Chung-Ming Wang

A high quality steganographic method with pixel-value differencing and modulus function

In this paper, we shall propose a new image steganographic technique capable of producing a secret-embedded image that is totally indistinguishable from the original image by the human eye. In addition, our new method avoids the falling-off-boundary problem by using pixel-value differencing and the modulus function. First, we derive a difference value from two consecutive pixels by utilizing the pixel-value differencing technique (PVD). The hiding capacity of the two consecutive pixels depends on the difference value. In other words, the smoother area is, the less secret data can be hidden; on the contrary, the more edges an area has, the more secret data can be embedded. This way, the stego-image quality degradation is more imperceptible to the human eye. Second, the remainder of the two consecutive pixels can be computed by using the modulus operation, and then secret data can be embedded into the two pixels by modifying their remainder. In our scheme, there is an optimal approach to alter the remainder so as to greatly reduce the image distortion caused by the hiding of the secret data. The values of the two consecutive pixels are scarcely changed after the embedding of the secret message by the proposed optimal alteration algorithm. Experimental results have also demonstrated that the proposed scheme is secure against the RS detection attack.

Hiding data in spatial domain images with distortion tolerance

Data hiding is a technique that is used to embed secret information into a cover media. It has been widely used in protecting copyright and transmitting sensitive data over an insecure channel. Conventional data hiding schemes only focus on how to reduce the distortion when sensitive data is embedded into the cover image. However, the transmitted images may be compressed or occur transmitting errors. If such errors occur, the receiver cannot extract the correct information from the stego-image. In this paper, we proposed a novel hiding data scheme with distortion tolerance. The proposed scheme not only can prevent the quality of the processed image from being seriously degraded, but also can simultaneously achieve distortion tolerance. Experimental results show that the proposed scheme indeed can obtain a good image quality and is superior to the other schemes in terms of its distortion tolerance.

An Efficient Information Hiding Algorithm for Polygon Models

We present an efficient digital steganographic technique for three-dimensional (3D) triangle meshes. It is based on a substitutive blind procedure in the spatial domain. The basic idea is to consider every vertex of a triangle as a message vertex. We propose an efficient data structure and advanced jump strategy to fast assign order to the message vertex. We also provide a Multi-Level Embed Procedure (MLEP), including sliding, extending, and rotating levels, to embed information based on shifting the message vertex by its geometrical property. Experimental results show that the proposed technique is efficient and secure, has high capacity and low distortion, and is robust against affine transformations (which include translation, rotation, scaling, or their combined operations). The technique provides an automatic, reversible method and has proven to be feasible in steganography.

A high-capacity steganographic approach for 3D polygonal meshes

We present a high-capacity steganographic approach for three-dimensional (3D) polygonal meshes. We first use the representation information of a 3D model to embed messages. Our approach successfully combines both the spatial domain and the representation domain for steganography. In the spatial domain, every vertex of a 3D polygonal mesh can be represented by at least three bits using a modified multi-level embed procedure (MMLEP). In the representation domain, the representation order of vertices and polygons and even the topology information of polygons can be represented with an average of six bits per vertex using the proposed representation rearrangement procedure (RRP). Experimental results show that the proposed technique is efficient and secure, has high capacity and low distortion, and is robust against affine transformations. Our technique is a feasible alternative to other steganographic approaches.

A novel adaptive steganography based on local complexity and human vision sensitivity

This paper presents a novel adaptive steganographic scheme that is capable of both preventing visual degradation and providing a large embedding capacity. The embedding capacity of each pixel is dynamically determined by the local complexity of the cover image, allowing us to maintain good visual quality as well as embedding a large amount of secret messages. We classify pixels into three levels based on the variance of the local complexity of the cover image. When determining which level of local complexity a pixel should belong to, we take human vision sensitivity into consideration. This ensures that the visual artifacts appeared in the stego image are imperceptible, and the difference between the original and stego image is indistinguishable by the human visual system. The pixel classification assures that the embedding capacity offered by a cover image is bounded by the embedding capacity imposed on three levels that are distinguished by two boundary thresholds values. This allows us to derive a combination ratio of the maximal embedding capacity encountered with at each level. Consequently, our scheme is capable of determining two threshold values according to the desired demand of the embedding capacity requested by the user. Experimental results demonstrated that our adaptive steganographic algorithm produces insignificant visual distortion due to the hidden message. It provides high embedding capacity superior to that offered by a number of existing schemes. Our algorithm can resist the RS steganalysis attack, and it is statistically invisible for the attack of histogram comparison. The proposed scheme is simple, efficient and feasible for adaptive steganographic applications.

Reversible image steganographic scheme via predictive coding

The reversible image steganographic scheme in this study provides the ability to embed secret data into a host image and then recover the host image without losing any information when the secret data is extracted. In this paper, a reversible image steganographic scheme based on predictive coding is proposed by embedding secret data into compression codes during the lossless image compression. The proposed scheme effectively provides a lossless hiding mechanism in the compression domain. During the predictive coding stage, the proposed scheme embeds secret data into error values by referring to a hiding-tree. In an entropy decoding stage, the secret data can be extracted by referring to the hiding-tree, and the host image can be recovered during the predictive decoding stage. The experimental results show that the average hiding capacity of the proposed scheme is 0.992 bits per pixel (bpp), and the host image can be reconstructed without losing any information when the secret data is extracted.

An adaptive steganographic algorithm for 3D polygonal meshes

This paper presents a new adaptive digital steganographic technique for three-dimensional (3D) polygonal meshes. It is based on an adaptive substitutive blind procedure in the spatial domain. We use angle features to remove all restrictions of fixed embedding size in each vertex to provide larger embedding capacity and to minimize the distortion by minimum distortion distance estimation. This method exploits the correlation between neighboring polygons with respect to the human visual system to estimate the degree of smoothness or roughness properties. If the vertex is located on a rough surface, then it may tolerate larger position changes by embedding more messages than those on smooth surfaces. Our method provides an easy way to produce a more imperceptible result. In addition, a simple contagious diffusion technique is devoted to improving performance for polygonal meshes traversal. Experimental results show that the proposed technique is adaptive, simple, efficient, general, and secure. This technique has high capacity and low distortion, and it is robust against affine transformations. Our technique provides an adaptive method and has proven feasible in steganography.

An efficient key-management scheme for hierarchical access control based on elliptic curve cryptosystem

The elliptic curve cryptosystem is considered to be the strongest public-key cryptosystem known today and is preferred over the RSA cryptosystem because the key length for secure RSA has increased over recent years, and this has put a heavier processing load on its applications. An efficient key management and derivation scheme based on the elliptic curve cryptosystem is proposed in this paper to solve the hierarchical access control problem. Each class in the hierarchy is allowed to select its own secret key. The problem of efficiently adding or deleting classes can be solved without the necessity of regenerating keys for all the users in the hierarchy, as was the case in previous schemes. The scheme is shown much more efficiently and flexibly than the schemes proposed previously.

Data hiding approach for point-sampled geometry

We present a novel scheme for digital steganography of point-sampled geometry in the spatial domain. Our algorithm is inspired by the concepts proposed by Cayre and Macq for 3D polygonal models. It employs a principal component analysis (PCA), resulting in a blind approach. We validate our scheme with various model complexities in terms of capacity, complexity, visibility, and security. This scheme is robust against translation, rotation, and scaling operations. It is fast and can achieve high data capacity with insignificant visual distortion in the stego models.

Exploring pixel-value differencing and base decomposition for low distortion data embedding

This paper presents a low distortion data embedding method using pixel-value differencing and base decomposition schemes. The pixel-value differencing scheme offers the advantage of conveying a large amount of payload, while still maintaining the consistency of an image characteristic after data embedding. We introduce the base decomposition scheme, which defines a base pair for each degree in order to construct a two-base notational system. This scheme provides the advantage of significantly reducing pixel variation encountered due to secret data embedding. We analyze the pixel variation and the expected mean square error caused by concealing with secret messages. The mathematical analysis shows that our scheme produces much smaller maximal pixel variations and expected mean square error while producing a higher PSNR. We evaluate the performance of our method using 6 categories of metrics which allow us to compare with seven other state-of-the-art algorithms. Experimental statistics verify that our algorithm outperforms existing counterparts in terms of lower image distortion and higher image quality. Finally, our scheme can survive from the RS steganalysis attack and the steganalytic histogram attack of pixel-value difference. We conclude that our proposed method is capable of embedding large amounts of a message, yet still produces the embedded image with very low distortion. To the best of our knowledge, in comparison with the current seven state-of-the-art data embedding algorithms, our scheme produces the lowest image distortion while embedding the same or slightly larger quantities of messages.