A Novel CDMA Based High Performance Reversible Data Hiding Scheme

This paper presents a secure and large capacity reversible watermarking scheme based on modified integer-to-integer discrete wavelet transform (iDWT) and code division multiple access (CDMA) algorithms. In this scheme, the watermark data are spread by orthogonal spreading sequence and then embedded into wavelet domain, which can only be extracted with same spreading codes and be removed after extraction to recover the original image exactly. The iDWT is modified with the method of exchanging the positions of nearby pixels to generate positive wavelet coefficients, through which the length of the spreading sequence is cut down and the embedding capacity enhanced effectively. The influence of the length of different spreading sequences on watermark capacity is discussed and optimal length of orthogonal spreading sequence is obtained to achieve balance between the watermark capacity and image distortion. Performance comparison with some state-of-art reversible watermarking schemes shows that the proposed scheme achieves higher embedding capacity while maintaining image distortion at lower level.

In this paper, a reversible data hiding algorithm for audio files based on code division multiplexing (CDM) is proposed. In the scheme, the orthogonal spreading sequences are employed to carry the embedding data, and the host audio file can also be recovered completely after the secret message has been extracted accurately. At the same time, according the orthogonal character of the spreading sequences, the secret message can be embedded into the audio files repeatedly, and most elements of the spreading sequences are mutually canceled in the process of multi-level data embedding, which maintains the audio file in good auditory even at high data embedding capacity. Moreover, only the receiver who holds the same spreading sequences, as the sender can restore the embedded data, which enhance the security of the proposed scheme. As shown in the experimental results, the CDM based reversible data hiding (RDH) algorithm for audio files can achieve higher data embedding capacity at the same audio distortion compared with those state-of-the-art audio RDH algorithms.

This work presents a novel histogram-based reversible data hiding scheme. Although common histogram-based reversible data hiding schemes can achieve high image quality, embedding capacity is restricted because general images usually do not contain a great number of pixels with the same pixel values. To improve embedding capacity and retain low distortion, the proposed scheme uses prediction-error values, which are derived from the difference between an original image and a predictive image, instead of using the original pixels to convey a secret message. In the proposed scheme, a predictive image is generated using the mean interpolation prediction method. Since the obtained predictive image is very similar to the original image, prediction-error values are to be tended to zero. That is, a great quantity of peak points gathers around zero. The proposed scheme takes full advantage of this property to increase embedding capacity and retain slight distortion. Moreover, a threshold is used to balance the tradeoff between embedding capacity and image quality, i.e. embedding capacity in the proposed scheme is scalable. Furthermore, only a threshold is needed to record, not a large amount of information of peak and zero points, when high embedding capacity is required. Additionally, a multilevel mechanism is employed to further increase embedding capacity. Experimental results indicate that the proposed scheme is superior to other reversible schemes in terms of both image quality and embedding capacity.

The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR) with an adaptive least significant bit (ALSB) is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns) and higher texture (asymmetry patterns) areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS) steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images) are conducted with recent least significant bit (LSB)-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits) while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR)).

This paper proposes a new lossless data embedding algorithm on spatial domain of digital images. A single key parameter is required to embed and extract data in the algorithm instead of embedding any additional information such as the location map. A × window slides over the cover image by one pixel unit, and one bit can be embedded at each position of the window. So, the ideal embedding capacity equals to the number of pixels in an image. For further increase of embedding capacity, new weight parameters for the estimation of embedding target pixels have been used. As a result, significant increase in embedding capacity and better quality of the message-embedded image in high capacity embedding have been achieved. This algorithm is verified with simulations.

Image steganography is the art of hiding secret message in greyscale or cover images. Easy detection of secret message for any state-of-art image steganography can break the stego system. To prevent the breakdown of the stego system two tier data hiding is used. In this paper, we propose a high capacity image steganography with greyscale primary cover. Predictive primary cover PPC is computed from the primary cover using median edge detector MED predictor. Predictive error PE is the difference between primary cover and the PPC. The high level bit planes of the secret image payload are X-ORed with low level bit planes of the PPC and vice-verse. The resulting Stego image is embedded in a secondary cover image using bit plane X-OR algorithm. The cover image used is an RGB colour image. The proposed steganography scheme enhances the level of security of the existing bit plane X-OR algorithm without considerably increasing the computation time and detectability. The experimental results show that the proposed scheme achieves higher level of security with high embedding capacity. Higher level of security achieved by the proposed multilayer steganography scheme enhances the performance and security of the bit plane X-OR algorithm.

High embedding capacity and low image distortion factors are main concerns of information hiding researchers. No scheme can achieve these two factors simultaneously. The purpose of achieving either high embedding capacity or low image distortion varies from application to application. This paper presents a high embedding capacity information hiding method for grayscale images. The proposed method converts binary secret data into secret digits in the base-5 numeral system first. Next, one secret digit in the base-5 numeral system is embedded into one cover pixel. The experimental results show that the proposed method can be used to embed two secret bits into one cover pixel with the imperceptible image distortion. Comparing with some other works, we found that our method indeed outperforms all others in terms of embedding capacity.

A reversible data hiding scheme, which can restore the original image completely after data extraction, is presented in this paper. In the proposed method, a cover image is reordered into a sequence using space filling curves. For each pixel (except the first pixel) in the sequence, a pixel difference is generated between the pixel and its neighbor pixel. Due to the inherent structure of images causes a correlation of adjacent pixels, by utilizing the space filling curve scanning we can improve the embedding capacity while keeping the distortion low. Experimental results show that the proposed algorithm provides high embedding capacity while keeping the distortions low.

Reversible Data Hiding (RDH) should be secured as per requirements to protect content in open environments such as the cloud and internet. Integrity and undetectability of steganographic images are amongst the main concerns in any RDH scheme. As steganographic encryption using linear prediction over bit-planes is challenging, so the security and embedding capacity of the existing RDH techniques could not be adequate. Therefore, a new steganographic technique is proposed which provides better security, higher embedding capacity and visual quality to the RDH scheme. In this technique, the cover image is divided into n-bit planes (nBPs) and linear prediction is applied to it. Next, the histogram of the residual nBPs image is taken, and secret data bits are encrypted using the RC4 cryptographic algorithm. To embed the encrypted secret data bits, the histogram shifting process is applied. This is achieved by using peak and zero pairs of residual nBPs images. This scheme provides security to the cover image and hidden data. The proposed RDH scheme is capable of extracting the embedded secret data accurately and recovering the original cover or residual nBPs image.

A new exploiting modification direction embedding method (also called the EMD embedding for short) was proposed by Zhang et al. to show that their proposed method has high embedding capacity and high stego-image quality as well because at most one cover pixel need increase/decrease by one among n cover pixels. Adopting the advantages of the EMD embedding method, we develop a condensed technique based on consecutive ones transformation and token representation to squeeze out of more embedding spaces for secret data to be embedded in a cover image. This contributes data embedding capacity.

Steganography is the art of hiding covert message in unsuspected digital media and is generally used in secret communication between acknowledged parties. A good approach to steganography must provide good visual quality, high embedding capacity and security. In this paper, a new data hiding scheme based on octagon shaped shells is proposed to obtain better image quality and higher embedding capacity while security is achieved by scrambling the secret image using magic square. In the proposed method, a secret digit is embedded into each cover pixel pair with the help of a reference matrix consisting of connected octagons. Experimental results show that the proposed scheme ensures higher embedding capacity and security compared with existing schemes and also provides good visual quality but also better visual perception of the stego-image.

Enhanced pairwise IPVO-based reversible data hiding scheme using rhombus context

Inter-view local texture analysis based stereo image reversible data hiding

Adaptive embedding combining LBE and IBBE for high-capacity reversible data hiding in encrypted images

Steganography allows a user to hide the large amount of secret data within a image and audio files. It has become an interesting research area to enhance the security of network communications, copyright protection etc. The simplest methodology to hiding the data within an image is called LSB substitution method. LSB substitution method take the binary representation of hidden data and overwrite the LSB of each byte with in a cover image. In the proposed system the text data can be embedded into the LSB of cover image using Pixel Indicators in a Zigzag manner. The aim is to provide a better security with high embedding capacity and a better stego image quality than the existing systems. There are two different indicators are used, based on those indicators used in a Zigzag manner the hidden data is embedded into the LSB of the respective cover image. This type of embedding technique making it difficult for any attacker to extract the hidden data from the stego-image. Peak Signal-to-Noise Ratio is used to measure the quality of the stego image. The proposed method provides better PSNR value than the existing systems.