Cheng-Ta Huang

Reversible steganography based on side match and hit pattern for VQ-compressed images

Data hiding is a technique which embeds secret data into cover media. It is important to the multimedia security and has been widely studied. Recently, some researchers paid attention to reversible data hiding methods. These methods can reconstruct the original image from the stego-image when embedded data are extracted. In this paper, we propose a new reversible steganographic method for vector quantization (VQ) compressed images. The new method uses the hit pattern to achieve reversibility, and the hit pattern strategy successfully reduces the overhead. The codebook is partitioned by the extension method which makes the stego-image have good visual features. Also, a look-up table is used to speed up the partitioning operation. Compared to Chang et al.’s method, the experimental results show that the proposed method has higher capacity, better visual quality, and lower running time.

VQ Applications in Steganographic Data Hiding Upon Multimedia Images

Data hiding is one of the most important techniques to achieve better data and communication protection by hiding information into a media carrier. It provides a secure method to distribute data through a public and open channel. Data hiding for vector quantization (VQ)-based images focuses on the problem of embedding secret data into a cover VQ-based image to achieve secret communication and data protection. This paper provides a state-of-the-art review and comparison of the different existing data-hiding methods for VQ-based images. In this paper, we classify VQ-based data-hiding methods into four nonoverlapping groups according to their reversibility and output formats, introduce the details of the representative methods, summarize the features of the representative methods, and compare the performance of the representative methods using peak signal-to-noise ratio, capacity of secret data, and bit rate. Our paper shows that an irreversible method is very likely a VQ-based data-hiding method that produces a stego-image as its output, and it can embed more secret data than a reversible method. Nonstandard encoding methods (e.g., joint neighboring coding) are becoming popular in reversible data hiding since they can increase the capacity for embedding the secret data. Some methods with high compression rate, such as the search order coding-based methods, may reduce the compression rate in return for the capacity for the secret data.

Data embedding for vector quantization image processing on the basis of adjoining state-codebook mapping

Information hiding for images is an important research issue in digital multimedia. It provides a way to certify copyrights of image files, as well as a means of secret communication for people. In this paper, we propose a reversible image information hiding scheme based on vector quantization (VQ). The proposed scheme uses a new technique called Adjoining State-Codebook Mapping (ASCM) to map the content of an image block to an index in the corresponding state-codebooks. The ASCM technique uses two adjacent image blocks of an encoding image block to create two state-codebooks, which can represent the encoding image block more accurately. Therefore, it can reduce the size of the output code-stream and yet still provide large embedding capacity for secret data. Experimental results indicate that the proposed scheme has better compression bit rate and larger embedding capacity when we compare the proposed scheme with recent similar studies, proposed by Chang et al. in 2009 and Yang et al. in 2011 respectively.

iPhone social networking for evidence investigations using iTunes forensics

The smart phone, like a small computer, providing not only the functions of normal phones and wireless Internet access, but also all kinds of application tools, serves as a platform of the sources of real-time information, information sharing and information exchange in our daily lives. As a result, the extract the crucial digital evidence in the smart phone, it has now become a challenge in the technology time. In particular, it is for when the smart phone applications are committed as the illegal contacts. In this paper, we discuss the most five popular mobile social networking applications in iPhone usages. The backup files of social networking applications could offer us the crucial evidence in this paper study. The relative information of social networking applications operated in iPhone is able to be accessed if necessary, even though iPhone has been destructed or encrypted by the suspect. It could help the investigators to exactly reconstruct the crime venue and find the truth.

Steganography of Data Embedding in Multimedia Images Using Interpolation and Histogram Shifting

In this paper, we propose a data hiding scheme with high capacity in steganography. First of all, we improve the data hiding technique based one neighbor mean interpolation for increasing the image quality of a stego-image without losing any capacity. A stego-image is derived from a cover image which has embedded the secret data. A cover image is generated from an original image by using interpolating method. Secondly, we apply histogram shifting technique to embed more secret data. The difference tables between the cover image and the stego-image except pivot pixels are calculated to make a histogram at first. Then, we modify the histogram data in an embedding procedure, and construct a new stego-image with two levels data hiding method. Our scheme can not only provide better image quality of the stego-image, but also have a very high capacity compared with other data hiding schemes based on interpolation.

SAMEVED: A System Architecture for Managing and Establishing Virtual Elastic Datacenters

Cloud computing is an emerging computing paradigm that provides all kinds of services through the Internet. Existing elastic computing approaches are popular in cloud computing. They can fulfill the requirements of some cloud applications, but usually fail to provide an isolated computing environment consisting of connected virtual machines over a user-defined network topology. This paper presents a system architecture, namely SAMEVED, which exposes a cloud service that can allocate and manage a private, virtual elastic datacenter by integrating VPN and virtual routers into existing virtualization technologies. Authentication is required by user login while using SAMEVED. A user-friendly web interface and remote invocation interface are provided to support different operations for different users with different privileges.

VQ-based algorithms extended to non-embedded watermarking for multimedia ownership prevention systems

This paper presents some novel watermarking approaches that are based on vector quantization and provide ownership protection in gray-level images. Nowadays, information sharing in P2P architecture is immensely involved with knowledge-learning on the Internet. Copyright protection is therefore considered in the studies of P2P systems. The proposed approaches combine images, watermarks, and codebooks together by generating key streams to claim ownership and guarantee the integrity of images. Non-embedded approaches that generate claimed key streams have the benefit of maintaining the authorized image in its original state without any modifications. Compared to Lin et al.’s method, our approaches save both running time and space for storage. Moreover, in order to provide broader applications of image protection, robust watermark and fragile watermark strategies are proposed. The experimental results show that these strategies are effective.

Reversible data hiding using neighboring block in VQ-compressed images

Data hiding is a technique which embeds secret data into cover media. It is important to multimedia security and has been widely studied. Recently, some researchers paid attention to reversible data hiding methods. The proposed schemes are able to reconstruct the original image from the embedded index when embedded data are extracted. In this paper, we propose a new reversible method in vector quantization (VQ) compressed images. Our scheme takes advantages of the relationship of neighboring blocks to achieve reversibility. Compared to past studies, for example, Wang et al.s method, the experimental results show that the proposed method outperforms the past one in terms of higher compression rate and larger c [apacity.

Image Steganography Using Gradient Adjacent Prediction in Side-Match Vector Quantization

This study presents a new steganographic method that embeds secret data into a cover digital image using VQ encoding. The core concept of the proposed method uses the gradient adjacent prediction (GAP) algorithm, which enhances prediction accuracy of neighboring blocks in SMVQ encoding. To embed secret data into the cover image, the proposed method utilizes the features of GAP to decide the capacity of the secret data per pixel in a block. It then embeds the secret data accordingly. It also embeds an index value in each block to ensure that the secret data can be recovered back. The index value points to the closest codeword of a state codebook to the encoding block, where the state codebook is generated by GAP-based SMVQ. The result shows that the proposed method has better performance than a recent similar work proposed by Chen and Lin in 2010.

A Secret Embedding Scheme by Means of Re-indexing VQ Codebook upon Image Processing

A VQ-based, reversible information hiding method embeds secret data into a VQ-encoded image to achieve data protection. It produces either a VQ-encoded image or a compressed codestream as the output. The embedded secret data and the original VQ-encoded image can be extracted from the encoded output when needed. This paper proposes a novel information hiding method for VQ-encoded images. The proposed method allows the users to decide the embedding capacity of secret data in an image. The proposed method utilizes the fact that two neighboring blocks in a VQ-encoded image are usually similar. First, it re-orders the codebook according to the similarity to the codeword of the first block in an image. Second, it sequentially picks up two consequent blocks, calculates the difference of their new indices that are mapped from the re-ordered codebook, and encodes the secret bits along with the difference value as the compressed output for each block. We conducted several experiments, and used the results to compare the performance of the proposed method with the performance of a recent similar method. The experimental results showed that the proposed method is very efficient in terms of bit rate, in particular when an image has many similar neighboring blocks in it.