Showing papers on "Steganography published in 2014"

Universal distortion function for steganography in an arbitrary domain

Abstract: Currently, the most successful approach to steganography in empirical objects, such as digital media, is to embed the payload while minimizing a suitably defined distortion function. The design of the distortion is essentially the only task left to the steganographer since efficient practical codes exist that embed near the payload-distortion bound. The practitioner’s goal is to design the distortion to obtain a scheme with a high empirical statistical detectability. In this paper, we propose a universal distortion design called universal wavelet relative distortion (UNIWARD) that can be applied for embedding in an arbitrary domain. The embedding distortion is computed as a sum of relative changes of coefficients in a directional filter bank decomposition of the cover image. The directionality forces the embedding changes to such parts of the cover object that are difficult to model in multiple directions, such as textures or noisy regions, while avoiding smooth regions or clean edges. We demonstrate experimentally using rich models as well as targeted attacks that steganographic methods built using UNIWARD match or outperform the current state of the art in the spatial domain, JPEG domain, and side-informed JPEG domain.

A new cost function for spatial image steganography

Abstract: A well defined cost function is crucial to steganography under the scenario of minimizing embedding distortion. In this paper, we present a new cost function for spatial image steganography. The proposed cost function is designed by using a high-pass filter to locate the less predictable parts in an image, and then using two low-pass filters to make the low cost values more clustered. Experiments show that the steganographic method with the proposed cost function makes the embedding changes more concentrated in texture regions, and thus achieves a better performance on resisting the state-of-the-art steganalysis over prior works, including HUGO, WOW, and S-UNIWARD.

Selection-channel-aware rich model for Steganalysis of digital images

Abstract: From the perspective of signal detection theory, it seems obvious that knowing the probabilities with which the individual cover elements are modified during message embedding (the so-called probabilistic slection channel) should improve steganalysis. It is, however, not clear how to incorporate this information into steganalysis features when the detector is built as a classifier. In this paper, we propose a variant of the popular spatial rich model (SRM) that makes use of the selection channel. We demonstrate on three state-of-the-art content-adaptive steganographic schemes that even an imprecise knowledge of the embedding probabilities can substantially increase the detection accuracy in comparison with feature sets that do not consider the selection channel. Overly adaptive embedding schemes seem to be more vulnerable than schemes that spread the embedding changes more evenly throughout the cover.

Steganalysis of least significant bit matching using multi-order differences

Abstract: This paper presents a learning-based steganalysis/detection method to attack spatial domain least significant bit LSB matching steganography in grayscale images, which is the antetype of many sophisticated steganographic methods. We model the message embedded by LSB matching as the independent noise to the image, and theoretically prove that LSB matching smoothes the histogram of multi-order differences. Because of the dependency among neighboring pixels, histogram of low order differences can be approximated by Laplace distribution. The smoothness caused by LSB matching is especially apparent at the peak of the histogram. Consequently, the low order differences of image pixels are calculated. The co-occurrence matrix is utilized to model the differences with the small absolute value in order to extract features. Finally, support vector machine classifiers are trained with the features so as to identify a test image either an original or a stego image. The proposed method is evaluated by LSB matching and its improved version "Hugo". In addition, the proposed method is compared with state-of-the-art steganalytic methods. The experimental results demonstrate the reliability of the new detector. Copyright © 2013 John Wiley & Sons, Ltd.

Uniform Embedding for Efficient JPEG Steganography

Abstract: Steganography is the science and art of covert communication, which aims to hide the secret messages into a cover medium while achieving the least possible statistical detectability. To this end, the framework of minimal distortion embedding is widely adopted in the development of the steganographic system, in which a well designed distortion function is of vital importance. In this paper, a class of new distortion functions known as uniform embedding distortion function (UED) is presented for both side-informed and non side-informed secure JPEG steganography. By incorporating the syndrome trellis coding, the best codeword with minimal distortion for a given message is determined with UED, which, instead of random modification, tries to spread the embedding modification uniformly to quantized discrete cosine transform (DCT) coefficients of all possible magnitudes. In this way, less statistical detectability is achieved, owing to the reduction of the average changes of the first- and second-order statistics for DCT coefficients as a whole. The effectiveness of the proposed scheme is verified with evidence obtained from exhaustive experiments using popular steganalyzers with various feature sets on the BOSSbase database. Compared with prior arts, the proposed scheme gains favorable performance in terms of secure embedding capacity against steganalysis.

Trends in steganography

Abstract: Methods for embedding secret data are more sophisticated than their ancient predecessors, but the basic principles remain unchanged.

A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm

Abstract: Steganography is knowledge and art of hiding secret data into information which is largely used in information security systems. Various methods have been proposed in the literature which most of them are not capable of both preventing visual degradation and providing a large embedding capacity. In this paper, we propose a tunable visual image quality and data lossless method in spatial domain based on a genetic algorithm (GA). The main idea of the proposed technique is modeling the steganography problem as a search and optimization problem. Experimental results, in comparison with other currently popular steganography techniques, demonstrate that the proposed algorithm not only achieves high embedding capacity but also enhances the PSNR of the stego image.

Investigation on Cost Assignment in Spatial Image Steganography

Abstract: Relating the embedding cost in a distortion function to statistical detectability is an open vital problem in modern steganography. In this paper, we take one step forward by formulating the process of cost assignment into two phases: 1) determining a priority profile and 2) specifying a cost-value distribution. We analytically show that the cost-value distribution determines the change rate of cover elements. Furthermore, when the cost-values are specified to follow a uniform distribution, the change rate has a linear relation with the payload, which is a rare property for content-adaptive steganography. In addition, we propose some rules for ranking the priority profile for spatial images. Following such rules, we propose a five-step cost assignment scheme. Previous steganographic schemes, such as HUGO, WOW, S-UNIWARD, and MG, can be integrated into our scheme. Experimental results demonstrate that the proposed scheme is capable of better resisting steganalysis equipped with high-dimensional rich model features.

Image steganography techniques: an overview

Abstract: Steganography - the art and science of hiding information has received much attention in the recent years. It can also be defined as the study of invisible communication that usually involves communication of secret data in an appropriate carrier, e.g., image, audio, video or TCP/IP header file. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the Internet. The main goal of steganography is to ensure that the transmitted message is completely masked, thereby ensuring that the message is accessible only to the intended receiver and does not attract attention from eavesdroppers and attackers. This paper is an attempt to study the various techniques use in steganography and provide a general overview of different algorithms of image steganography. There exists a large variety of steganography techniques

Adaptive steganalysis against WOW embedding algorithm

Abstract: WOW (Wavelet Obtained Weights) [5] is one of the advanced steganographic methods in spatial domain, which can adaptively embed secret message into cover image according to textural complexity. Usually, the more complex of an image region, the more pixel values within it would be modified. In such a way, it can achieve good visual quality of the resulting stegos and high security against typical steganalytic detectors. Based on our analysis, however, we point out one of the limitations in the WOW embedding algorithm, namely, it is easy to narrow down those possible modified regions for a given stego image based on the embedding costs used in WOW. If we just extract features from such regions and perform analysis on them, it is expected that the detection performance would be improved compared with that of extracting steganalytic features from the whole image. In this paper, we first proposed an adaptive steganalytic scheme for the WOW method, and use the spatial rich model (SRM) based features [4] to model those possible modified regions in our experiments. The experimental results evaluated on 10,000 images have shown the effectiveness of our scheme. It is also noted that our steganalytic strategy can be combined with other steganalytic features to detect the WOW and/or other adaptive steganographic methods both in the spatial and JPEG domains.

Using transcoding for hidden communication in IP telephony

Abstract: The paper presents a new steganographic method for IP telephony called TranSteg (Transcoding Steganography). Typically, in steganographic communication it is advised for covert data to be compressed in order to limit its size. In TranSteg it is the overt data that is compressed to make space for the steganogram. The main innovation of TranSteg is to, for a chosen voice stream, find a codec that will result in a similar voice quality but smaller voice payload size than the originally selected. Then, the voice stream is transcoded. At this step the original voice payload size is intentionally unaltered and the change of the codec is not indicated. Instead, after placing the transcoded voice payload, the remaining free space is filled with hidden data. TranSteg proof of concept implementation was designed and developed. The obtained experimental results are enclosed in this paper. They prove that the proposed method is feasible and offers a high steganographic bandwidth while introducing small voice degradation. Moreover, TranSteg detection is difficult to perform when compared with existing VoIP steganography methods.

A Novel Turtle Shell Based Scheme for Data Hiding

Abstract: Data hiding is a well-known technique which embeds the secret data into a digital media. Most of the existing schemes either have the low image quality, or provide the restricted embedding capacity. In this paper, a new data hiding scheme based on turtle shell is proposed to obtain better image quality and higher embedding capacity. In the proposed scheme, a secret digit is embedded into each cover pixel pair with the guidance of the turtle shell. Experimental results reveal that the proposed scheme ensures not only higher embedding capacity, but also obtains better visual quality compared with the existing schemes.

Edge-based image steganography

Abstract: This paper proposes a novel steganography technique, where edges in the cover image have been used to embed messages. Amount of data to be embedded plays an important role on the selection of edges, i.e., the more the amount of data to be embedded, larger the use of weaker edges for embedding. Experimental results have shown that the proposed technique performs better or at least at par with the state-of-the-art steganography techniques but provides higher embedding capacity.

A technique for digital steganography using chaotic maps

Abstract: Chaos has been applied extensively in secure communication over the last decade, but most of the chaotic security protocols defined, are cryptographically weak or slow to compute. Also, study of chaotic phenomena as application in security area is not discussed in detail. In this paper, we have intensely studied chaos, their influence in secure communications and proposed a steganography technique in spatial domain for digital images based upon chaotic maps. By applying chaos effectively in secure communication, the strength of the overall anticipated algorithm has been increased to a significant level. In addition, few security statistical analyses such as correlation, entropy, energy, contrast, homogeneity, peak signal to noise ratio, and mean square error have also been carried out and shown that it can survive against various differential attacks such as the known message attack, known cover attack, known stego attack, and stego only attack.

A universal image forensic strategy based on steganalytic model

Abstract: Image forensics have made great progress during the past decade. However, almost all existing forensic methods can be regarded as the specific way, since they mainly focus on detecting one type of image processing operations. When the type of operations changes, the performances of the forensic methods usually degrade significantly. In this paper, we propose a universal forensics strategy based on steganalytic model. By analyzing the similarity between steganography and image processing operation, we find that almost all image operations have to modify many image pixels without considering some inherent properties within the original image, which is similar to what in steganography. Therefore, it is reasonable to model various image processing operations as steganography and it is promising to detect them with the help of some effective universal steganalytic features. In our experiments, we evaluate several advanced steganalytic features on six kinds of typical image processing operations. The experimental results show that all evaluated steganalyzers perform well while some steganalytic methods such as the spatial rich model (SRM) [4] and LBP [19] based methods even outperform the specific forensic methods significantly. What is more, they can further identify the type of various image processing operations, which is impossible to achieve using the existing forensic methods.

An efficient filtering based approach improving LSB image steganography using status bit along with AES cryptography

Abstract: In Steganography, the total message will be invisible into a cover media such as text, audio, video, and image in which attackers don't have any idea about the original message that the media contain and which algorithm use to embed or extract it. In this paper, the proposed technique has focused on Bitmap image as it is uncompressed and convenient than any other image format to implement LSB Steganography method. For better security AES cryptography technique has also been used in the proposed method. Before applying the Steganography technique, AES cryptography will change the secret message into cipher text to ensure two layer security of the message. In the proposed technique, a new Steganography technique is being developed to hide large data in Bitmap image using filtering based algorithm, which uses MSB bits for filtering purpose. This method uses the concept of status checking for insertion and retrieval of message. This method is an improvement of Least Significant Bit (LSB) method for hiding information in images. It is being predicted that the proposed method will able to hide large data in a single image retaining the advantages and discarding the disadvantages of the traditional LSB method. Various sizes of data are stored inside the images and the PSNR are also calculated for each of the images tested. Based on the PSNR value, the Stego image has higher PSNR value as compared to other method. Hence the proposed Steganography technique is very efficient to hide the secret information inside an image.

Video Steganalysis Against Motion Vector-Based Steganography by Adding or Subtracting One Motion Vector Value

Abstract: This paper presents a method for detection of motion vector-based video steganography. First, the modification on the least significant bit of the motion vector is modeled. The influence of the embedding operation on the sum of absolute difference (SAD) is illustrated, which allows us to focus on the difference between the actual SAD and the locally optimal SAD after the adding-or-subtracting-one operation on the motion value. Finally, based on the fact that most motion vectors are locally optimal for most video codecs, two feature sets are extracted and used for classification. Experiments are carried out on videos corrupted by various steganography methods and encoded by various motion estimation methods, in various bit rates, and in various video codecs. Performance results demonstrate that our scheme outperforms previous works in general, and is more favorable for real-world applications.

Hash Based Least Significant Bit Technique For Video Steganography

Abstract: The Hash Based Least Significant Bit Technique For Video Steganography deals with hiding secret message or information within a video.Steganography is nothing but the covered writing it includes process that conceals information within other data and also conceals the fact that a secret message is being sent.Steganography is the art of secret communication or the science of invisible communication. In this paper a Hash based least significant bit technique for video steganography has been proposed whose main goal is to embed a secret information in a particular video file and then extract it using a stego key or password. In this Least Significant Bit insertion method is used for steganography so as to embed data in cover video with change in the lower bit.This LSB insertion is not visible.Data hidding is the process of embedding information in a video without changing its perceptual quality. The proposed method involve with two terms that are Peak Signal to Noise Ratio (PSNR) and the Mean Square Error (MSE) .This two terms measured between the original video files and steganographic video files from all video frames where a distortion is measured using PSNR. A hash function is used to select the particular position for insertion of bits of secret message in LSB bits.

Discrete Wavelet Transform and Singular Value Decomposition Based ECG Steganography for Secured Patient Information Transmission

Abstract: ECG Steganography provides secured transmission of secret information such as patient personal information through ECG signals. This paper proposes an approach that uses discrete wavelet transform to decompose signals and singular value decomposition (SVD) to embed the secret information into the decomposed ECG signal. The novelty of the proposed method is to embed the watermark using SVD into the two dimensional (2D) ECG image. The embedding of secret information in a selected sub band of the decomposed ECG is achieved by replacing the singular values of the decomposed cover image by the singular values of the secret data. The performance assessment of the proposed approach allows understanding the suitable sub-band to hide secret data and the signal degradation that will affect diagnosability. Performance is measured using metrics like Kullback---Leibler divergence (KL), percentage residual difference (PRD), peak signal to noise ratio (PSNR) and bit error rate (BER). A dynamic location selection approach for embedding the singular values is also discussed. The proposed approach is demonstrated on a MIT-BIH database and the observations validate that HH is the ideal sub-band to hide data. It is also observed that the signal degradation (less than 0.6 %) is very less in the proposed approach even with the secret data being as large as the sub band size. So, it does not affect the diagnosability and is reliable to transmit patient information.

Online payment system using steganography and visual cryptography

Abstract: A rapid growth in E-Commerce market is seen in recent time throughout the world. With ever increasing popularity of online shopping, Debit or Credit card fraud and personal information security are major concerns for customers, merchants and banks specifically in the case of CNP (Card Not Present). This paper presents a new approach for providing limited information only that is necessary for fund transfer during online shopping thereby safeguarding customer data and increasing customer confidence and preventing identity theft. The method uses combined application of steganography and visual cryptography for this purpose.

Steganography in Modern Smartphones and Mitigation Techniques

Abstract: By offering sophisticated services and centralizing a huge volume of personal data, modern smartphones changed the way we socialize, entertain and work. To this aim, they rely upon complex hardware/software frameworks leading to a number of vulnerabilities, attacks and hazards to profile individuals or gather sensitive information. However, the majority of works evaluating the security degree of smartphones neglects steganography, which can be mainly used to: i) exfiltrate confidential data via camouflage methods, and ii) conceal valuable or personal information into innocent looking carriers. Therefore, this paper surveys the state of the art of steganographic techniques for smartphones, with emphasis on methods developed over the period 2005 to the second quarter of 2014. The different approaches are grouped according to the portion of the device used to hide information, leading to three different covert channels, i.e., local, object and network. Also, it reviews the relevant approaches used to detect and mitigate steganographic attacks or threats. Lastly, it showcases the most popular software applications to embed secret data into carriers, as well as possible future directions.

An analysis of LSB based image steganography techniques

Abstract: Steganography refers to information or a file that has been concealed inside a digital picture, video or audio file. If a person views the object in which the information is hidden inside, he or she will have no indication that there is any hidden information. So the person will not try to decrypt the information. Steganography can be divided into Text Steganography, Image Steganography, Audio/Video Steganography. Image Steganography is one of the common methods used for hiding the information in the cover image. LSB is very efficient algorithm used to embed the information in a cover file. This paper presents the detail knowledge about the LSB based image steganography and its applications to various file formats. In this paper we also analyze the available image based steganography along with cryptography technique to achieve security.

Principles and overview of network steganography

Abstract: The article discusses basic principles of network steganography, which is a comparatively new research subject in the area of information hiding, followed by a concise overview and classification of network steganographic methods and techniques.