26 research outputs found

    Recent Advances in Steganography

    Get PDF
    Steganography is the art and science of communicating which hides the existence of the communication. Steganographic technologies are an important part of the future of Internet security and privacy on open systems such as the Internet. This book's focus is on a relatively new field of study in Steganography and it takes a look at this technology by introducing the readers various concepts of Steganography and Steganalysis. The book has a brief history of steganography and it surveys steganalysis methods considering their modeling techniques. Some new steganography techniques for hiding secret data in images are presented. Furthermore, steganography in speeches is reviewed, and a new approach for hiding data in speeches is introduced

    Further study on the security of S-UNIWARD

    Full text link

    Side-Information For Steganography Design And Detection

    Get PDF
    Today, the most secure steganographic schemes for digital images embed secret messages while minimizing a distortion function that describes the local complexity of the content. Distortion functions are heuristically designed to predict the modeling error, or in other words, how difficult it would be to detect a single change to the original image in any given area. This dissertation investigates how both the design and detection of such content-adaptive schemes can be improved with the use of side-information. We distinguish two types of side-information, public and private: Public side-information is available to the sender and at least in part also to anybody else who can observe the communication. Content complexity is a typical example of public side-information. While it is commonly used for steganography, it can also be used for detection. In this work, we propose a modification to the rich-model style feature sets in both spatial and JPEG domain to inform such feature sets of the content complexity. Private side-information is available only to the sender. The previous use of private side-information in steganography was very successful but limited to steganography in JPEG images. Also, the constructions were based on heuristic with little theoretical foundations. This work tries to remedy this deficiency by introducing a scheme that generalizes the previous approach to an arbitrary domain. We also put forward a theoretical investigation of how to incorporate side-information based on a model of images. Third, we propose to use a novel type of side-information in the form of multiple exposures for JPEG steganography

    Review of steganalysis of digital images

    Get PDF
    Steganography is the science and art of embedding hidden messages into cover multimedia such as text, image, audio and video. Steganalysis is the counterpart of steganography, which wants to identify if there is data hidden inside a digital medium. In this study, some specific steganographic schemes such as HUGO and LSB are studied and the steganalytic schemes developed to steganalyze the hidden message are studied. Furthermore, some new approaches such as deep learning and game theory, which have seldom been utilized in steganalysis before, are studied. In the rest of thesis study some steganalytic schemes using textural features including the LDP and LTP have been implemented

    Detection of content adaptive LSB matching: a game theory approach

    Full text link

    The role of side information in steganography

    Full text link
    Das Ziel digitaler Steganographie ist es, eine geheime Kommunikation in digitalen Medien zu verstecken. Der ΓΌbliche Ansatz ist es, die Nachricht in einem empirischen TrΓ€germedium zu verstecken. In dieser Arbeit definieren wir den Begriff der Steganographischen Seiteninformation (SSI). Diese Definition umfasst alle wichtigen Eigenschaften von SSI. Wir begrΓΌnden die Definition informationstheoretisch und erklΓ€ren den Einsatz von SSI. Alle neueren steganographischen Algorithmen nutzen SSI um die Nachricht einzubetten. Wir entwickeln einen Angriff auf adaptive Steganographie und zeigen anhand von weit verbreiteten SSI-Varianten, dass unser Angriff funktioniert. Wir folgern, dass adaptive Steganographie spieltheoretisch beschrieben werden muss. Wir entwickeln ein spieltheoretisches Modell fΓΌr solch ein System und berechnen die spieltheoretisch optimalen Strategien. Wir schlussfolgern, dass ein Steganograph diesen Strategien folgen sollte. Zudem entwickeln wir eine neue spieltheoretisch optimale Strategie zur Einbettung, die sogenannten Ausgleichseinbettungsstrategien.TheΒ  goal of digital steganography is to hide a secret communication in digital media. The common approach in steganography is to hide the secret messages in empirical cover objects. We are the first to define Steganographic Side Information (SSI). Our definition of SSI captures all relevant properties of SSI. We explain the common usage of SSI. All recent steganographic schemes use SSI to identify suitable areas fot the embedding change. We develop a targeted attack on four widely used variants of SSI, and show that our attack detects them almost perfectly. We argue that the steganographic competition must be framed with means of game theory. We present a game-theoretical framework that captures all relevant properties of such a steganographic system. We instantiate the framework with five different models and solve each of these models for game-theoretically optimal strategies. Inspired by our solutions, we give a new paradigm for secure adaptive steganography, the so-called equalizer embedding strategies

    Efficient steganography detection by means of compression-based integral classifier

    Get PDF
    ΠŸΡ€Π΅Π΄Π»Π°Π³Π°Π΅Ρ‚ΡΡ концСпция ΠΈΠ½Ρ‚Π΅Π³Ρ€Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ классификатора, ΠΏΡ€Π΅Π΄Π½Π°Π·Π½Π°Ρ‡Π΅Π½Π½ΠΎΠ³ΠΎ для ΠΏΠΎΠ²Ρ‹ΡˆΠ΅Π½ΠΈΡ точности ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² стСгоанализа, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ Π±Π°Π·ΠΈΡ€ΡƒΡŽΡ‚ΡΡ Π½Π° машинном ΠΎΠ±ΡƒΡ‡Π΅Π½ΠΈΠΈ. ВмСсто ΠΎΠ΄ΠΈΠ½ΠΎΡ‡Π½ΠΎΠ³ΠΎ классификатора, ΠΏΡ€ΠΈΠ½ΠΈΠΌΠ°ΡŽΡ‰Π΅Π³ΠΎ Ρ€Π΅ΡˆΠ΅Π½ΠΈΠ΅ ΠΎ пустотС ΠΈΠ»ΠΈ заполнСнности ΠΊΠΎΠ½Ρ‚Π΅ΠΉΠ½Π΅Ρ€Π°, прСдлагаСтся ΠΎΠ±ΡƒΡ‡Π°Ρ‚ΡŒ Π½Π°Π±ΠΎΡ€ классификаторов, ΠΊΠ°ΠΆΠ΄Ρ‹ΠΉ ΠΈΠ· ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… ΠΏΡ€Π΅Π΄Π½Π°Π·Π½Π°Ρ‡Π΅Π½ для ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ ΠΊΠΎΠ½Ρ‚Π΅ΠΉΠ½Π΅Ρ€ΠΎΠ² с ΠΎΠΏΡ€Π΅Π΄Π΅Π»Ρ‘Π½Π½Ρ‹ΠΌΠΈ свойствами. Π’ качСствС Ρ€Π΅Π°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ Π΄Π°Π½Π½ΠΎΠΉ ΠΊΠΎΠ½Ρ†Π΅ΠΏΡ†ΠΈΠΈ прСдставлСн ΠΈΠ½Ρ‚Π΅Π³Ρ€Π°Π»ΡŒΠ½Ρ‹ΠΉ классификатор, основанный Π½Π° сТатии Π΄Π°Π½Π½Ρ‹Ρ…, Ρ‡Ρ‚ΠΎ ΠΏΠΎΠ΄Ρ€Π°Π·ΡƒΠΌΠ΅Π²Π°Π΅Ρ‚ Π²Ρ‹Π±ΠΎΡ€ ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ классификатора ΠΈΠ· Π½Π°Π±ΠΎΡ€Π° Π½Π° основС коэффициСнтов сТатия ΠΊΠΎΠ½Ρ‚Π΅ΠΉΠ½Π΅Ρ€ΠΎΠ². Π­Ρ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ ΠΏΡ€Π΅Π΄Π»Π°Π³Π°Π΅ΠΌΠΎΠ³ΠΎ классификатора для Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ Π·Π°Π΄Π°Ρ‡ΠΈ обнаруТСния скрытой ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½ΠΎ продСмонстрирована для соврСмСнных ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² Π°Π΄Π°ΠΏΡ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ внСдрСния HUGO, WOW ΠΈ S-UNIWARD Π½Π° изобраТСниях-ΠΊΠΎΠ½Ρ‚Π΅ΠΉΠ½Π΅Ρ€Π°Ρ… ΠΈΠ· извСстной Π±Π°Π·Ρ‹ BOSSbase 1.01. Показано, Ρ‡Ρ‚ΠΎ Π² зависимости ΠΎΡ‚ ΠΌΠ΅Ρ‚ΠΎΠ΄Π° внСдрСния ΠΈ количСства скрываСмой ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ ΠΎΡˆΠΈΠ±ΠΊΡƒ обнаруТСния ΠΌΠΎΠΆΠ½ΠΎ ΡΠ½ΠΈΠ·ΠΈΡ‚ΡŒ Π½Π° 0,05-0,16 ΠΏΠΎ ΡΡ€Π°Π²Π½Π΅Π½ΠΈΡŽ с Π»ΡƒΡ‡ΡˆΠΈΠΌΠΈ ΠΈΠ· извСстных Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ²

    Data Hiding in Digital Video

    Get PDF
    With the rapid development of digital multimedia technologies, an old method which is called steganography has been sought to be a solution for data hiding applications such as digital watermarking and covert communication. Steganography is the art of secret communication using a cover signal, e.g., video, audio, image etc., whereas the counter-technique, detecting the existence of such as a channel through a statistically trained classifier, is called steganalysis. The state-of-the art data hiding algorithms utilize features; such as Discrete Cosine Transform (DCT) coefficients, pixel values, motion vectors etc., of the cover signal to convey the message to the receiver side. The goal of embedding algorithm is to maximize the number of bits sent to the decoder side (embedding capacity) with maximum robustness against attacks while keeping the perceptual and statistical distortions (security) low. Data Hiding schemes are characterized by these three conflicting requirements: security against steganalysis, robustness against channel associated and/or intentional distortions, and the capacity in terms of the embedded payload. Depending upon the application it is the designer\u27s task to find an optimum solution amongst them. The goal of this thesis is to develop a novel data hiding scheme to establish a covert channel satisfying statistical and perceptual invisibility with moderate rate capacity and robustness to combat steganalysis based detection. The idea behind the proposed method is the alteration of Video Object (VO) trajectory coordinates to convey the message to the receiver side by perturbing the centroid coordinates of the VO. Firstly, the VO is selected by the user and tracked through the frames by using a simple region based search strategy and morphological operations. After the trajectory coordinates are obtained, the perturbation of the coordinates implemented through the usage of a non-linear embedding function, such as a polar quantizer where both the magnitude and phase of the motion is used. However, the perturbations made to the motion magnitude and phase were kept small to preserve the semantic meaning of the object motion trajectory. The proposed method is well suited to the video sequences in which VOs have smooth motion trajectories. Examples of these types could be found in sports videos in which the ball is the focus of attention and exhibits various motion types, e.g., rolling on the ground, flying in the air, being possessed by a player, etc. Different sports video sequences have been tested by using the proposed method. Through the experimental results, it is shown that the proposed method achieved the goal of both statistical and perceptual invisibility with moderate rate embedding capacity under AWGN channel with varying noise variances. This achievement is important as the first step for both active and passive steganalysis is the detection of the existence of covert channel. This work has multiple contributions in the field of data hiding. Firstly, it is the first example of a data hiding method in which the trajectory of a VO is used. Secondly, this work has contributed towards improving steganographic security by providing new features: the coordinate location and semantic meaning of the object
    corecore