Coverless Steganography for Digital Images Based on a Generative Model

In this paper, we propose a novel coverless image steganographic scheme based on a generative model. In our scheme, the secret image is first fed to the generative model database, to generate a meaning-normal and independent image different from the secret image. The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image. Thus, we only need to transmit the meaning-normal image which is not related to the secret image, and we can achieve the same effect as the transmission of the secret image. This is the first time to propose the coverless image information steganographic scheme based on generative model, compared with the traditional image steganography. The transmitted image is not embedded with any information of the secret image in this method, therefore, can effectively resist steganalysis tools. Experimental results show that our scheme has high capacity, security and reliability.     

Analysis and Improvement of Steganography Protocol Based on Bell States in Noise Environment

In the field of quantum communication, quantum steganography is an important branch of quantum information hiding. In a realistic quantum communication system, quantum noises are unavoidable and will seriously impact the safety and reliability of the quantum steganographic system. Therefore, it is very important to analyze the influence of noise on the quantum steganography protocol and how to reduce the effect of noise. This paper takes the quantum steganography protocol proposed in 2010 as an example to analyze the effects of noises on information qubits and secret message qubits in the four primary quantum noise environments. The results show that when the noise factor of one quantum channel noise is known, the size of the noise factor of the other quantum channel can be adjusted accordingly, such as artificially applying noise, so that the influence of noises on the protocol is minimized. In addition, this paper also proposes a method of improving the efficiency of the steganographic protocol in a noisy environment.     

Steganalysis of images based on spatial domain and two-dimensional JPEG array

The aim of digital image steganalysis is to detect hidden information (which can be a message or an image) in a steganographic image. An ideal steganography method encrypts the information in the image such that it cannot be easily detected. Currently, a wide variety of different steganography techniques are being used; therefore, more advanced steganalysis methods are needed that can detect the steganographic images coded by different techniques. A typical steganalysis technique consists of two parts: (1) feature extraction and (2) classification. In this paper, a new steganalysis technique based on the Markov chain process is proposed. In the proposed technique, after extraction of the new features, a non-linear classifier named support vector machine is applied to classify clean and encrypted images. Analysis of variance is used to reduce the dimensions of the proposed features. The performance of the proposed technique is compared against subtractive DCT coefficient adjacency matrix (SDAM) and subtractive pixel adjacency matrix (SPAM) methods using an image database prepared by three strong steganography techniques called yet another steganographic scheme, model based, and perturbed quantization. The obtained results show that the proposed method provides better performance than SDAM and SPAM methods.     

Imaging through Nonlinear Metalens Using Second Harmonic Generation

The abrupt phase change of light at metasurfaces provides high flexibility in wave manipulation without the need for accumulation of propagating phase through dispersive materials. In the linear optical regime, one important application field of metasurfaces is imaging by planar metalenses, which enables device miniaturization and aberration correction compared to conventional optical microlens systems. With the incorporation of nonlinear responses into passive metasurfaces, optical functionalities of metalenses are anticipated to be further enriched, leading to completely new application areas. Here, imaging with nonlinear metalenses that combine the function of an ultrathin planar lens with simultaneous frequency conversion is demonstrated. With such nonlinear metalenses, imaging of objects with near infrared light while the image appears in the second harmonic signal of visible frequency range is experimentally demonstrated. Furthermore, the functionality of these nonlinear metalenses can be modified by switching the handedness of the circularly polarized fundamental wave, leading to either real or virtual nonlinear image formation. Nonlinear metalenses not only enable infrared light imaging through a visible detector but also have the ability to modulate nonlinear optical responses through an ultrathin metasurface device while the fundamental wave remains unaffected, which offers the capability of nonlinear information processing with novel optoelectronic devices.     

New LSB-based colour image steganography method to enhance the efficiency in payload capacity,security and integrity check

Steganography is the technique for hiding information within a carrier file so that it is imperceptible for unauthorized parties. In this study, it is intended to combine many techniques to gather a new method for colour image steganography to obtain enhanced efficiency, attain increased payload capacity, posses integrity check and security with cryptography at the same time. Proposed work supports many different formats as payload. In the proposed method, the codeword is firstly formed with secret data and its CRC-32 checksum, then the codeword is compressed by Gzip just before encrypting it by AES, and it is finally added to encrypted header information for further process and then embedded into the cover image. Embedding the encrypted data and header information process utilizes Fisher-Yates Shuffle algorithm for selecting next pixel location. To hide one byte, different LSB (least significant bits) of all colour channels of the selected pixel is exploited. In order to evaluate the proposed method, comparative performance tests are carried out against different spatial image steganographic techniques using some of the well-known image quality metrics. For security analysis, histogram, enhanced LSB and Chi-square analyses are carried out. The results indicate that with the proposed method has an improved payload capacity, security and integrity check for common problems of simple LSB method. Moreover, it has been shown that the proposed method increases the visual quality of the stego image when compared to other studied methods, and makes the secret message difficult to be discovered.     

Digital video steganalysis using motion vector recovery-based features

As a novel digital video steganography, the motion vector (MV)-based steganographic algorithm leverages the MVs as the information carriers to hide the secret messages. The existing steganalyzers based on the statistical characteristics of the spatial/frequency coefficients of the video frames cannot attack the MV-based steganography. In order to detect the presence of information hidden in the MVs of video streams, we design a novel MV recovery algorithm and propose the calibration distance histogram-based statistical features for steganalysis. The support vector machine (SVM) is trained with the proposed features and used as the steganalyzer. Experimental results demonstrate that the proposed steganalyzer can effectively detect the presence of hidden messages and outperform others by the significant improvements in detection accuracy even with low embedding rates.     

A MV-Based Steganographic Algorithm for H.264/AVC without Distortion

H.264/AVC video is one of the most popular multimedia and has been widely used as the carriers of video steganography. In this paper, a novel motion vector (MV) based steganographic algorithm is proposed for the H.264/AVC compressed video without distortion. Four modules are introduced to eliminate the distortion caused by the modifications of motion vectors and guarantee the security of the algorithm. In the embedding block, the motion vector space encoding is used to embed a (2n+1)-ary notational number into an n-dimension vector composed of motion vectors generated from the selection block. Scrambling is adopted to disturb the order of steganographic carriers to improve the randomness of the carrier before the operation of embedding. The re-motion compensation (re-MC) block will re-construct the macroblock (MB) whose motion vectors have been modified by embedding block. System block plays the role of the generator for chaotic sequences and encryptor for secret data. Experimental results demonstrate that our proposed algorithm can achieve high embedding capacity without stego video visual quality distortion, it also presents good undetectability for existing MV-based steganalysis feature. Performance comparisons with other existing algorithms are provided to demonstrate the superiority of the proposed algorithm.     

Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture. We use seeded region growing algorithm to ensure texture’s similar local appearance. Secondly, the size and capacity of image can be decreased by introducing the information segmentation, because the capacity of the secret information is proportional to the size of the synthetic texture. Thirdly, enhanced security is also a contribution in this research, because our method does not need to transmit parameters for secret information extraction. LSB is used to embed these parameters in the synthetic texture.     

A Novel Steganography Algorithm Based on Instance Segmentation

Information hiding tends to hide secret information in image area where is rich texture or high frequency, so as to transmit secret information to the recipient without affecting the visual quality of the image and arousing suspicion. We take advantage of the complexity of the object texture and consider that under certain circumstances, the object texture is more complex than the background of the image, so the foreground object is more suitable for steganography than the background. On the basis of instance segmentation, such as Mask R-CNN, the proposed method hides secret information into each object's region by using the masks of instance segmentation, thus realizing the information hiding of the foreground object without background. This method not only makes it more efficient for the receiver to extract information, but also proves to be more secure and robust by experiments.     

From Single‐Dimensional to Multidimensional Manipulation of Optical Waves with Metasurfaces

Metasurfaces, 2D artificial arrays of subwavelength elements, have attracted great interest from the optical scientific community in recent years because they provide versatile possibilities for the manipulation of optical waves and promise an effective way for miniaturization and integration of optical devices. In the past decade, the main efforts were focused on the realization of single‐dimensional (amplitude, frequency, polarization, or phase) manipulation of optical waves. Compared to the metasurfaces with single‐dimensional manipulation, metasurfaces with multidimensional manipulation of optical waves show significant advantages in many practical application areas, such as optical holograms, sub‐diffraction imaging, and the design of integrated multifunctional optical devices. Nowadays, with the rapid development of nanofabrication techniques, the research of metasurfaces has been inevitably developed from single‐dimensional manipulation toward multidimensional manipulation of optical waves, which greatly boosts the application of metasurfaces and further paves the way for arbitrary design of optical devices. Herein, the recent advances in metasurfaces are briefly reviewed and classified from the viewpoint of different dimensional manipulations of optical waves. Single‐dimensional manipulation and 2D manipulation of optical waves with metasurfaces are discussed systematically. In conclusion, an outlook and perspectives on the challenges and future prospects in these rapidly growing research areas are provided.     

Coverless Image Steganography Based on Jigsaw Puzzle Image Generation

Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels, creating the stego image. However, the left traces that are caused by these modifications will make steganalysis algorithms easily detect the hidden payload. A coverless data hiding concept is proposed to solve this issue. Coverless does not mean that cover is not required, or the payload can be transmitted without a cover. Instead, the payload is embedded by cover generation or a secret message mapping between the cover file and the payload. In this paper, a new coverless image steganography method has been proposed based on the jigsaw puzzle image generation driven by a secret message. Firstly, the image is divided into equal rows then further divided into equal columns, creating blocks (i.e., sub-images). Then, according to secret message bits and a proposed mapping function, each block will have tabs/blanks to get the shape of a puzzle piece creating a fully shaped jigsaw puzzle stego-image. After that, the generated jigsaw puzzle image is sent to the receiver. Experimental results and analysis show a good performance in the hiding capacity, security, and robustness compared with existing coverless image steganography methods.     

A Novel Quantum Stegonagraphy Based on Brown States

In this paper, a novel quantum steganography protocol based on Brown entangled states is proposed. The new protocol adopts the CNOT operation to achieve the transmission of secret information by the best use of the characteristics of entangled states. Comparing with the previous quantum steganography algorithms, the new protocol focuses on its anti-noise capability for the phase-flip noise, which proved its good security resisting on quantum noise. Furthermore, the covert communication of secret information in the quantum secure direct communication channel would not affect the normal information transmission process due to the new protocol’s good imperceptibility. If the number of Brown states transmitted in carrier protocol is many enough, the imperceptibility of the secret channel can be further enhanced. In aspect of capacity, the new protocol can further expand its capacity by combining with other quantum steganography protocols. Due to that the proposed protocol does not require the participation of the classic channel when it implements the transmission of secret information, any additional information leakage will not be caused for the new algorithm with good security. The detailed theoretical analysis proves that the new protocol can own good performance on imperceptibility, capacity and security.     

A Fusion Steganographic Algorithm Based on Faster R-CNN

The aim of information hiding is to embed the secret message in a normal cover media such as image, video, voice or text, and then the secret message is transmitted through the transmission of the cover media. The secret message should not be damaged on the process of the cover media. In order to ensure the invisibility of secret message, complex texture objects should be chosen for embedding information. In this paper, an approach which corresponds multiple steganographic algorithms to complex texture objects was presented for hiding secret message. Firstly, complex texture regions are selected based on a kind of objects detection algorithm. Secondly, three different steganographic methods were used to hide secret message into the selected block region. Experimental results show that the approach enhances the security and robustness.     

Coverless Image Steganography Based on Image Segmentation

To resist the risk of the stego-image being maliciously altered during transmission, we propose a coverless image steganography method based on image segmentation. Most existing coverless steganography methods are based on whole feature mapping, which has poor robustness when facing geometric attacks, because the contents in the image are easy to lost. To solve this problem, we use ResNet to extract semantic features, and segment the object areas from the image through Mask RCNN for information hiding. These selected object areas have ethical structural integrity and are not located in the visual center of the image, reducing the information loss of malicious attacks. Then, these object areas will be binarized to generate hash sequences for information mapping. In transmission, only a set of stego-images unrelated to the secret information are transmitted, so it can fundamentally resist steganalysis. At the same time, since both Mask RCNN and ResNet have excellent robustness, pre-training the model through supervised learning can achieve good performance. The robust hash algorithm can also resist attacks during transmission. Although image segmentation will reduce the capacity, multiple object areas can be extracted from an image to ensure the capacity to a certain extent. Experimental results show that compared with other coverless image steganography methods, our method is more robust when facing geometric attacks.     

Hierarchical secret image sharing using phase modulation based on the Fresnel transform

ABSTRACT

In idealized secret image sharing (SIS), all of the shared images (shadows) play the same role, but in real life, the shared images are often hierarchical. This paper proposes a hierarchical secret image sharing (HSIS) method by means of optical imaging. To implement the scheme, a generalized single-phase modulation algorithm is proposed in Fresnel transform domain. Its features that multiple secret images can be recovered through combination of some shared images though each participant only holds one share of images. Theoretically, the secret images are divided into multiple phase encodings (shared images) by phase modulation, each secret image can be directly captured by the intensity detector when illuminating some of the shared images orderly displayed with parallel light. Experimental simulation shows that the shared images and the restored secret images do not have any size distortion, and further verifies the feasibility of the proposed scheme.     

An Image Steganography Algorithm Based on Quantization Index Modulation Resisting Scaling Attacks and Statistical Detection

In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method, this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection. For the spatial image, this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain. Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography, and use the minimum distortion coding to realize the embedding of the secret messages. Finally, according to the embedding modification amplitude of secret messages in the new embedded domain, the quantization index modulation algorithm is applied to realize the final embedding of secret messages in the original embedded domain. The experimental results show that the algorithm proposed is robust to the three common interpolation attacks including the nearest neighbor interpolation, the bilinear interpolation and the bicubic interpolation. And the average correct extraction rate of embedded messages increases from 50% to over 93% after 0.5 times-fold scaling attack using the bicubic interpolation method, compared with the classical steganography algorithm S-UNIWARD. Also the algorithm proposed has higher detection resistance than the original watermarking algorithm based on quantization index modulation.     

基于灰度图像的像素量化隐写算法

目的为了提高灰度图像处理的规模、嵌入量、安全性及鲁棒性,提出一种基于灰度图像的像素量化隐写算法。方法首先对载体图像进行Hilbert曲线扫描和图像像素量化,将量化信息产生的阈值区域准确地划分标记,然后分别对载体图像、待嵌入信息执行Hilbert置乱和D-S(data encryption security algorithm)数据加密处理,最后将加密后产生的秘密信息和相关辅助信息嵌入密文图像内。结果实验结果表明,该算法的嵌入率相较于原算法提升了10%,接收者能通过密钥解密获取原始信息,还原完整的载体图像。结论该隐写算法信息嵌入率高,鲁棒性和安全性较强。     

A robust information hiding scheme for tampered cover images

In this paper, we propose a robust information hiding scheme such that the secret information is restorable upon cover image tampering. The secret information is first translated into a binary image, and then the binary image is encoded into an ‘index table’ via Vector Quantisation (VQ). Without noticeable damage to image quality, the secret information codes (VQ index table of secret information) are hidden repeatedly into the cover image. Using our proposed scheme, the extracted secret codes can be almost completely restored to their original state even when the cover image has been tampered with. Experimental results show that our proposed scheme restores the secret information perfectly under many types of tampering attacks.     

Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix

In recent years, binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security. In most state-of-the-art binary image steganographic schemes, they always find out the flippable pixels to minimize the embedding distortions. For this reason, the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain. However, the distortion maps can be calculated for cover and stego images and the difference between them is significant. In this paper, a novel binary image steganalytic scheme is proposed, which is based on distortion level co-occurrence matrix. The proposed scheme first generates the corresponding distortion maps for cover and stego images. Then the co-occurrence matrix is constructed on the distortion level maps to represent the features of cover and stego images. Finally, support vector machine, based on the gaussian kernel, is used to classify the features. Compared with the prior steganalytic methods, experimental results demonstrate that the proposed scheme can effectively detect stego images.     

Multichannel‐Independent Information Encoding with Optical Metasurfaces

Optical metasurfaces, as an emerging platform, have been shown to be capable of effectively manipulating the local properties (amplitude, phase, and polarization) of the reflected or transmitted light and have unique strengths in high‐density optical storage, holography, display, etc. The reliability and flexibility of wavefront manipulation makes optical metasurfaces suitable for information encryption by increasing the possibility of encoding combinations of independent channels and the capacity of encryption, and thus the security level. Here, recent progress in metasurface‐based information encoding is reviewed, in which the independent channels for information encoding are built with wavelength and/or polarization in one‐dimensional/two‐dimensional (1D/2D) modes. The way to increase information encoding capacity and security level is proposed, and the opportunities and challenges of information encoding with independent channels based on metasurfaces are discussed.