Embedding Secret Data Research Articles

Enhanced secure lossless image steganography using invertible neural networks

Image steganography is a technique that embeds secret data into cover images in an imperceptible manner, ensuring that the original data can be recovered by the receiver without arousing suspicion. The key challenges currently faced by image steganography are capacity, invisibility, and security. We suggest an invertible neural network-based image steganography technique to concurrently address these three issues. To achieve better invisibility, we adopt a method that avoids the loss of information, thereby preventing ill-posed problems. The learning cost during image embedding can be reduced by only fitting part of the color channels in order to address the issue of high capacity. Additionally, we introduce the concept of a key to constrain the embedding process of the secret information, significantly enhancing the security of the hidden data. According to our experimental results, our method outperforms other image steganography algorithms on DIV2K, COCO, and ImageNet datasets, achieving perfect recovery of the secret images, its PSNR and SSIM can reach the theoretical maximum values.

High Capacity Adaptive Block-Based Color Image Steganography and Human Perception-Guided Steganalysis

In the realm of image steganography, where the delicate balance between secrecy and visibility is paramount, our proposed method represents a significant advancement. We leverage the human eye's heightened sensitivity to subtle changes in smoother image regions, introducing a novel approach to embedding secret data. Unlike conventional methods, our approach delves deep into the intricacies of each RGB plane in color images, optimizing data embedding while preserving visual integrity. Through a sophisticated block complexity measurement and selection process, we harness image redundancy efficiently using the Hilbert scan pattern. What distinguishes our method is its simplicity and self-sufficiency; no additional complexity is required for data extraction. Our experiments on benchmark datasets validate the superior stego image quality and precise data embedding capabilities of our approach. Moreover, our innovative human perception-based validation approach accounts for the complexities of the human visual system and subjective perceptions, enhancing the reliability of our method. This research not only advances the field of steganography but also lays the groundwork for more effective data hiding applications in color imagery.

Advancements in Spatial Domain Image Steganography: Techniques, Applications, and Future Outlook

Abstract. Image steganography, a technique for transmitting secret information hidden within images over public networks undetected, serves as a discreet alternative to cryptography in the field of information security. This article explores new steganography techniques based on the Least Significant Bit (LSB) method, widely recognized for its simplicity in embedding secret data by altering the least significant bit of pixels in the spatial domain. The performance of these LSB-based methods is critically assessed using criteria such as Peak Signal-to-Noise Ratio (PSNR), embedding capacity, and histogram analysis. A comprehensive review of recent literature provides a foundation for this evaluation, highlighting advancements and identifying areas for future improvement. Additionally, the article discusses practical applications of LSB-based steganography in healthcare, government operations, and cloud storage, suggesting directions for further research and development in this subtly powerful area of data security.

PSO-based Quaternion Fourier Transform steganography: Enhancing imperceptibility and robustness through multi-dimensional frequency embedding

This paper presents a novel steganography technique using the Quaternion Fourier Transform (QFT) in the 4D frequency domain to enhance imperceptibility and robustness in digital image embedding. Steganography, the art of hiding information within media, faces challenges in balancing security, imperceptibility, and robustness. To address this, we leverage the multi-dimensional properties of quaternions, enabling the embedding of secret data in both grayscale and color images. For grayscale images, two quaternion dimensions are utilized for intensity and secret data, while for color images, all four dimensions are employed with one reserved for metadata. The research question centers on how to maximize spatial dispersion and color similarity while maintaining high imperceptibility and robustness against attacks. Experimental results show that the proposed method improves visual imperceptibility by more than 4 % and exhibits a 13 % increase in robustness against common steganalysis attacks compared to the best state-of-the-art existing technique. These advancements highlight the potential of this method for applications in secure communication, digital watermarking, and copyright protection. By combining the quaternion mathematical framework with a novel optimization strategy, this approach significantly improves upon traditional steganography methods.

Stealthy Messaging: Leveraging Message Queuing Telemetry Transport for Covert Communication Channels

Covert channel methods are techniques for improving privacy and security in network communications. These methods consist of embedding secret data within normal network channels, making it more difficult for unauthorized parties to detect such data. This paper presents a new approach for creating covert channels using the Message Queuing Telemetry Transport (MQTT) protocol, widely used in the context of the Internet of Things (IoT). The proposed method exploits storage channels by altering the field length of MQTT messages. Our solution leverages well-known one-way mathematical functions to ensure that data remain hidden from third parties observing the MQTT stream. In this way, we ensure that not only the content of the communication is preserved but also that the communication itself takes place. We conducted a security analysis to show that our solution offers the above-mentioned property even against severe threats, such as an adversary being able to observe all the messages exchanged in the network (even in the clear). Finally, we conducted an overhead analysis of our solution both in terms of the time required to perform the required operations and of the bytes to send. Our study shows that our solution adds no significant time overhead, and the additional overhead in terms of transmitted bytes remains within acceptable limits.

Reversible data hiding in encrypted images based on secret sharing and hierarchical embedding

With the increasing emphasis on information security, reversible data hiding technology in encrypted images (RDH-EI) has been widely applied in cloud storage privacy protection in recent years. However, once the data hider is leaked or compromised, the current algorithm of RDH-EI will encounter the challenge of effectiveness and security. In order to tackle this issue, this paper proposes an RDH-EI scheme based on secret sharing and hierarchical embedding. First, an image secret sharing based on (4, 6)-threshold algorithm is proposed. This algorithm aims to combine image encryption and sharing processes to generate six different encrypted images with vertical correlation. Sending them in encrypted form to cloud storage is beneficial for protecting the semantics of cover image. Then, the hierarchical embedding method is suggested to attain a high embedding payload. In this approach, by analyzing the vertical correlation of adjacent pixels, we have designed three mapping rules based on multi-MSB prediction. Among them, case 1 reserves the highest embedding capacity, case 2 follows, and case 3 has no embedding space. Based on this, the paper can adaptively embed secret data. Finally, fully authorized users can extract secret data and restore the original image by decrypting four or more marked encrypted images. Experimental results indicate that our approach surpass some existing RDH-EI approaches in payload, which average payloads in the best case on the BOSSbase and BOWS-2 datasets reach 4.466 bpp and 4.152 bpp, respectively. Additionally, the proposed RDH-EI method transfers and stores image data in a distributed manner, which helps prevent excessive concentration of power by data hiders and misuse of data. Compared to traditional end-to-end RDH-EI schemes, the proposed approach offers higher security.

Separable Reversible Data Hiding for Encrypted 3D Meshes Based on Self-Organized Blocking and Most Significant Bit Prediction

As a booming technique that allows secret data extraction and information carrier recovery without any loss, reversible data hiding in different carriers has attracted more and more concerns in the field of information security. In this paper, a separable reversible data hiding technique for encrypted 3D meshes is proposed based on self-organized blocking and most significant bit (MSB) prediction. The content-owner traverses all faces of the mesh in the ascending index order. Through self-organized blocking, adjacent vertices are concentrated in different small sets. The central vertex is considered as the reference and the others as embedded vertices in each set. Then, multiple most significant bits between the central vertex and others are adaptively predicted and reserved as embeddable bits for secret data embedding. Because vertex coordinates in each set have a high space correlation and most vertices participate in the prediction process, a huge number of most significant bits can be marked as embeddable bits to embed secret data. Experimental results demonstrate that the proposed method can obtain the highest embedding rate compared with representative methods. To our best knowledge, the average embedding rate of the proposed method is about 28 bits per vertex (bpv) higher than the recently proposed method. Most importantly, instead of recovering meshes with higher quality, original meshes with high visual symmetry/quality can be recovered.

GAN-Based Steganography: Enhancing Data Concealment

Ensuring the secure transfer of information across networks is paramount to uphold confidentiality and privacy, both of which are critical in today's society. To safeguard information from unauthorized access, interception, or tampering during communication, various protective techniques are employed. Steganography is one such method, involving the concealment of information within a cover medium, such as an image, so that the presence of the hidden message remains undetected. This approach is particularly valuable when cryptographic measures alone are insufficient for protecting sensitive data. Even if the cover image is intercepted, the concealed message should only be accessible to the intended sender and recipient. Our proposed solution addresses security risks by embedding secret data within stego-images generated through Generative Adversarial Networks (GANs), and then accurately extracting it with a decoder. The advantage of using GANs lies in their ability to produce images that are visually realistic and appealing, thus minimizing the chances of the hidden message being discovered. Furthermore, this platform can be adapted to prevent digital piracy by embedding watermarks into digital content, and it can be further refined with expert input.

Digital Steganography : A Comprehensive Study on Various Methods for Hiding Secret Data in a Cover file

This research paper offers an in-depth examination of digital steganography, with a focus on the diverse methodologies utilized for embedding secret data within cover files. Steganography, the practice of concealing information within other non-secret data, ensures the hidden message remains undetectable to unauthorized observers. This study systematically reviews both traditional and modern steganographic techniques, dissecting their fundamental mechanisms, advantages, and weaknesses. Techniques explored include Least Significant Bit (LSB) insertion, discrete cosine transform (DCT), discrete wavelet transform (DWT), and innovative methods leveraging deep learning and adaptive algorithms. Each method is assessed for its imperceptibility, robustness, and data capacity, offering a comparative analysis to underscore their respective practical applications and limitations. Additionally, the paper delves into steganalysis—methods for detecting hidden information—to provide a comprehensive perspective on the field. Through experimental evaluation and theoretical analysis, this study seeks to enhance the understanding of digital steganography, presenting insights that could inform future research and the development of more secure data hiding techniques.

Data Hiding and Authentication Scheme for Medical Images Using Double POB

To protect the security of medical images and to improve the embedding ability of data in encrypted medical images, this paper proposes a permutation ordered binary (POB) number system-based hiding and authentication scheme for medical images, which includes three parts: image preprocessing, double hiding, and information extraction and lossless recovery. In the image preprocessing and double hiding phase, firstly, the region of significance (ROS) of the original medical image is segmented into a region of interest (ROI) and a region of non-interest (RONI). Then, the bit plane of the ROI and RONI are separated and cross-reorganization to obtain two new Share images. After the two new Share images are compressed, the images are encrypted to generate two encrypted shares. Finally, the embedding of secret data and attaching of authentication bits in each of these two encrypted shares was performed using the POB algorithm. In the information extraction and lossless recovery phase, the POBN algorithm is first used to extract the authentication bits to realize image tamper detection; then, the embedded secret message is extracted, and the original medical image is recovered. The method proposed in this research performs better in data embedding and lossless recovery, as demonstrated by experiments.

Reversible data hiding in encrypted image with secure multi-party for telemedicine applications

Privacy protection of electronic patient information (EPI) is a crucial concern in the telemedicine applications, especially when it comes to communication between patients and doctors. In this paper, we propose a high-capacity reversible data hiding (RDH) algorithm combined with secure multi-party computation for telemedicine applications. The pixel values within a 3 × 3-size image block are divided into embedded pixels (EPs) and sampled pixels (SPs), secret data is embedded into the prediction errors of EPs and SPs in two stages. In the first stage, two edge servers predict EPs using the four SPs in the block to obtain the prediction error of EPs. The secret data is embedded into EPs through addition operation and histogram shift method. In the second stage, the prediction error of SPs is calculated as the difference between EPs and SPs, and the embedding of secret data follows the same method as used in the first stage. The experimental results demonstrate that the proposed algorithm achieves a higher embedding rate compared to classical and state-of-the-art algorithms, with an average embedding rate of 0.47bpp on the UCID dataset. Furthermore, the proposed algorithm exhibits robustness against existing attacks.

Dynamic feedback bit-level image privacy protection based on chaos and information hiding

Bit is the most basic unit of a digital image in the spatial domain, and bit-level encryption is regarded as an important technical means for digital image privacy protection. To address the vulnerability of image privacy protection to cryptographic attacks, in this paper, a bit-level image privacy protection scheme using Zigzag and chain-diffusion is proposed. The scheme uses a combination of Zigzag interleaving scrambling with chaotic sequences and chain-diffusion method images are encrypted at each bit level, while using non-sequential encryption to achieve efficient and secure encryption. To balance security and efficiency, the encryption strategy for each bit layer is weighted. The chaos-based sequences used for encryption depend on the previous hash value, thus the effect of chain-diffusion is achieved. To further enhance the encryption effect, a non-sequential encryption technique by non-linearly rearranging the bit cipher image is employed, so that the attacker cannot crack the protection scheme by analyzing the encrypted image. The ciphertext image hidden by discrete wavelet transform (DWT) also provides efficient encryption, higher level of security and robustness to attacks. This technology provides indistinguishable secret data embedding, making it difficult for attackers to detect or extract hidden information. Experimental results show that this scheme can effectively protect the confidentiality of the image and can resist various common cryptographic attacks. The scheme proposed in this paper is a preferred digital image privacy protection technology, so it has broad application prospects in image secure transmission occasions.

Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction

Reversible data hiding (RDH) is a technique that embeds secret data into digital media while preserving the integrity of the original media and the secret data. RDH has a wide range of application scenarios in industrial image processing, such as intellectual property protection and data integrity verification. However, with the increasing prevalence of color images in industrial applications, traditional RDH methods for grayscale images are inadequate to meet the requirements of image fidelity. This paper proposes an RDH method for color images based on channel reference mapping (CRM) and adaptive pixel prediction. Initially, the CRM mode for a color image is established based on the pixel variation correlation between the RGB channels. Then, the pixel local complexity context is adaptively selected using the CRM mode. Next, each pixel value is adaptively predicted based on the features and characteristics of adjacent pixels and reference channels, and then data is embedded by expanding the prediction error. Finally, we compare seven existing RDH algorithms on the standard image dataset and the Kodak dataset to validate the advantages of our method. The experimental results demonstrate that our approach achieves average peak signal-to-noise ratio (PSNR) values of 63.61 and 60.53 dB when embedding 20,000 and 40,000 bits of data, respectively. These PSNR values surpass those of other RDH methods. These findings indicate that our method can effectively preserve the visual quality of images even under high embedding capacities.

Security analysis of a reversible data hiding scheme in encrypted images by redundant space transfer

Redundant space transfer (RST) encryption can effectively enhance the security and embedding capacity of reversible data hiding in encrypted images. To demonstrate the security risks of RST encryption in the cloud environment, according to the known plaintext image and marked encrypted image(MEI) pairs, this paper proposes a known plaintext attack (KPA) based on hamming-weight of bit block. The proposed KPA method includes two stages. The first stage is to find the correct ciphertext image. For possible block sizes, all possible ciphertext images of MEI are reconstructed by deleting the embedded secret data. The Hamming weight image (HWI) of plaintext and all possible ciphertext images is calculated in m×8n domain (m, n is the image size). When the histogram distance between the plaintext HWI and a possible ciphertext HWI is the minimum, the correct ciphertext image is found. The second stage is to estimate the permutation keys. The bit block characteristic matrix (BBCM) is defined by using that the bit values of plaintext and ciphertext remain unchanged in the process of RST encryption. Based on the intersection of BBCM’s index set, the block permutation key is directly estimated. Then, the bit plane permutation key in each image block is further estimated. Experimental results show that for RST encryption, when the block size is not less than 3 × 3, the block permutation and bit plane permutation key can be estimated in less than 3 min by using one pair of plain–ciphertext. The estimation accuracy of block permutation key is more than 50%, and the estimation accuracy of bit plane permutation key is 10% for Qin’s RST algorithm, most of the content information of the ciphertext image is leaked.

High Payload Lossless Steganography Using Image Interpolation

Interpolation-based reversible data hiding (IRDH) is a method for embedding data in a reversible manner into digital images. It is based on the polynomial interpolation to hide the secret data bit stream in the coefficients of the interpolation polynomial. In this paper, an IRDH method that combines a modified neighbor mean interpolation is presented with a new method for reversibly embedding secret data in interpolated pixels. This method uses log base 2 of the decimal value of the interpolated pixel to replace a corresponding number of bits with the bits of the secret data, allowing for a higher bit stream to be embedded with better image quality. The results from experiments show that the introduced method can implant on average, 1300000 bits of secret data with an average PSNR of 28.5 dB, which is a significant improvement over existing and related works.

A Multistage High Capacity Reversible Data Hiding Technique Without Overhead Communication

Reversible Data Hiding(RDH) has been extensively investigated, recently, due to its numerous applications in the field of defence, medical, law enforcement and image authentication. However, most of RDH techniques suffer from low secret data hiding capacity and communication overhead. For this, multistage high-capacity reversible data hiding technique without overhead is proposed in this manuscript. Proposed reversible data hiding approach exploits histogram peaks for embedding the secret data along with overhead bits both in plain and encrypted domain. First, marked image is obtained by embedding secret data in the plain domain which is further processed using affine cipher maintaining correlation among the pixels. In second stage, overhead bits are embedded in the encrypted marked image. High embedding capacity is achieved through exploiting histogram peak for embedding multiple bits of secret data. Proposed approach is experimentally validated on different datasets and results are compared with the state-of-the-art techniques over different images.

A New Approach for Roni Based Medical Image Watermarking Using Contourlet Transform

The majority of modern healthcare systems rely their diagnoses on data collected from the internet. The medical imaging and patient health records are transmitted over the network via the internet-enabled healthcare (E-health) applications. In practical medical applications, the primary problem is the security of medical images transmitted over the internet. For the purpose of embedding secret data on medical images without affecting important information, a trustworthy watermarking approach is required. We provide a unique watermarking approach in this research that embeds the watermark data in the medical image's Region of Non- Interest (RONI). The medical image is subjected to a contourlet transform, and RONI is determined using contourlet coefficients. In this work, we demonstrate the embedding and extraction process of medical image watermarking using Contourlet transform. Experiments are carried out on medical images such as MRI and CT images. The performance of the proposed scheme is analyzed using the metric PSNR. The proposed scheme provides an average PSNR value of 47.1604% for MRI images and 57.5452% of PSNR for CT images.

Steganography: The Art of Encrypting and Decrypting Information with Different Hiding Tools and Command Prompt

The concealing information within other non-secret data to hide its existence. It involves embedding secret messages or data within innocuous carriers, like images, audio files, or text. This hidden information is often encrypted to enhance security. Steganography focuses on maintaining the secrecy of the communication. The efficiency of two steganography tools Shusssh and SteganographX Plus freely available on internet. Different file format of images (JPEG, JPG and BMP) were analysed by Windows-based Command Prompt Utility and two different steganography tools (Shusssh! and SteganographX Plus).

Digital Watermarking, Methodology, Techniques, and Attacks: A Review

The use of multimedia technology is growing every day, and it is difficult and time-consuming to provide allowed data while preventing secret information from being used without authorization. The material that has been watermarked can only be accessed by authorized users. Digital watermarking is a popular method for protecting digital data. The embedding of secret data into actual information is the subject of digital watermarking. This paper examines watermarking techniques, methodologies, and attacks, as well as the development of watermarking digital images stored in both the spatial and frequency domains.

Segmentation embedding method with modified interpolation for increasing the capacity of adaptable and reversible audio data hiding

The development of digital technology brings many advantages to human life. However, it also comes with the risk of making data protection required. This protection can come in many forms, one of which is the data hiding method, often called steganography. It works by embedding secret data into media data, such as images, audio, and video, to avoid suspicion caused by their existence. Nevertheless, the embedding capacity and stego-data quality problems have become challenging. This research proposed new audio steganography, which utilizes modified linear interpolation values to give flexibility to the embedding capacity. This proposed method also adds bit thresholds to distribute the embedding capacity as evenly as possible to maintain its similarity level (quality) as high as possible by shifting the embedded sample value towards the original value of stego-data produced. The experimental results show that this method can obtain an average similarity level of 100.55 dB on 0.75 bit per sample audio data and 87.68 dB on 2.267 bit per sample audio data. The stability of stego-data quality is also measured by considering the best and minimum quality measurements with a difference of less than 1 dB on embedding secret data below 1.52 bit per sample.