images of different resolutions validate that our proposed method exhibits significant advantages in image quality over existing implicit representation steganography methods. [ABSTRACT FROM AUTHOR]

Traditional information hiding techniques achieve information hiding by modifying carrier data, which can easily leave detectable traces that may be detected by steganalysis tools. Especially in image transmission, both geometric and non-geometric attacks can cause subtle changes in the pixels of the image during transmission. To overcome these challenges, we propose a constructive robust image steganography technique based on style transformation. Unlike traditional steganography, our algorithm does not involve any direct modifications to the carrier data. In this study, we constructed a mapping dictionary by setting the correspondence between binary codes and image categories and then used the mapping dictionary to map secret information to secret images. Through image semantic segmentation and style transfer techniques, we combined the style of secret images with the content of public images to generate stego images. This type of stego image can resist interference during public channel transmission, ensuring the secure transmission of information. At the receiving end, we input the stego image into a trained secret image reconstruction network, which can effectively reconstruct the original secret image and further recover the secret information through a mapping dictionary to ensure the security, accuracy, and efficient decoding of the information. The experimental results show that this constructive information hiding method based on style transfer improves the security of information hiding, enhances the robustness of the algorithm to various attacks, and ensures information security. [ABSTRACT FROM AUTHOR]

The rapid development of the internet and digital media has provided convenience while also posing a potential risk of steganography abuse. Identifying steganographer is essential in tracing secret information origins and preventing illicit covert communication online. Accurately discerning a steganographer from many normal users is challenging due to various factors, such as the complexity in obtaining the steganography algorithm, extracting highly separability features, and modeling the cover data. After extensive exploration, several methods have been proposed for steganographer identification. This paper presents a survey of existing studies. Firstly, we provide a concise introduction to the research background and outline the issue of steganographer identification. Secondly, we present fundamental concepts and techniques that establish a general framework for identifying steganographers. Within this framework, state-of-the-art methods are summarized from five key aspects: data acquisition, feature extraction, feature optimization, identification paradigm, and performance evaluation. Furthermore, theoretical and experimental analyses examine the advantages and limitations of these existing methods. Finally, the survey highlights outstanding issues in image steganographer identification that deserve further research. [ABSTRACT FROM AUTHOR]

Abstract Due to the advancement in biomedical technologies, to diagnose problems in people, a number of psychological signals are extracted from patients. We should be able to ensure that psychological signals are not altered by adversaries and it should be possible to relate a patient to his/her corresponding psychological signal. As far as our awareness extends, none of the existing methods possess the capability to both identify and verify the authenticity of the ECG signals. Consequently, this paper introduces an innovative dual-layer data-embedding approach for electrocardiogram (ECG) signals, aiming to achieve both signal identification and authenticity verification. Since file name-based signal identification is vulnerable to modifications, we propose a robust watermarking method which will embed patient-related details such as patient identification number, into the medically less-significant portion of the ECG signals. The proposed robust watermarking algorithm adds data into ECG signals such that the patient information hidden in an ECG signal can resist the filtering attack (such as high-pass filtering) and noise addition. This is achieved via the use of error buffers in the embedding algorithm. Further, modification-sensitive fragile watermarks are added to ECG signals. By extracting and checking the fragile watermark bits, we can determine whether an ECG signal is modified or not. To ensure the security of the proposed mechanism, two secret keys are used. Our evaluation demonstrates the usefulness of the proposed system.

Due to the advancement in biomedical technologies, to diagnose problems in people, a number of psychological signals are extracted from patients. We should be able to ensure that psychological signals are not altered by adversaries and it should be possible to relate a patient to his/her corresponding psychological signal. As far as our awareness extends, none of the existing methods possess the capability to both identify and verify the authenticity of the ECG signals. Consequently, this paper introduces an innovative dual-layer data-embedding approach for electrocardiogram (ECG) signals, aiming to achieve both signal identification and authenticity verification. Since file name-based signal identification is vulnerable to modifications, we propose a robust watermarking method which will embed patient-related details such as patient identification number, into the medically less-significant portion of the ECG signals. The proposed robust watermarking algorithm adds data into ECG signals such that the patient information hidden in an ECG signal can resist the filtering attack (such as high-pass filtering) and noise addition. This is achieved via the use of error buffers in the embedding algorithm. Further, modification-sensitive fragile watermarks are added to ECG signals. By extracting and checking the fragile watermark bits, we can determine whether an ECG signal is modified or not. To ensure the security of the proposed mechanism, two secret keys are used. Our evaluation demonstrates the usefulness of the proposed system. [ABSTRACT FROM AUTHOR]

Information hiding ensures necessary security of massive data in the cloud and Internet of things environments. Although traditional encryption can protect the privacy of the image effectively, it cannot protect the image in other aspects such as copyright and integrity. Therefore, information hiding in encrypted domain is required and challenged. An information hiding scheme in homomorphic encrypted domain is proposed. Firstly, the homomorphism of compressive sensing is explored, and it is found that doubling the measurements obtained by compressive sensing is equivalent to directly extending the original signal before compressive sensing. Secondly, by using homomorphic addition, information hiding in the compressive sensing encrypted domain is realized based on differential extension. The experimental simulation results show that the proposed algorithm has satisfactory performances in both privacy protection and information hiding, and the embedding capacity is higher than the related state of art works. [ABSTRACT FROM AUTHOR]

Image steganography is the art of hiding information in a cover image in such a way that a third party does not notice the hidden information. This paper presents a novel technique for image steganography in the spatial domain. The new method hides and recovers hidden information of substantial length within digital imagery while maintaining the size and quality of the original image. The image gradient is used to generate a saliency image, which represents the energy of each pixel in the image. Pixels with higher energy are more salient and they are valuable for hiding data since their visual impairment is low. From the saliency image, a cumulative maximum energy matrix is created; this matrix is used to generate horizontal seams that pass over the maximum energy path. By embedding the secret bits of information along the seams, a stego-image is created which contains the hidden message. In the stego-image, we ensure that the hidden data is invisible, with very small perceived image quality degradation. The same algorithms are used to reconstruct the hidden message from the stego-image. Experiments have been conducted using two types of images and two types of hidden data to evaluate the proposed technique. The experimental results show that the proposed algorithm has a high capacity and good invisibility, with a Peak Signal-to-Noise Ratio (PSNR) of about 70, and a Structural SIMilarity index (SSIM) of about 1. [ABSTRACT FROM AUTHOR]

Image steganography is one of the prominent technologies in data hiding standards. Steganographic system performance mostly depends on the embedding strategy. Its goal is to embed strictly confidential information into images without causing perceptible changes in the original image. The randomization strategies in data embedding techniques may utilize random domains, pixels, or region-of-interest for concealing secrets into a cover image, preventing information from being discovered by an attacker. The implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility, but it is challenging. A systematic approach is used with a standard methodology to carry out this study. This review concentrates on the critical examination of several embedding strategies, incorporating experimental results with state-of-the-art methods emphasizing the robustness, security, payload capacity, and visual quality metrics of the stego images. The fundamental ideas of steganography are presented in this work, along with a unique viewpoint that sets it apart from previous works by highlighting research gaps, important problems, and difficulties. Additionally, it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography. [ABSTRACT FROM AUTHOR]

Nowadays, preventing data transmission via networks from unauthorized access has become crucial. In this work, we introduce a new enhanced Crow Search Algorithm (CSA), named NECSA, for solving the search problem. Then, we propose a steganographic approach called Steganographic NECSA (SNECSA). It is based on NECSA for obtaining optimal positions and the Least Significant Bit (LSB) method for concealing secret data in these positions. For gray-scale images, SNECSA is applied with 4-LSB. For colored images, SNECSA is applied in two versions. The first one uses 3–3–2 LSB, while the other uses 3–3–2 LSB and permutations on each secret byte, obtaining six patterns and choosing the fittest pattern to embed. The practical results show that the proposed approach outperforms other previous approaches with respect to peak signal to noise ratio, bit error rate, and number of pixel change, where the average peak signal to noise ratios achieved by the proposed approach are approximately 76.25 dB, 73.47 dB, and 71 dB in gray-scale images, and 83.76 dB, 80.9 dB, and 78.7 dB in color images on the tested data set. Additionally, the suggested approach shows outstanding resistance to stego-attacks such as salt and paper noise and regular and singular analysis. [ABSTRACT FROM AUTHOR]

Traceability via quick response (QR) codes is regarded as a clever way to learn specifics about a product's history, from its creation to its transit and preservation before reaching consumers. The QR code can, however, be easily copied and faked. Therefore, we suggest a novel strategy to prevent tampering with this code. The method is divided into two primary phases: concealing a security element in the QR code and determining how similar the QR code on the goods is to the real ones. For the first problem, error-correcting coding is used to encode and decode the secret feature in order to manage faults in noisy communication channels. A deep neural network is used to both conceal and extract the information encoded in a QR code, and the suggested network creates watermarked QR code images with good quality and noise tolerance. The network has the ability to be resilient to actual distortions brought on by the printing and photographing processes. In order to measure the similarity of QR codes, we create neural networks based on the Siamese network design. To assess whether a QR code is real or fraudulent, the hidden characteristic extracted from the acquired QR code and the outcome of QR code similarity estimation are merged. With an average accuracy of 98%, the proposed technique performs competitively and has been used in practice for QR code authentication. [ABSTRACT FROM AUTHOR]

This paper describes a new steganographic method for QR codes. Unlike most information-hiding techniques in this field, it does not rely on the error correction property. Instead, it uses the segmentation feature of QR codes. Encoding of data in a QR code is achieved by creating segments of specific modes, chosen according to data type in order to save space. However, the segmentation does not have to be optimal. A secret message may be embedded into a QR code by selecting an alternative segment type. The presented method generates valid QR codes that may be decoded with standard readers. The solution has been tested using several QR decoders, and it has been confirmed that only the regular message was returned. Additionally, the error correction quality of produced codes is not diminished. The described algorithm is suitable for either digital or printed media, and in both cases, QR codes retain secret data. [ABSTRACT FROM AUTHOR]

The hiding capacity of the current information hiding field has reached a relatively high level, which can hide two color images into one color image. In order to explore a larger hidden capacity, an information hiding scheme based on an improved FCdDNet is proposed, which can hide large-size color images into small-size color images. An improved FCdDNet network is used as the main structure shared by the hidden network and the extraction network. These two networks promote and improve each other during the confrontation training process and are used in pairs. It can be seen that the proposed scheme achieves a larger information hiding capacity, and the hidden information is four times larger than the scale of the carrier image. At the same time, the visual effect after hiding is guaranteed, and the image extracted from the hidden image also has a high degree of restoration. The scheme can be applied to image authentication, secret image transmission, and other fields. [ABSTRACT FROM AUTHOR]

Steganography and cryptography are spy craft cousins, working differently to achieve the same target. Cryptography is perceptible and observable without understanding the real content, while steganography hides the content so that it is not perceptible or observable and without producing noticeable changes to the carrier image. The challenge is finding the right balance between security and retrievability of embedded data from embedding locations without increasing the required embedded information. This paper proposes a secure map-based steganography technique to enhance the message security level based on the sender and recipient mac addresses. The proposed technique uses rivest-shamir-adleman (RSA) to encrypt the message, then embeds the cipher message in the host image based on the sender and recipient media access control addresses (mac addresses) exclusive or operation "XOR" results without increasing the required embedded information for the embedding location map. The proposed technique is evaluated on various metrics, including peak signal-to-noise ratio (PSNR) and embedding capacity, and the results show that it provides a high level of security and robustness against attacks without an extra location map. The proposed technique can embed more data up to 196.608 KB in the same image with a PSNR higher than 50.58 dB. [ABSTRACT FROM AUTHOR]

This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission. The algorithm we designed aims to mitigate the impact of various noise attacks on the integrity of secret information during transmission. The method we propose involves encoding secret images into stylized encrypted images and applies adversarial transfer to both the style and content features of the original and embedded data. This process effectively enhances the concealment and imperceptibility of confidential information, thereby improving the security of such information during transmission and reducing security risks. Furthermore, we have designed a specialized attack layer to simulate real-world attacks and common noise scenarios encountered in practical environments. Through adversarial training, the algorithm is strengthened to enhance its resilience against attacks and overall robustness, ensuring better protection against potential threats. Experimental results demonstrate that our proposed algorithm successfully enhances the concealment and unknowability of secret information while maintaining embedding capacity. Additionally, it ensures the quality and fidelity of the stego image. The method we propose not only improves the security and robustness of information hiding technology but also holds practical application value in protecting sensitive data and ensuring the invisibility of confidential information. [ABSTRACT FROM AUTHOR]

The rapid advancement of technology is closely linked to the development of the modern era. Technology is always expected to provide convenience to each user according to their individual needs, especially when it comes to sending messages. In the present day, sending messages is a fundamental necessity and security plays a crucial role. Data transmission can be easily intercepted by third parties, even if the data are private or confidential. Therefore, it is crucial to have a security approach in place. However, some methods introduced earlier have not been suitable in terms of the capacity and quality produced. This study addresses this issue by using audio as a medium to insert a secret message. This research focuses on optimizing the quality of the stegoaudio produced without reducing the insertion capacity. The experimental results show an increase in quality based on the Peak Signal-to-Noise Ratio (PSNR) evaluation results. [ABSTRACT FROM AUTHOR]

Information hiding is to protect the security of secret information during transmission. This paper proposes a random sequential high-capacity hiding scheme based on pixel value difference (PVD) and least significant bit (LSB), which can maintain a good image quality and extract data accurately. Firstly, the image is divided into 2 × 2 blocks. A random sequence is generated to determine the embedding order and the first pixel in block is selected as the reference pixel. Secondly, the LSB substitution is applied to the reference pixel. A hybrid method of PVD and LSB is utilized to embed the remaining pixels. Calculate the difference between the remaining pixels and the reference pixel to determine the embedding bits according to the difference range table. Finally, the embedded pixels are adjusted to ensure that the differences before and after embedding are within the same range. The experiment compared the embedding capacity (EC), peak signal-noise ratio and structure similarity index with other schemes, demonstrating that this scheme achieved good visual quality while increasing capacity. The experiment results demonstrate that the proposed method has high EC (930,312 bits) and good visual quality (35.51 dB). In addition, the proposed scheme has shown excellent resistance ability to salt-and-pepper noise, regular and singular analysis, pixel difference histogram analysis, and subtractive pixel adjacency matrix steganalysis. [ABSTRACT FROM AUTHOR]

Previous studies have specifically demonstrated that incorporating high-quality side-information can notably enhance the steganographic security of JPEG images. To obtain more precise side-information estimates, researchers utilize sophisticated deblocking or denoising filters, which enhance security but require a substantial amount of time. The challenge lies in achieving a significant improvement in security and efficiency. This paper introduces a steganographic network named WTSNet, which leverages wavelet transform for estimating side-information through iterative optimization in both the pixel and wavelet domains. The wavelet domain is purposely designed to capture intricate high-frequency texture details and facilitate precise estimation of the side-information. Furthermore, the embedding cost is adjusted based on the polarity of the estimated rounding error, ensuring both secure and efficient performance. Experimental results demonstrate that the proposed scheme substantially enhances the security of conventional JPEG steganography, which relies on additive distortion. Moreover, it outperforms the state-of-the-art JPEG steganography methods based on estimating side-information while consuming less time.

Steganography is a process to hide data inside a cover file mostly used in media files like image, video, and audio files. Least significant bit (LSB) steganography is a technique where the least significant bits of pixels are used for information hiding. The purpose of using only those bits is to minimize the visual impact of the hidden data on the image file. LSB technique of steganography is one of the most popular forms of steganography available today. As a result, various steganalysis techniques are developed for this steganography technique. One of them is the visual analysis of pixels through pixel modifications to expose hidden data in a visual manner. The proposed method achieves resistance to this attack using an image segmentation model and extracting the most texture-complex areas of an image and hiding information in these specific areas as pseudo-randomized least significant bit replacements. As the outcome of the study, an alternative approach to LSB steganography that results competitively with existing methods is provided.

During the past few decades, research on digital media watermarking–initially designed for digital images with the envisioned applications of copyright protection or copy control– has significantly evolved with respect to other covers (i.e., video, audio, speech) and many more potential applications, including tamper detection, broadcast monitoring, and, more recently, fake news detection. As a result, various surveys have tried to summarize certain aspects of this research field as it has grown. This has led to more than 130 survey papers being written at different points in time, describing various parts of the scientific efforts focused on digital media watermarking. Considering the above, the aim of this paper is twofold. First, we conduct a meta-survey based on 64 selected research works, in order to summarize the most notable survey papers in this field, which allows us to “draw a map” of this research area. Second, we focus on providing the requirements for digital watermarking techniques when applied to their most recent application: detecting fake news in multimedia content. Finally, an outline of the approach taken within the DISSIMILAR (Detection of fake newS on SocIal MedIa pLAtfoRms) project for the detection of disinformation is presented.

In this paper, we describe the concept of a new data-hiding technique for steganography in RGB images where a secret message is embedded in the blue layer of specific bytes. For increasing security, bytes are chosen randomly using a random square Hermitian positive definite matrix, which is a stego-key. The proposed solution represents a very strong key since the number of variants of positive definite matrices of order 8 is huge. Implementing the proposed steganographic method consists of splitting a color image into its R, G, and B channels and implementing two segments, which take place in several phases. The first segment refers to embedding a secret message in the carrier (image or text) based on the unique absolute elements values of the Hermitian positive definite matrix. The second segment refers to extracting a hidden message based on a stego-key generated based on the Hermitian positive definite matrix elements. The objective of the data-hiding technique using a Hermitian positive definite matrix is to embed confidential or sensitive data within cover media (such as images, audio, or video) securely and imperceptibly; by doing so, the hidden data remain confidential and tamper-resistant while the cover media’s visual or auditory quality is maintained.

Mobile communication is ubiquitous in everyday life. The fifth generation of mobile networks (5G) introduced 5G New Radio as a radio access technology that meets current bandwidth, quality, and application requirements. Network steganographic channels that hide secret message transfers in an innocent carrier communication are a particular threat in mobile communications as these channels are often used for malware, ransomware, and data leakage. We systematically analyze the protocol stack of the 5G–air interface for its susceptibility to network steganography, addressing both storage and timing channels. To ensure large coverage, we apply hiding patterns that collect the essential ideas used to create steganographic channels. Based on the results of this analysis, we design and implement a network covert storage channel, exploiting reserved bits in the header of the Packet Data Convergence Protocol (PDCP). the covert sender and receiver are located in a 5G base station and mobile device, respectively. Furthermore, we sketch a timing channel based on a recent overshadowing attack. We evaluate our steganographic storage channel both in simulation and real-world experiments with respect to steganographic bandwidth, robustness, and stealthiness. Moreover, we discuss countermeasures. Our implementation demonstrates the feasibility of a covert channel in 5G New Radio and the possibility of achieving large steganographic bandwidth for broadband transmissions. We also demonstrate that the detection of the channel by a network analyzer is possible, limiting its scope to application scenarios where operators are unaware or ignorant of this threat.

Visual masking plays a crucial role in optimizing distortion position and intensity in information hiding. However, existing studies on stereoscopic visual masking effects are insufficient and may not align with human perceptual thresholds. This paper aims to fill this research gap by conducting psychophysical experiments to investigate binocular target-to-target visual masking effects that leverage the perceptual mechanisms of the human eye, leading to precise determination of masking thresholds. The experiments involve adjusting the orientation of noise gratings in two scenarios: binocular combination and binocular rivalry, and quantitatively measure the masking thresholds for various binocular noise orientations. Experiment I focuses on investigating the intraocular target-to-target orientation modulation effects in binocular combination, while Experiments II and III explore the interocular target-to-target masking effects and orientation modulation effects in binocular rivalry. The findings indicate that the target-to-target masking effects can increase stereoscopic visual masking thresholds by 23% to 65% compared to previous context-to-target masking effects, while ensuring the noise remains invisible. These findings have practical implications for information hiding technologies related to stereoscopic images and videos. By selecting the orientation, position, and intensity for distortion, improvements can be made in metrics such as embedding strength and capacity while ensuring high-quality display. [ABSTRACT FROM AUTHOR]

An important reason to protect provider and medical care patient information and data is digital terrorism. Patient health records and healthcare provider information are sensitive issues that can affect patients' health or even national security. Many frequent attacks have carried out breaches on health databases/data sets continuously and on remote servers and local servers with wireless sensor networks (WSNs) in different places. Various modern approaches addressed this issue and were designed to prevent these attacks with the aim of providing the security of patient information and data transmitted and collected by WSNs. However, there are still several signs of weakness in these approaches, which are described in the literature review. This research proposes a new trustworthy approach that supports the provision of data security and information collected by WSN and stored on basestation databases. This approach takes advantage of the integration of several security mechanisms including symmetric cryptography for encryption, asymmetric cryptography for signature and access control, as well as the implementation of the Lesamnta-LW function in the signature mechanism. Solid methodology and careful use of these mechanisms protect and hide users' information from being exposed to attackers. Security analyses, investigative comparisons and rigorous findings indicate that the proposed approach is superior to previous approaches. [ABSTRACT FROM AUTHOR]

A new encod-decoder steganography scheme based on dense residual connection was proposed to solve the problem of poor quality of encod-decoder images and message images generated by image steganography schemes based on encoder-decoder networks. Different from the existing end-to-end image steganography networks, the proposed scheme does not need to preprocess the image, and adopts dense residual connections to transport the features of the shallow network to each layer of the deep network structure, effectively preserving the details of the feature map, and uses channels and spatial attention modules to filter the features, improving the codec's attention to the complex texture region of the image. Experimental results on LFW, PASCAL-VOC12 and ImageNet datasets show that the proposed method can effectively improve image quality under the premise of ensuring the security of the algorithm, including the peak signal-to-noise ratio of dense images and carrier images. The mean values of peak signal-to-noise ratio(PSNR) and structural similarity(SSIM) are 36. 2 dB and 0. 98 respectively. [ABSTRACT FROM AUTHOR]

The security of digital image in the process of cloud environment transmission becomes one of the research hotspots in the field of information security. In order to overcome the problems of insufficient camouflage ability,susceptibility to malicious attacks, and limited information hiding space in traditional reversible information hiding algorithms in the ciphertext domain, this paper proposes a high-capacity ciphertext domain reversible information hiding algorithm based on image camouflage encryption and bidirectional interpolation extension. This algorithm first employs two techniques, VQ coding and Discrete Wavelet Transform, to perform camouflage encryption on the original image, ensuring secrecy and secure transmission of the image in cloud environments. Then, it utilizes an information hiding technique based on bidirectional interpolation extension to embed secret information into the camouflaged encrypted image, achieving high-capacity information hiding. The experimental results show that the proposed method not only achieves image camouflage, but also has no obvious visual difference with the original image. The Peak Signalto-Noise Ratio (PSNR) reaches more than 40dB, indicating a good camouflage effect on the original image. It also achieves high-capacity secret information embedding with an average embedding rate of the image approaching 0.6bpp with outstanding experimental performance. [ABSTRACT FROM AUTHOR]

Adding perturbation to images can mislead classification models to produce incorrect results. Based on this, research has exploited adversarial perturbation to protect private images from retrieval by malicious intelligent models. However, adding adversarial perturbation to images destroys the original data, making images useless in digital forensics and other fields. To prevent illegal or unauthorized access to sensitive image data such as human faces without impeding legitimate users, the use of reversible adversarial attack techniques is becoming more widely investigated, where the original image can be recovered from its reversible adversarial examples. However, existing reversible adversarial attack methods are designed for traditional imperceptible adversarial perturbation and ignore the local visible adversarial perturbation. In this paper, we propose a new method for generating reversible adversarial examples based on local visible adversarial perturbation. The information needed for image recovery is embedded into the area beyond the adversarial patch by the reversible data hiding technique. To reduce image distortion, lossless compression and the B-R-G (blue-red-green) embedding principle are adopted. Experiments on CIFAR-10 and ImageNet datasets show that the proposed method can restore the original images error-free while ensuring good attack performance. [ABSTRACT FROM AUTHOR]

This paper presents a technique for hiding secret messages in images while transferring them over a network using steganography. The preprocessed standard datasets create steganographic datasets for facial re-enactment purposes. The facial re-enactment GAN (FRe-GAN) technique and qualitative and quantitative results have been presented over various datasets. A comparative study has been conducted that showcase the drawbacks of existing literature and motivated their work. We propose a steganography-based GAN model and used benchmark datasets such as Flickr-Faces-HQ (FFHQ), IMPA-FACE3D, FaceForensics++, and CelebFaces Attributes (CelebA) facial datasets in the experimentation. We have derived a Generative Adversarial Networks-based approach to face re-synthesis and re-enactment that adjusts for facial expressions and pose. The face blending network is used to blend two faces seamlessly. We have compared the proposed approach with existing state-of-the-art systems and show that our method achieves qualitatively and quantitatively better results. [ABSTRACT FROM AUTHOR]

Information hiding is a crucial technology in the field of information security. Embedding capacity and stego-image quality are two key performance metrics in information hiding. In recent years, many information-hiding methods have been proposed to enhance embedding capacity and stego-image quality. However, through the study of these methods, we found that there is still room for improvement in terms of performance. This paper proposes a high-capacity information-hiding method based on a chunking matrix (CM). CM divides a 256×256 matrix into blocks, where each block contains k×k corresponding secret numbers. A pair of pixels is extracted from the original image and used as the coordinates for the matrix. In the search domain at that coordinate position, the corresponding secret number is found, and the matrix coordinates of the secret information are used as the pixel value for the stego-image. This paper evaluates the security and effectiveness of CM through measures such as embedding capacity, peak signal-to-noise ratio (PSNR), and bit-plane analysis. CM achieves a maximum embedding capacity of 4.806 bits per pixel (bpp) and maintains a PSNR value of more than 30 dB. Furthermore, the bit-plane analysis fails to detect the presence of the information hidden using CM method. [ABSTRACT FROM AUTHOR]

This work deals with digital image processing using the steganography technique in real life. Various steganography techniques face data authentication, data security, and copyright issues. Due to the fact that the problem of data security is currently very topical, these techniques are often sought after. This is related to the constant development of new algorithms that provide solutions that will safely hide the secret message in the image and at the same time will be resistant to various types of attacks. The motivation for writing this work lies in the technique of representing a secret message using a Quick Response code. Later in this work is comparison between our results and results of approach made by scientific community, which works with data hiding within steganographic principles. The secret message is written in the least significant bit plane of the cover image, which ensures that the modification of the image cannot be detected by the naked eye. The proposed solution is evaluated by mathematical quality assessment parameters Peak signal-to-noise ratio, Mean squared error, Normalized cross-correlation and Structural similarity index.