Dual image based reversible data hiding method using neighbouring pixel value differencing

Abstract

Dual image based reversible data hidings are recently proposed where dual copies of a cover image are used to embed the secret data. In this paper, a novel reversible data hiding method based on neighbouring pixel value differencing is proposed to increase embedding capacity with a good image quality. The mean value of neighbouring pixels and the difference values are used to decide the size of embedding bits per the sub-block. The receiver can extract the secret data and recover the cover image from dual stegoimages. The experimental results show that the proposed method has a higher capacity and still a good image quality where it could embed 767,922 bits and maintain 45.58 and 45.33?dB for dual images.     

Reversible Data Hiding in Classification-Scrambling Encrypted-Image Based on Iterative Recovery

To improve the security and quality of decrypted images, this work proposes a reversible data hiding in encrypted image based on iterative recovery. The encrypted image is firstly generated by the pixel classification scrambling and bit-wise exclusive-OR (XOR), which improves the security of encrypted images. And then, a pixel-type-mark generation method based on block-compression is designed to reduce the extra burden of key management and transfer. At last, an iterative recovery strategy is proposed to optimize the marked decrypted image, which allows the original image to be obtained only using the encryption key. The proposed reversible data hiding scheme in encrypted image is not vulnerable to the ciphertext-only attack due to the fact that the XOR-encrypted pixels are scrambled in the corresponding encrypted image. Experimental results demonstrate that the decrypted images obtained by the proposed method are the same as the original ones, and the maximum embedding rate of proposed method is higher than the previously reported reversible data hiding methods in encrypted image.     

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 reversible data hiding method without rounding based on Haar wavelet transform: NON-R

The techniques that allow to obtain hidden data and recover the image has recently been much sought after. The basic objective of the method provided in this study was to analyse coefficients of digital images achieved by wavelet transform in the frequency space, to hide data, and to recover original image without loss. Wavelet transform is an efficient method to find pixel coefficient characteristic of digital images. The proposed method (NON-R) hides data using shifted histogram high-frequency Haar coefficients without rounding into integer. Thus, both hidden data and cover image can be easily recovered. Reversibility is provided by retrieving the cover image after hiding into high-frequency wavelet coefficients and extracting the message from wavelet coefficients. Experimental results show that the NON-R has a better performance than its counterparts in terms of statistical and perceptual outcomes.     

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.     

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.     

Secret data embedding scheme modifying the frequency of occurrence of image brightness values

The main purpose of this presented work is to develop a data embedding method based on a new digital image histogram modification approach. The proposed scheme fundamentally is concerned about the frequency of occurrence of the image brightness values of the cover image for the data embedding procedures. The proposed scheme effectively realizes both perceptual invisibility and statistical invisibility so that obtained covered images are highly robust against common perceptual and statistical steganalysis techniques. The scheme provides reasonably higher payload values than its counterparts, as well as providing comparatively improved PSNR results.     

A high-payload,reversible data hiding scheme based on histogram modification in JPEG bitstream

In this paper, we have presented a high-payload, reversible data hiding scheme that is focused on embedding secret data into joint photographic experts group (JPEG) bitstream by using histogram modification. In JPEG, for AC coefficients, 162 different variable length codes (VLCs) are defined and assigned by Huffman coding for all 162 run/size possibilities. After parsing VLC usage in the bitstream, we generated a histogram of run/size. According to a peak point and the nearest zero point of the histogram, the secret data were embedded by modifying the corresponding VLC values slightly. The experimental results and comparing the performance of our scheme with those of other existing schemes demonstrated that the proposed scheme preserved the quality of the image with no distortion and achieved the goal of high embedding capacity.     

Reversible Data Hiding in Encrypted Images Based on Prediction and Adaptive Classification Scrambling

Reversible data hiding in encrypted images (RDH-EI) technology is widely used in cloud storage for image privacy protection. In order to improve the embedding capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed a reversible data hiding algorithm for encrypted images based on prediction and adaptive classification scrambling. First, the prediction error image is obtained by a novel prediction method before encryption. Then, the image pixel values are divided into two categories by the threshold range, which is selected adaptively according to the image content. Multiple high-significant bits of pixels within the threshold range are used for embedding data and pixel values outside the threshold range remain unchanged. The optimal threshold selected adaptively ensures the maximum embedding capacity of the algorithm. Moreover, the security of encrypted images can be improved by the combination of XOR encryption and classification scrambling encryption since the embedded data is independent of the pixel position. Experiment results demonstrate that the proposed method has higher embedding capacity compared with the current state-ofthe-art methods for images with different texture complexity.     

Information hiding based on double-random phase encoding technology

This paper proposes a method for information hiding based on doubled-random phase encoding technology. In this method, data is split into real and imaginary compartments. The real part of the encoded data is embedded into a large enough host image, together with the imaginary part through grey level superposition. The composed image is not subject to severe degradation compared to the original host image. During the decryption process, the composed image is decrypted directly without the use of the original host image. Factors affecting the quality of the composed image as well as the reconstructed image are discussed. It is shown how optimum results are achieved by adjusting the superposition weight of the definitive host and hiding images.     

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.     

Watermarking patient data in encrypted medical images

In this paper, we propose a method for watermarking medical images for data integrity which consists of image encryption, data embedding and image-recovery phases. Data embedding can be completely recovered from the watermarked image after the watermark has been extracted. In the proposed method, we utilize standard stream cipher for image encryption and selecting non-region of interest tile to embed patient data. We show that the lower bound of the PSNR (peak-signal-to-noise-ratio) values for medical images is about 48 dB. Experimental results demonstrate that the proposed scheme can embed a large amount of data while keeping high visual quality of test images.     

A steganographic approach for secure communication of medical images based on the DCT-SVD and the compressed sensing (CS) theory

In this paper, a hybrid approach based on cryptography and steganography is proposed for the security of medical image over an open communication channel. In this approach, medical image information is embedded using discrete cosine transform (DCT)-singular value decomposition (SVD)-based embedding process. The medical image is encrypted using CS encryption before embedding into the standard image. This encrypted medical image is inserted into the singular values of DCT coefficients of the standard image to get the stego image. The experimental results show that the encrypted medical image is successfully extracted from the stego image under various image processing attacks at recovering side. The result analysis also shows improved imperceptibility of the stego image with a peak signal-to-noise ratio value above 60 dB for all types of medical images under consideration. Furthermore, the computation time of proposed approach is less than that of existing approaches.     

A novel LSB data hiding scheme with the lowest distortion

The proposed scheme groups three pixels as an embedding unit to conceal three bits of secret data in which the possible modification for each pixel is at most +1 or ?1. With our new scheme, the probability of altering one pixel by adding 1 or subtracting 1 is 6/8; it is 1/8 when altering two pixels, and 1/8 when preserving pixels without any modification. In conventional algorithms, the expected number of modification per pixel (ENMPP) mostly ranges from 0.375 to 0.5 on average when the embedding capacity of each pixel is one bit of secret message. In contrast, our new scheme groups three pixels together to convey three bits of secret message. The ENMPP is reduced at least by 0.333 on average. As a result, our algorithm offers higher visual quality for the stego image. The experimented results have verified that our scheme is super to the previous algorithms.     

Data hiding based on generalised exploiting modification direction method

Abstract

Two schemes using the exploiting modification direction (EMD) method to obtain good stego image quality and increase embedding capacity were respectfully introduced by Zhang and Wang and Lee et al. This study proposes a data-hiding scheme based on an improved EMD method. According to experimental results, the proposed scheme retains high embedding capacity and good stego image quality.     

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。     

Improved Lossless Data Hiding for JPEG Images Based on Histogram Modification

This paper proposes a lossless and high payload data hiding scheme for JPEG images by histogram modification. The most in JPEG bitstream consists of a sequence of VLCs (variable length codes) and the appended bits. Each VLC has a corresponding RLV (run/length value) to record the AC/DC coefficients. To achieve lossless data hiding with high payload, we shift the histogram of VLCs and modify the DHT segment to embed data. Since we sort the histogram of VLCs in descending order, the filesize expansion is limited. The paper’s key contribution includes: Lossless data hiding, less filesize expansion in identical pay-load and higher embedding efficiency.     

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.     

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.     

A high-capacity reversible data hiding method: HCRHide

Reversible data hiding methods have drawn considerable attention in the last decade, which allow full recovery of the original image used for embedding secret data as well as avert the third parties who should not realise the existence of hidden data. In this paper, we propose a high-capacity reversible data hiding method called HCRHide based on the Neighbour Mean Interpolation (NMI) method and the R-weighted Coding Method (RCM). Throughout a joint imperceptibility and data hiding capacity evaluation, results have approved high performance of the proposed method over the existing reversible data hiding methods.