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A novel data hiding method in halftone images with authentication ability was proposed in this paper. A secret image and an authentication image were simultaneously encoded into two halftone images. The secret image was visually reconstructed by stacking the two halftone images together. To verify the validity of the secret, one halftone image was shifted down for several units and stacked with the other one to reveal the authentication image. Experimental results were provided, demonstrating that the proposed method is effective and outperforms existing methods.

In this paper, we investigate how special is the choice of parameter values in the three-dimensional nonlinear system, proposed by Akgul and Pehlivan (2016), in producing a system, which exhibits chaos but has no real equilibrium states. Also, a data hiding method with a three-dimensional chaotic system without equilibrium point, developed by Akgul and Pehlivan, is realized. Numerous encryption studies have recently been made based on chaos. Encryption processes that are used with chaos bring about some security deficiencies in some cases. Steganography, unlike encryption studies, helps communicate the secret data by hiding it in an innocent-looking cover in order to avoid detection by third parties at first glance. In this work, a novel chaos-based data hiding method that hides an image with a different color into color images is proposed. Via the proposed method, data are hidden in bit spaces with the help of the chaotic random number generator (RNG). The generated random numbers are found with a chaotic system without equilibrium point, which is new in the literature. Shilnikov method cannot be applied to find whether the system is chaotic or not because they cannot have homoclinic or heteroclinic orbits. Thus, it can be useful in several engineering applications, especially in chaos-based cryptology and coding information. In the study, bits are hidden in pixels indicated by numbers generated by RNG. As the order of the hiding process is made randomly on a chaotic level, it has made data hiding algorithm stronger. The proposed method hides the data in cover image in such a way that it cannot be easily detected. Furthermore, the proposed method has been evaluated with steganalysis methods and image distortion measurement method PSNR. The chaos-based steganography method realized here has produced more best results in image distortion measurement method PSNR than other studies in the literature.

This paper proposes a method for hiding an important image in a cover image whose size is limited. In this method, in order to save space, a modified search-order coding (MSOC) technique first transforms the important image, then, a randomization procedure permutes the transformed image to further increase the security. Finally, a modulus function embeds the permuted code in a cover image; notably, in the modules function, the modulus base used for a pixel is determined according to the variance of its neighboring pixels. Experimental results show that the images are of high quality. Comparisons with reported methods are provided.

Image watermarking intends to hide secret data for the purposes of copyright protection, image authentication, data privacy, and broadcast monitoring. The ultimate goal is to achieve highest embedding capacity and lowest image distortion. In this paper, we present an intelligent watermarking scheme which can automatically analyze an image content to extract significant regions of interest (ROIs). A ROI is an area involving crucial information, and will be kept intact. The remaining regions of non-interest (RONIs) are collated for embedding watermarks, and will be ranked according to their entropy fuzzy memberships into a degree of importance. They are embedded by different amounts of bits to achieve optimal watermarking. The watermark is compressed and embedded in the frequency domain of the image. Experimental results show that the proposed technique has accomplished high capacity, high robustness, and high PSNR (peak signal-to-noise ratio) watermarking.

Steganography has become an important method for concealed communication especially through image files. Recent proposed steganographic methods employ multiple levels of complex techniques. Hence, there is an increasing significance for hardware implementation and its performance metrics. The objective of this article is to analyze and model the performance of FPGA hardware implementations of several spatial steganography methods, including: least significant bit (LSB), random LSB, mix-bit LSB and texture method. This paper presents innovative models to estimate energy-to-embed-secret-bit, peak signal-to-noise-ratio (PSNR) energy cost, power and resources in complex systems. Examining the performance results of the FPGA implementations shows that embedding misalignment degrades the performance, and random embedding increases resources by 43% and power by 13%. Furthermore, the mix-bit method has the best results in terms of balancing the energy consumption and PSNR. Moreover, the accuracy of the model to predict the energy to embed a single secret bit is 2%, and the accuracy of the model to predict complex system performance is 1% for hardware resources and 16.6% for power.

A Reversible Data Hiding technique by using histogram shifting and modulus operator is proposed in which secret data is embedded into blocks of the cover image. These blocks are modified by using modulus operator to increase the number of peak points in the histogram of the cover image which further increases its embedding capacity. Secret data is embedded in the original cover blocks of the cover image by using peak points of the predicted blocks, which are generated by using modulus operator. Peak Signal to Noise Ratio and PSNR-Human Visual System are used to show the human visual acceptance of the proposed technique. Experimental results show that the embedding capacity is high as compared to the capacity of existing RDH techniques, while distortion in marked images is also less as compared to distortion produced by these existing techniques.

Wide utilization of audio files has attracted the attention of cyber-criminals to employ this media as a cover for their concealed communications. As a countermeasure and to protect cyberspace, several techniques have been introduced for steganalysis of various audio formats, such as MP3, VoIP, etc. The combination of machine learning and signal processing techniques has helped steganalyzers to obtain higher accuracies. However, as the statistical characteristics of a normal audio file differ from the speech ones, the current methods cannot discriminate clean and stego speech instances efficiently. Another problem is the high numbers of extracted features and analysis dimensions that drastically increase the implementation cost. To tackle these, this paper proposes the Percent of Equal Adjacent Samples (PEAS) feature for single-dimension least-significant-bit replacement (LSBR) speech steganalysis. The model first classifies the samples into speech and silence groups according to a threshold which has been determined through extensive experiments. It then uses an MLP classifier to detect stego instances and determine the embedding ratio. PEAS steganalysis detects 99.8% of stego instances in the lowest analyzed embedding ratio — 12.5% — and its sensitivity increases to 100% for the ratios of 37.5% and above.

The increasing need for image communication and storage has created a great necessity for securely transforming and storing images over a network. Whereas traditional image encryption algorithms usually consider the security of the whole plain image, region of interest (ROI) encryption schemes, which are of great importance in practical applications, protect the privacy regions of plain images. Existing ROI encryption schemes usually adopt approximate techniques to detect the privacy region and measure the quality of encrypted images; however, their performance is usually inconsistent with a human visual system (HVS) and is sensitive to statistical attacks. In this paper, we propose a novel privacy-aware ROI image encryption (PRIE) scheme based on logistical mapping and data hiding. The proposed scheme utilizes salient object detection to automatically, adaptively and accurately detect the privacy region of a given plain image. After private pixels have been encrypted using chaotic cryptography, the significant bits are embedded into the nonprivacy region of the plain image using data hiding. Extensive experiments are conducted to illustrate the consistency between our automatic ROI detection and HVS. Our experimental results also demonstrate that the proposed scheme exhibits satisfactory security performance.

The interest for multimedia contents authentication has recently increased. In particular watermarking-based authentication schemes seem to be offering some advantages with respect to classical cryptography tools (e.g. real content authentication, localization of manipulations, storage format independence, transparency to common signal processing, etc.). In this paper a simple and secure self recovery authentication algorithm which hides an image digest into some DWT subbands of the to be authenticated image is presented. This technique has been designed for video surveillance and/or remote sensing applications. The main goal of this approach is to detect possible malevolent object manipulations undergone by the image (object replacing and/or deletion) by means of a self recovery processing. This valuable characteristic has to be maintained also when an image is processed through an usual and friendly transformation like JPEG compression. Particular care is given to make the scheme robust against innocuous manipulations, and secure against forgery attempts. Experimental results are presented that demonstrate the good performance of the proposed system.

In this paper, we investigate the general problem of data hiding and propose an approach for effective cover noise interference rejection in oblivious applications. We first evaluate the performance in the commonly used direct sequence modulation approach where a low-power signal is embedded into the original cover signal. The optimal detection is derived and its performance is analyzed. Second, we study a novel approach in oblivious data hiding and evaluate its performance and compare it with existing algorithms. Both simulation studies and empirical data hiding results validate its efficiency in the multimedia oblivious applications.

Transmission of block-coded images through error-prone radio mobile channel often results in lost blocks. Error concealment (EC) techniques exploit inherent redundancy and reduce visual artifacts through post-processing at the decoder side. In this paper, we propose an efficient quantization index modulation (QIM)-based data hiding scheme using dual-tree complex wavelet transform (DTCWT) for the application of image error concealment. The goal is achieved by embedding important information (image digest) as watermark signal that is extracted from the original image itself and is used to introduce sufficient redundancy in the transmitted image. At the decoder side, the extracted image digest is used to correct the damaged regions. DTCWT offers three-fold advantages viz. (1) high embedding capacity due to inherent redundancy that leads to the better reconstruction of high volume missing data, (2) better imperceptibly after data embedding since it most closely captures human visual system (HVS) characteristics than conventional DWT and (3) better watermark decoding reliability. Simulation results duly support the claims and relative performance improvement with respect to the existing results.

Method for data hiding based on LeGall 5/3 of Cohen-Daubechies-Feauveau: CDF 5/3 wavelet with data compression and random scanning of secret imagery data together with steganography is proposed. Invisibility of secret imagery data is evaluated based on Peak Signal to Noise Ratio: PSNR with SIDBA standard image database. The experimental results show that PSNR of LeGall based wavelet utilized data hiding ranges from 43.82 to 46.9 while that of Daubechies based method ranges from 44.33 to 44.75 when the coded secret imagery data is inserted in the first 3 digits from Least Significant Bit: LSB of the original image. Data compression ratio for the secret imagery data ranges from 1.3 to 19.4 which depends on the complexity of the secret imagery data. Meanwhile, PSNR of data hidden image ranges from 46.83 to 47.41. Consequently, the proposed data hiding method is permissive because PSNR is over 40 dB results in satisfaction on invisibility of the secret imagery data in the data hidden image.

Digital watermarking consists in embedding imperceptible information into a host signal. It has been proposed to solve problems as varied as the protection of the copyright, content authentication, fingerprinting and broadcast monitoring. This paper presents a new approach for audio watermarking using the QR factorization in wavelet domain. This approach is based on embedding a watermark binary image in the R matrices of low frequency blocks DWT coefficients of audio signal. In this algorithm, the watermark is embedded by applying a Quantization Index Modulation (QIM) process on the determined optimal sample for each matrix R. The watermark can be blindly extracted without the knowledge of the original audio signal. Experimental results show that the proposed audio watermarking scheme maintains high quality of the audio signal. Signal to Noise Ratio (SNR), Log Spectral Distortion (LSD) and Mean Opinion Score (MOS) are about 40 dB, 0.37 dB and 4.84, respectively. Moreover, the scheme is quite robust against common signal processing attacks such as noise addition, filtering and MP3 compression. In addition, this method ensures a secure extraction process by using a private key, making it suitable for secure applications such as copyright protection.

In the process of data embedding and extraction,there are a little articles that change the host media too much.In this paper,we present a method for still image steganography in which we change the host image into Gaussian white noise for increase the quantity of embedden information.In the process of extraction,we use the method of denoise, regard the host image as noise,take advantage of the character of Gassian white noise to delete the host image for getting the hidden image.Method of denoise used for extraction is a new view in steganography.

We present a scalable encoding strategy for the 3D facial data in various bandwidth scenarios. The scalability, needed to cater diverse clients, is achieved through the multiresolution characteristic of JPEG2000. The disparate 3D facial data is synchronously unified by the application of data hiding wherein the 2.5D facial model is embedded in the corresponding 2D texture in the discrete wavelet transform (DWT) domain. The unified file conforms to the JPEG2000 standard and thus no novel format is introduced. The method is effective and has the potential to be applied in videosurveillance and videoconference applications.

Many covert channels take advantages of weaknesses, flaws, or unused data fields in network protocols. In this paper, a behavior-based covert channel, that takes advantages of behavior of an application, is presented along with a formal definition in the framework of finite state machines. The behavior-based covert channel is application specific and lies at the application layer of the network OSI model, which makes the detection of this type of covert channel much more difficult. A detailed sample implementation demonstrates an example of this type of covert channel in the form of a simple online two-person game.The potential of this type of covert channel is also discussed.