Data Hiding in Digital Video

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

Steganalysis of 3D objects using statistics of local feature sets

3D steganalysis aims to identify subtle invisible changes produced in graphical objects through digital watermarking or steganography. Sets of statistical representations of 3D features, extracted from both cover and stego 3D mesh objects, are used as inputs into machine learning classifiers in order to decide whether any information was hidden in the given graphical object. The features proposed in this paper include those representing the local object curvature, vertex normals, the local geometry representation in the spherical coordinate system. The effectiveness of these features is tested in various combinations with other features used for 3D steganalysis. The relevance of each feature for 3D steganalysis is assessed using the Pearson correlation coefficient. Six different 3D watermarking and steganographic methods are used for creating the stego-objects used in the evaluation study

Hide Secret Information in Blocks: Minimum Distortion Embedding

In this paper, a new steganographic method is presented that provides minimum distortion in the stego image. The proposed encoding algorithm focuses on DCT rounding error and optimizes that in a way to reduce distortion in the stego image, and the proposed algorithm produces less distortion than existing methods (e.g., F5 algorithm). The proposed method is based on DCT rounding error which helps to lower distortion and higher embedding capacity.Comment: This paper is accepted for publication in IEEE SPIN 2020 conferenc

A Video Steganography Method based on Transform Block Decision for H.265/HEVC

High definition video application has drawn a lot of interest both from academy and industry. The relevant latest video coding technology, H.265/HEVC has been a promising area for video steganography. In this paper, we present a novel and efficient video steganography method based on transform block decision for H.265. In order to improve the visual quality of carrier video, we analyze the embedding error of data hiding with modifying partitioning parameters of CB, PB and TB, and modify the transform block decision to embed secret message and update corresponding residuals synchronously. In order to limit embedding error, we utilize an efficient embedding mapping rule which can embed N (N>1) bits message and at most modify one bit transform partitioning flag. Our experimental results show that the proposed method can achieve better visual quality, larger embedding capacity and less bit-rate increase than state-of-the-art researches

A Comprehensive Review of Video Steganalysis

Steganography is the art of secret communication and steganalysis is the art of detecting the hidden messages embedded in digital media covers. One of the covers that is gaining interest in the field is video. Presently, the global IP video traffic forms the major part of all consumer Internet traffic. It is also gaining attention in the field of digital forensics and homeland security in which threats of covert communications hold serious consequences. Thus, steganography technicians will prefer video to other types of covers like audio files, still images or texts. Moreover, video steganography will be of more interest because it provides more concealing capacity. Contrariwise, investigation in video steganalysis methods does not seem to follow the momentum even if law enforcement agencies and governments around the world support and encourage investigation in this field. In this paper, we review the most important methods used so far in video steganalysis and sketch the future trends. To the best of our knowledge this is the most comprehensive review of video steganalysis produced so far

3D Mesh Steganalysis using local shape features

Steganalysis aims to identify those changes performed in a specific media with the intention to hide information. In this paper we assess the efficiency, in finding hidden information, of several local feature detectors. In the proposed 3D ste- ganalysis approach we first smooth the cover object and its corresponding stego-object obtained after embedding a given message. We use various operators in order to extract lo- cal features from both the cover and stego-objects, and their smoothed versions. Machine learning algorithms are then used for learning to discriminate between those 3D objects which are used as carriers of hidden information and those are not used. The proposed 3D steganalysis methodology is shown to provide superior performance to other approaches in a well known database of 3D objects