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.     

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.     

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.     

Varying index varying bits substitution algorithm for the implementation of VLSB steganography

Variable least significant bits (VLSB) steganography is a pretty powerful and secure technique for data hiding in cover images, having variable data hiding capacity, signal-to-noise ratio, peak signal-to-noise ratio, and mean square error (MSE). This study presents a new algorithm for the implementation of VLSB steganography named varying index varying bits substitution (VIVBS). The VIVBS algorithm is a very secure, high capacity, flexible, and statistically unpredictable mechanism to conceal information in cover images. The method uses a secret stego-key comprising a reference point, and variation of the number of bits to be hidden with varying indices of pixels in the cover image. The secret key adds an extra feature of security to steganography, making it much immune to steganalysis. The VIVBS algorithm is capable of providing variable data hiding capacity and variable key size which can be changed by changing the range of least significant bits used. A data hiding capacity of 43.75% with a negligible MSE 14.67 dB has been achieved using the VIVBS algorithm. For larger data hiding capacity, the MSE and distortion increases significantly which make the existence of information predictable but the key size also increases significantly, making the retrieval of hidden information difficult for the unauthorized person.     

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.     

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.     

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。     

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.     

Improved security in the genetic algorithm-based image steganography scheme using Hilbert space-filling curve

This paper presents the security analysis of a recently proposed data hiding scheme by Kanan and Nazeri [A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm. Expert Syst Appl. 2014;41(14):6123–6130]. Security of the scheme depends upon a secret key\chromosome constructed using a genetic algorithm. The key specifies offsets and patterns for data embedding. By performing the key-sensitivity analysis and exploiting image pixel correlation, it is shown in the present paper that the secret data can be easily revealed. Simulation results demonstrate that just 11 bits out of the 27-bit secret key are sufficient to reveal the data. To overcome the problem, an improvement is suggested in the data embedding pattern that demonstrates high data security. Bitwise analysis of the secret key used in the modified approach exhibits high sensitivity to change in the key.     

Multiplexing Optical Images for Steganography by Single Metasurfaces

Image steganography based on intelligent devices is one of the effective routes for safely and quickly transferring secret information. However, optical image steganography has attracted far less attention than digital one due to the state-of-the-art technology limitations of high-resolution optical imaging in integrated devices. Optical metasurfaces, composed of ultrathin subwavelength meta-atoms, are extensively considered for flat optical-imaging nano-components with high-resolutions as competitive candidates for next-generation miniaturized devices. Here, multiplex imaging metasurfaces composed of single nanorods are proposed under a detailed strategy to realize optical image steganography. The simulation and experimental results demonstrate that an optical steganographic metasurface can simultaneously transfer independent secret image information to two receivers with special keys, without raising suspicions for the general public under the cloak of a cover image. The proposed optical steganographic strategy by metasurfaces can arbitrarily distribute a continuous grayscale image together with a black-and-white image in separate channels, implying the distinguishing feature of high-density information capacity for integration and miniaturization in optical meta-devices.     

优美图随机嵌入路径耦合像素优化的图像隐写

目的为了解决当前图像隐写方案不可感知能力差、秘密信息嵌入路径随机性较低、难以抵御盲隐写攻击,以及隐写容量小等问题。方法提出优美图随机嵌入路径耦合像素优化控制的图像无损隐写术。基于HIWT机制将载体图像转换为频域整数系数,实现无损隐写。定义图像直方图修改规则,构造隐藏信息长度估算模型,确定图像分块的频域表示,增强该算法的可靠性。引入LSB替代,设计像素区间控制机制,缩小密文与载体之间的嵌入误差。再嵌入图论,构建优美图,获取随机矩阵,确定秘密信息自适应随机嵌入路径,增强隐写的不可感知性能。借助逆向HIWT获取隐写图像。结果与当前隐写方案相比,文中隐写术具备更强的不可感知性,有效降低了阶梯效应,且隐写容量更高,提取图像无失真。结论文中算法可对图像进行安全无损隐藏,有效保护图像可靠传输。     

Secret image transmission based on VQ and data embedding

A new secret image transmission scheme suitable for narrow communication channel is proposed in this article. A set of secret images can be simultaneously and efficiently delivered to the receiver via a small and meaningless data stream by the proposed scheme. To reduce the volume of secret images, a codebook is first generated and these secret images are encoded into binary indexes based on the vector quantization (VQ) technique. The compressed message is then embedded into the VQ codebook utilized in the encoding procedure by an adaptive least‐significant‐bits (LSB) modification technique. For the purpose of security, the slightly modified codebook is further encrypted into a meaningless data stream by the AES cryptosystem. Simulation results show that the proposed scheme provides an impressive improvement both in the visual quality of the extracted secret images at the receiver and in the hiding capacity of the cover medium. Experimental data also reveal the feasibility of the proposed secret image transmission scheme for limited‐bandwidth environment. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 1–9, 2007     

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.     

An Adaptive Image Calibration Algorithm for Steganalysis

In this paper, a new adaptive calibration algorithm for image steganalysis is proposed. Steganography disturbs the dependence between neighboring pixels and decreases the neighborhood node degree. Firstly, we analyzed the effect of steganography on the neighborhood node degree of cover images. Then, the calibratable pixels are marked by the analysis of neighborhood node degree. Finally, the strong correlation calibration image is constructed by revising the calibratable pixels. Experimental results reveal that compared with secondary steganography the image calibration method significantly increased the detection accuracy for LSB matching steganography on low embedding ratio. The proposed method also has a better performance against spatial steganography.     

A New Generative Mathematical Model for Coverless Steganography System Based on Image Generation

The ability of any steganography system to correctly retrieve the secret message is the primary criterion for measuring its efficiency. Recently, researchers have tried to generate a new natural image driven from only the secret message bits rather than using a cover to embed the secret message within it; this is called the stego image. This paper proposes a new secured coverless steganography system using a generative mathematical model based on semi Quick Response (QR) code and maze game image generation. This system consists of two components. The first component contains two processes, encryption process, and hiding process. The encryption process encrypts secret message bits in the form of a semi-QR code image whereas the hiding process conceals the pregenerated semi-QR code in the generated maze game image. On the other hand, the second component contains two processes, extraction and decryption, which are responsible for extracting the semi-QR code from the maze game image and then retrieving the original secret message from the extracted semi-QR code image, respectively. The results were obtained using the bit error rate (BER) metric. These results confirmed that the system achieved high hiding capacity, good performance, and a high level of robustness against attackers compared with other coverless steganography methods.     

Locating Steganalysis of LSB Matching Based on Spatial and Wavelet Filter Fusion

For the case of that only a single stego image of LSB (Least Significant Bit) matching steganography is available, the existing steganalysis algorithms cannot effectively locate the modified pixels. Therefore, an algorithm is proposed to locate the modified pixels of LSB matching based on spatial and wavelet filter fusion. Firstly, the validity of using the residuals obtained by spatial and wavelet filtering to locate the modified pixels of LSB matching is analyzed. It is pointed out that both of these two kinds of residuals can be used to identify the modified pixels of LSB matching with success rate higher than that of randomly guessing. Then, a method is proposed to measure the correlation between the results of two locating algorithms. Statistical results show that there are low correlations between the locating results of spatial filter based algorithm and wavelet filter based algorithm. Then these two kinds of residuals are fused by the voting method to improve the locating performance. The experimental results show that the proposed fusion algorithm can effectively improve the locating accuracy for the modified pixels of LSB matching.     

Real-time and MPEG-1 layer III compression resistant steganography in speech

Embedding a secret message into a cover media without attracting any attention, known as steganography, is one of the methods used for hidden communication purposes. One of the cover media that can be used for steganography is speech. In this study, the authors propose a new steganography method in speech signals. In this method, the silence intervals of speech are found and the length (number of samples) of these intervals is changed to hide information. The main feature of our method is robustness to MPEG-1 layer III (MP3) compression. This method can hide information in a speech stream with very low processing time which makes it a real-time steganography method. The hiding capacity of our method is comparable with other MP3 resistance methods and the listening tests show that the degradation in speech quality is not annoying. Additionally, the effect of our method on chaotic features is negligible, so it is difficult to detect our method with chaotic-based steganalysis methods.     

Enhancing security of DICOM images during storage and transmission in distributed environment

Digital watermarking is proposed as a method to enhance medical data security. Medical image watermarking requires extreme care when embedding additional information within medical images, because the additional information should not degrade medical image quality. Doctors diagnose medical images by seeing Region of Interest (ROI). A ROI of a medical image is an area including important information and must be stored without any distortion. If a medical image is illegally obtained or if its content is changed, it may lead to wrong diagnosis. In our scheme a well-known technique least significant bit substitution (LSB) is adapted to fulfill the requirements of data hiding and authentication in medical images. The scheme divide Digital Imaging and Communications in Medicine (DICOM) image into two parts ROI and non-ROI (non-region of interest). The DS (Digital Signature) which include patient data and SOP Instance UID are embedded randomly into the LSB border of the image. The DWT (Discrete Wavelet Transform) of ROI-MSB (most significant bit) embedded into the LSB middle of the image. The Result shows the ability to hide and retrieve DS in non-ROI, while ROI, the most important area for diagnosis, is retrieved exactly at the receiver side.     

LSB扩展的图像自嵌入方法

本文描述了一种基于LSB扩展的图像自嵌入方法.该方法在使用LSB数据隐藏的同时,对图像的高层位平面采用无损数据嵌入方法,将图像的压缩信息与认证信息嵌入到图像自身中.当原图像有缺损或被篡改时,使用认证信息可较准确地定位受损位置;使用从偏移图像子块中提取的数据,可近似地恢复原图像的受损部分;同时图像的高层位平面还可无损恢复.该方法增加了数据嵌入的容量,提高了恢复图像的质量.