Sharif Digital Repository

A major goal in image steganography is to preserve the statistical properties of the host image to thwart statistical based steganalysis. However, most steganography methods introduce some distortions into the host signal’s statistical properties that have been used, as a certain indication of manipulation of the signal, by steganalysis algorithms. In order to overcome such a methodical vulnerability, a new generation of data hiding algorithms has been proposed in the literature to preserve histogram of the host signal. In this thesis we present a novel image steganographic technique to preserve one-dimensional and two-dimensional histograms of the host image. Experimental results show that... 

Providing security for digital information in a communication channel is a challenge in the recent years. This is due to the strength of high-speed processing resources that can threaten the security and correctness of communicating information. Using steganography method, the secret information can be hidden in an innocent media that does not attract the attention of third parties. This research discusses about steganography in images. The main goal of this research is presenting a universal steganography scheme with high steganography capacity. Using this scheme the steganographer can embed every large secret data in images securely. The reasons for selecting the subject of “Improving... 

Nowadays, steganography is one of the secure communication methods. Exploitation of modern technologies has increased transmission bandwidth to a considerable scale. As a result of this, the multimedia signals such as Audio and Image have been used in communications widely. This application has led to the prevalent use of these signals as cover signals for carrying hidden messages. Given the proliferation of digital images, especially on the Internet, and given the large amount of redundant bits present in the digital representation of an image, images are the most popular cover objects for steganography. Simultaneously, steganalysis tries to defeat the very purpose of steganography by... 

Steganography is the art and technique of concealing secret message in ordinary data cover, transmitted over a public channel, in a way that eavesdroppers, as well as the channel users, cannot detect the presence of the secret message. However, steganalysis tries to detect this type of covert communication using some effective analysis techniques. Steganalysis is often based on statistical properties of the suspicious signal that are expected to change due to the message embedding process. Secret message (which mostly is a set of pseudo-random bits because of cryptography) affects the statistical features of the cover signal. So far, many steganalysis techniques have been reported that are... 

This thesis proposes new algorithms for digital watermarking that are based on Independent Component Analysis (ICA) technique. First, we will show that ICA allows the maximization of the information content and minimization of the induced distortion by decomposing the covertext (in this thesis the image) into statistically independent components. In fact, for a broad class of attacks and fixed capacity values, one can show that distortion is minimized when the message is embedded in statistically independent components. Information theoretical analysis also shows that the information hiding capacity of statistically independent components is maximal. Then we will propose a new wavelet... 

Digital Steganography is the embedding of digital data into a video, image or audio signal. The embedding must be done such that the perceptual quality of the host signal does not seriously degrade. In the last decade, Steganography has received considerable attention in various application fields. Steganography is not always a legal process and may be used to establish illegal communications, transfer malware files to certain targets, or collect data illicitly from an organization. Steganalysis methods are developed to detect Steganography in such applications.
The purpose of this thesis is to develop a new steganalysis method based on perceptual models and statistical structure of the... 

Image steganalysis is the technique and art of detecting covert communication via images.Reduction of features dimentionality is an important issue according to accuracy and time complexity. In this thesis, GA (genetic algorithm) and PSO (Particle Swarm Optimization) are used to reduce the dimentionality of JRM, a recently proposed feature set containing 11255 features which looks high dimentional compared to other feature sets which has been reduced by evolutionary algorithms so far. So, inspite of other works done using evolutionary algorithms in this field, we use the class sepearability criterion as fitness function instead of the accuracy of the classifier. Investigating these features,... 

Steganalysis is the science of detecting covert communication. It is called blind (universal) if designed to detect stego images steganographied by a wide range of embedding methods. In this method, statistical properties of the image are explored, regardless the embedding procedure employed. The main problem for image steganalysis is to find sensitive features and characteristics of the image which make a statistically significant difference between the clean and stego images. In this thesis we propose a blind image steganalysis method based on the singular value decomposition (SVD) of the discrete cosine transform (DCT) coefficients that are revisited in this work in order to enhance the... 

Widespread transfer of digital files over networks provides a hidden channel to transfer secret messages. Current steganalysis schemes need to work on a complete image for doing the detection job that starts when the image is entirely transferred, so are often restricted to an offline process. This restriction is serious when existence of the hidden message carriers on the network is shorter than the time required for the detection process. In this thesis, we propose a structurally fast detection method to detect the data hidden in an image passing through network. We use two of most powerful steganalysis algorithms for steganalysis of images that proposed by 1) Fridrich and Pevny and 2) Liu... 

Steganography is the art and science of writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message, a form of security through obscurity. In this thesis, we focus on entropic issue of multimedia signal in the two branches of Information hiding namely Steganography and Watermarking. How to choose the block and noise estimation in the watermarking, and analysis of the singular values decomposition in steganography are examples of using entopic issue which we use in our thesis. The two new designs for video signals AVI are presented in Watermarking. For the both proposed method ,first AVI video signal will be divided... 

Steganalysis is the art of detecting hidden message in a cover such as an image. All steganalysis methods either are designed for a specific steganographer or are blind. Since for a stego image, the steganography method is not available, this is important to detect a stego image without any knowledge about the steganography method using which the secret image was embedded. Therefore in order to dominate all steganography method, if a given image is a stego one, we need to use voting over several steganalysis methods applied on the stego image to improve the accuracy of detection. But this approach needs a long time to process that is not practical for most steganalysis applications. We know... 

The goal of this thesis is using sparse decomposition to design secure steganography algorithms to insert secret data into the different cover signals. We propose data embedding in higher semantic levels of the cover signal to reach this goal. Sparse decomposition represents a signal as a linear combination of its structural elements. Data insertion into the sparse coefficients slightly changes the effect of structural elements in the signal representation. So, quality of the stego signal is preserved and such a steganography method leads to higher imperceptibility. In addition, data insertion into the higher semantic levels leads to the higher undetectability. Steganalyzers use statistical... 

In this project we proposed a new method for improving the detection abality of a steganalyser with a pre-processing on contents of an image. Steganalysis, using machine learning, is designing a classifier with two classes: Stego or Cover. This classifier should be trained with extracted features from signal. The result of the training procedure is a machine that decides a signal belongs to stego or cover class. The first step of steganalysis process is extraction of proper features from signal. Proper feature is a variable that represents all of the useful properties of signal. Second step of this process is classifying data to two class of stego and cover. Many algorithms are proposed for... 

LSB embedding in spatial domain with very low rate can be easily performed and its detection in spite of many researches is very hard, while BOSS competition has been held to break an adaptive embedding algorithm with low rate. Thus, proposing powerful steganalyzer of very low rate in spatial domain is highly requested. In this thesis it has been tried to present some algorithms to detect secret message with very low rate in spatial domain using eigenvalues analysis and relative auto-correlation of image.First approach is based on the analysis of the eigenvalues of the cover correlation matrix that we used for the first time. Image partitioning, correlation function computation,... 

This thesis explored and described a new steganalysis system modeling. Image steganalysis systems are divided into two parts: feature extraction from images and classification of images. Many researches have been done in both parts and satisfactory results have also been reported. There are acceptable steganalysis methods which work accurately in high rates of steganography; however steganography in low rates is still undetectable. By lowering the rate of steganography in images, the difference between stego images and clean images would be reduced which accordingly led to the reduction of the difference between the corresponding extracted features. Thus, the ability of classification... 

Steganalysis is the process of discovering existence of hidden data in a file or image. Recent advances in steganographic methods result in their wide use in secure communications applications. Reports of using information hiding by criminals to send messages, and malwares to communicate to servers, emphasizes importance of steganalysis in real time applications. Due to wide use of JPEG images in social media and internet, steganalysis of JPEG images is a highly active research topic in information hiding. Number of steganographic tools available for steganography in JPEG domain, shows importance of steganalysis of this image format. Classic Steganalysis techniques combine feature... 

With the expansion of digital communications, the need for secure methods to transmit information confidentially has increased. Steganography, as one of the effective solutions, faces challenges in terms of quality, capacity, and security. This research presents novel schemes for steganography and steganalysis that utilize deep learning for embedding images into audio and detecting the audio carrier of the message. In the proposed steganography method, the image is embedded at the bit level in the frequency domain of the audio file. For this purpose, a structure with multiple paths between the layers of the network, utilizing the Inception-A network, is proposed, which improves processing and...