A Review of 2D &3D Image Steganography Techniques

This examination displays an outline of different three-dimensional (3D) picture steganography methods from overview perspective. This paper exhibit scientific categorization of 3D picture steganography systems and distinguish the ongoing advances in this field. Steganalysis and assaults on 3D picture steganography calculations have likewise been examined. 3D picture steganography strategies in all the three spaces: geometrical, topological and portrayal areas have been contemplated and thought about among each other on different parameters, for example, inserting limit, reversibility and reaction towards assaults. A few difficulties which restrain the advancement of 3D steganography calculations have been recognized. This investigation finishes up with some valuable discoveries at last

Information Analysis for Steganography and Steganalysis in 3D Polygonal Meshes

Information hiding, which embeds a watermark/message over a cover signal, has recently found extensive applications in, for example, copyright protection, content authentication and covert communication. It has been widely considered as an appealing technology to complement conventional cryptographic processes in the field of multimedia security by embedding information into the signal being protected. Generally, information hiding can be classified into two categories: steganography and watermarking. While steganography attempts to embed as much information as possible into a cover signal, watermarking tries to emphasize the robustness of the embedded information at the expense of embedding capacity. In contrast to information hiding, steganalysis aims at detecting whether a given medium has hidden message in it, and, if possible, recover that hidden message. It can be used to measure the security performance of information hiding techniques, meaning a steganalysis resistant steganographic/watermarking method should be imperceptible not only to Human Vision Systems (HVS), but also to intelligent analysis. As yet, 3D information hiding and steganalysis has received relatively less attention compared to image information hiding, despite the proliferation of 3D computer graphics models which are fairly promising information carriers. This thesis focuses on this relatively neglected research area and has the following primary objectives: 1) to investigate the trade-off between embedding capacity and distortion by considering the correlation between spatial and normal/curvature noise in triangle meshes; 2) to design satisfactory 3D steganographic algorithms, taking into account this trade-off; 3) to design robust 3D watermarking algorithms; 4) to propose a steganalysis framework for detecting the existence of the hidden information in 3D models and introduce a universal 3D steganalytic method under this framework. %and demonstrate the performance of the proposed steganalysis by testing it against six well-known 3D steganographic/watermarking methods. The thesis is organized as follows. Chapter 1 describes in detail the background relating to information hiding and steganalysis, as well as the research problems this thesis will be studying. Chapter 2 conducts a survey on the previous information hiding techniques for digital images, 3D models and other medium and also on image steganalysis algorithms. Motivated by the observation that the knowledge of the spatial accuracy of the mesh vertices does not easily translate into information related to the accuracy of other visually important mesh attributes such as normals, Chapters 3 and 4 investigate the impact of modifying vertex coordinates of 3D triangle models on the mesh normals. Chapter 3 presents the results of an empirical investigation, whereas Chapter 4 presents the results of a theoretical study. Based on these results, a high-capacity 3D steganographic algorithm capable of controlling embedding distortion is also presented in Chapter 4. In addition to normal information, several mesh interrogation, processing and rendering algorithms make direct or indirect use of curvature information. Motivated by this, Chapter 5 studies the relation between Discrete Gaussian Curvature (DGC) degradation and vertex coordinate modifications. Chapter 6 proposes a robust watermarking algorithm for 3D polygonal models, based on modifying the histogram of the distances from the model vertices to a point in 3D space. That point is determined by applying Principal Component Analysis (PCA) to the cover model. The use of PCA makes the watermarking method robust against common 3D operations, such as rotation, translation and vertex reordering. In addition, Chapter 6 develops a 3D specific steganalytic algorithm to detect the existence of the hidden messages embedded by one well-known watermarking method. By contrast, the focus of Chapter 7 will be on developing a 3D watermarking algorithm that is resistant to mesh editing or deformation attacks that change the global shape of the mesh. By adopting a framework which has been successfully developed for image steganalysis, Chapter 8 designs a 3D steganalysis method to detect the existence of messages hidden in 3D models with existing steganographic and watermarking algorithms. The efficiency of this steganalytic algorithm has been evaluated on five state-of-the-art 3D watermarking/steganographic methods. Moreover, being a universal steganalytic algorithm can be used as a benchmark for measuring the anti-steganalysis performance of other existing and most importantly future watermarking/steganographic algorithms. Chapter 9 concludes this thesis and also suggests some potential directions for future work

Simplification Resilient LDPC-Coded Sparse-QIM Watermarking for 3D-Meshes

We propose a blind watermarking scheme for 3-D meshes which combines sparse quantization index modulation (QIM) with deletion correction codes. The QIM operates on the vertices in rough concave regions of the surface thus ensuring impeccability, while the deletion correction code recovers the data hidden in the vertices which is removed by mesh optimization and/or simplification. The proposed scheme offers two orders of magnitude better performance in terms of recovered watermark bit error rate compared to the existing schemes of similar payloads and fidelity constraints.Comment: Submitted, revised and Copyright transfered to IEEE Transactions on Multimedia, October 9th 201

Adaptive 3D Mesh Steganography Based on Feature-Preserving Distortion

3D mesh steganographic algorithms based on geometric modification are vulnerable to 3D steganalyzers. In this paper, we propose a highly adaptive 3D mesh steganography based on feature-preserving distortion (FPD), which guarantees high embedding capacity while effectively resisting 3D steganalysis. Specifically, we first transform vertex coordinates into integers and derive bitplanes from them to construct the embedding domain. To better measure the mesh distortion caused by message embedding, we propose FPD based on the most effective sub-features of the state-of-the-art steganalytic feature set. By improving and minimizing FPD, we can efficiently calculate the optimal vertex-changing distribution and simultaneously preserve mesh features, such as steganalytic and geometric features, to a certain extent. By virtue of the optimal distribution, we adopt the Q-layered syndrome trellis coding (STC) for practical message embedding. However, when Q varies, calculating bit modification probability (BMP) in each layer of Q-layered will be cumbersome. Hence, we contrapuntally design a universal and automatic BMP calculation approach. Extensive experimental results demonstrate that the proposed algorithm outperforms most state-of-the-art 3D mesh steganographic algorithms in terms of resisting 3D steganalysis.Comment: IEEE TVCG major revisio

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography

Data hiding is the process of embedding information into a noise-tolerant signal such as a piece of audio, video, or image. Digital watermarking is a form of data hiding where identifying data is robustly embedded so that it can resist tampering and be used to identify the original owners of the media. Steganography, another form of data hiding, embeds data for the purpose of secure and secret communication. This survey summarises recent developments in deep learning techniques for data hiding for the purposes of watermarking and steganography, categorising them based on model architectures and noise injection methods. The objective functions, evaluation metrics, and datasets used for training these data hiding models are comprehensively summarised. Finally, we propose and discuss possible future directions for research into deep data hiding techniques

Nouvelles méthodes de synchronisation de nuages de points 3D pour l'insertion de données cachées

This thesis addresses issues relating to the protection of 3D object meshes. For instance, these objects can be created using CAD tool developed by the company STRATEGIES. In an industrial context, 3D meshes creators need to have tools in order to verify meshes integrity, or check permission for 3D printing for example.In this context we study data hiding on 3D meshes. This approach allows us to insert information in a secure and imperceptible way in a mesh. This may be an identifier, a meta-information or a third-party content, for instance, in order to transmit secretly a texture. Data hiding can address these problems by adjusting the trade-off between capacity, imperceptibility and robustness. Generally, data hiding methods consist of two stages, the synchronization and the embedding. The synchronization stage consists of finding and ordering available components for insertion. One of the main challenges is to propose an effective synchronization method that defines an order on mesh components. In our work, we propose to use mesh vertices, specifically their geometric representation in space, as basic components for synchronization and embedding. We present three new synchronisation methods based on the construction of a Hamiltonian path in a vertex cloud. Two of these methods jointly perform the synchronization stage and the embedding stage. This is possible thanks to two new high-capacity embedding methods (from 3 to 24 bits per vertex) that rely on coordinates quantization. In this work we also highlight the constraints of this kind of synchronization. We analyze the different approaches proposed with several experimental studies. Our work is assessed on various criteria including the capacity and imperceptibility of the embedding method. We also pay attention to security aspects of the proposed methods.Cette thèse aborde les problèmes liés à la protection de maillages d'objets 3D. Ces objets peuvent, par exemple, être créés à l'aide d'outil de CAD développés par la société STRATEGIES. Dans un cadre industriel, les créateurs de maillages 3D ont besoin de disposer d'outils leur permettant de vérifier l'intégrité des maillages, ou de vérifier des autorisations pour l'impression 3D par exemple. Dans ce contexte nous étudions l'insertion de données cachées dans des maillages 3D. Cette approche permet d'insérer de façon imperceptible et sécurisée de l'information dans un maillage. Il peut s'agir d'un identifiant, de méta-informations ou d'un contenu tiers, par exemple, pour transmettre de façon secrète une texture. L'insertion de données cachées permet de répondre à ces problèmes en jouant sur le compromis entre la capacité, l'imperceptibilité et la robustesse. Généralement, les méthodes d'insertion de données cachées se composent de deux phases, la synchronisation et l'insertion. La synchronisation consiste à trouver et ordonner les éléments disponibles pour l'insertion. L'un des principaux challenges est de proposer une méthode de synchronisation 3D efficace qui définit un ordre sur les composants des maillages. Dans nos travaux, nous proposons d'utiliser les sommets du maillage, plus précisément leur représentation géométrique dans l'espace comme composants de base pour la synchronisation et l'insertion. Nous présentons donc trois nouvelles méthodes de synchronisation de la géométrie des maillages basées sur la construction d'un chemin hamiltonien dans un nuage de sommets. Deux de ces méthodes permettent de manière conjointe de synchroniser les sommets et de cacher un message. Cela est possible grâce à deux nouvelles méthodes d'insertion haute capacité (de 3 à 24 bits par sommet) qui s'appuient sur la quantification des coordonnées. Dans ces travaux nous mettons également en évidence les contraintes propres à ce type de synchronisation. Nous discutons des différentes approches proposées dans plusieurs études expérimentales. Nos travaux sont évalués sur différents critères dont la capacité et l'imperceptibilité de la méthode d'insertion. Nous portons également notre attention aux aspects sécurité des méthodes

Graph Spectral Domain Watermarking for Unstructured Data from Sensor Networks

The modern applications like social networks and sensors networks are increasingly used in the recent years. These applications can be represented as a weighted graph using irregular structure. Unfortunately, we cannot apply the techniques of the traditional signal processing on those graphs. In this paper, graph spread spectrum watermarking is proposed for networked sensor data authentication. Firstly, the graph spectrum is computed based on the eigenvector decomposition of the graph Laplacian. Then, graph Fourier coefficients are obtained by projecting the graph signals onto the basis functions which are the eigenvectors of the graph Laplacian. Finally, the watermark bits are embedded in the graph spectral coefficients using a watermark strength parameter varied according to the eigenvector number. We have considered two scenarios: blind and non-blind watermarking. The experimental results show that the proposed methods are robust, high capacity and result in low distortion in data. The proposed algorithms are robust to many types of attacks: noise, data modification, data deletion, rounding and down-sampling

Robust feature-based 3D mesh segmentation and visual mask with application to QIM 3D watermarking

The last decade has seen the emergence of 3D meshes in industrial, medical and entertainment applications. Many researches, from both the academic and the industrial sectors, have become aware of their intellectual property protection arising with their increasing use. The context of this master thesis is related to the digital rights management (DRM) issues and more particularly to 3D digital watermarking which is a technical tool that by means of hiding secret information can offer copyright protection, content authentication, content tracking (fingerprinting), steganography (secret communication inside another media), content enrichment etc. Up to now, 3D watermarking non-blind schemes have reached good levels in terms of robustness against a large set of attacks which 3D models can undergo (such as noise addition, decimation, reordering, remeshing, etc.). Unfortunately, so far blind 3D watermarking schemes do not present a good resistance to de-synchronization attacks (such as cropping or resampling). This work focuses on improving the Spread Transform Dither Modulation (STDM) application on 3D watermarking, which is an extension of the Quantization Index Modulation (QIM), through both the use of the perceptual model presented, which presents good robustness against noising and smoothing attacks, and the the application of an algorithm which provides robustness noising and smoothing attacks, and the the application of an algorithm which provides robustness against reordering and cropping attacks based on robust feature detection. Similar to other watermarking techniques, imperceptibility constraint is very important for 3D objects watermarking. For this reason, this thesis also explores the perception of the distortions related to the watermark embed process as well as to the alterations produced by the attacks that a mesh can undergo