17 research outputs found
MeshAdv: Adversarial Meshes for Visual Recognition
Highly expressive models such as deep neural networks (DNNs) have been widely
applied to various applications. However, recent studies show that DNNs are
vulnerable to adversarial examples, which are carefully crafted inputs aiming
to mislead the predictions. Currently, the majority of these studies have
focused on perturbation added to image pixels, while such manipulation is not
physically realistic. Some works have tried to overcome this limitation by
attaching printable 2D patches or painting patterns onto surfaces, but can be
potentially defended because 3D shape features are intact. In this paper, we
propose meshAdv to generate "adversarial 3D meshes" from objects that have rich
shape features but minimal textural variation. To manipulate the shape or
texture of the objects, we make use of a differentiable renderer to compute
accurate shading on the shape and propagate the gradient. Extensive experiments
show that the generated 3D meshes are effective in attacking both classifiers
and object detectors. We evaluate the attack under different viewpoints. In
addition, we design a pipeline to perform black-box attack on a photorealistic
renderer with unknown rendering parameters.Comment: Published in IEEE CVPR201
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
A numerically stable fragile watermarking scheme for authenticating 3D models
International audienceThis paper analyzes the numerically instable problem in the current 3D fragile watermarking schemes. Some existing fragile watermarking schemes apply the floating-point arithmetic to embed the watermarks. However, these schemes fail to work properly due to the numerically instable problem, which is common in the floating-point arithmetic. This paper proposes a numerically stable fragile watermarking scheme. The scheme views the mantissa part of the floating-point number as an unsigned integer and operates on it by the bit XOR operator. Since there is no numerical problem in the bit operation, this scheme is numerically stable. The scheme can control the watermark strength through changing the embedding parameters. This paper further discusses selecting appropriate embedding parameters to achieve good performance in terms of the perceptual invisibility and the ability to detect unauthorized attacks on the 3D models. The experimental results show that the proposed public scheme could detect attacks such as adding noise, adding/deleting faces, inserting/removing vertices, etc. The comparisons with the existing fragile schemes show that this scheme is easier to implement and use
MỘT ĐỀ XUẤT SỬ DỤNG LƯỚI 3D KHÉP KÍN ĐỂ GIẤU TIN
This paper proposes a structure presentation of 3D mesh and closed mesh, which can apply for hidden messages. Based on shifting value coordinates of vertices, the technique allows information hidden on the triangular 3D mesh model. This above process is controled by rule secret key. The article also mentions a reverse to decode data from stego.Kỹ thuật giấu tin trong đối tượng lưới 3D được đưa ra trong [4], [5] là phương pháp giấu tin trên các đỉnh của một tập các tam giác Theo chuỗi bit khóa sinh ra trong quá trình giấu. Các phương pháp này, trong một số trường hợp, nếu gặp phải lưới hở thì không thực hiện được. Bài báo trình bày phương pháp xác định lưới 3D khép kín, từ đó đề xuất áp dụng các phương pháp giấu tin trong [4], [5] trên kiểu lưới kín đề xuất. Với kỹ thuật này, người nhận chỉ cần biết quy tắc của chuỗi khóa bí mật là có thể giải mã thông tin, sẽ làm tăng tính bảo mật cho các kỹ thuật giấu tin. Thực nghiệm với phương pháp MEP [4] trên các lưới 3D kín cho thấy kỹ thuật này đáp ứng được các yêu cầu giấu tin, có tính bảo mật cao và không cần gửi theo chuỗi bít khóa
Information Hiding Using Geographic Information System (GIS) Vector File
There are different techniques for securing data like cryptography and information hiding (steganography and watermarking) which has received more attention and faced many challenges. In this paper, an efficient digital steganography method has been proposed, where the Geographic Information System (GIS) files used as a cover media. This method depends on hiding text file in a map vector coordinate using ESRI (Environmental Systems Research Institute) Shape file, which stores the geometry of the digital features as sets of vector, coordinates. The method is based on changing the value of unspecific order bits depending on an Input location. Since we are interested in maximizing capacity and ensure robustness requirements. Exploiting the advantage of double percentage number capacity in the 2Dimension vector file was one of the main goals of this research. A Steganography techniques requirement was satisfied since changing maps did not raise any suspicion, while they do not alter the original data content
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
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
Applying 3D Polygonal Mesh Watermarking for Transmission Security Protection through Sensor Networks
Although many research works have been carried out in the area of transmission 3D data through sensor networks, the security issue of transmission remains to be unsolved. It is important to develop systems for copyright protection and digital right management (DRM). In this paper, a blind watermarking algorithm is proposed to protect the transmission security of 3D polygonal meshes through sensor networks. Our method is based on selecting prominent feature vertices (prongs) on the mesh and then embedding the same watermark into their neighborhood regions. The embedding algorithm is based on modifying the distribution of vertex norms by using quadratic programming (QP). Decoding results are obtained by a majority voting scheme over neighborhood regions of these prongs. Assuming that cropping cannot remove all prongs, we can achieve robustness against the cropping attack both theoretically and experimentally. Experiments indicate that the proposed method is also robust against noise, smoothing, and mesh simplification. The proposed method has provided a solution for 3D polygonal watermarking which is potential to withstand a variety of attacks
Steganalysis of meshes based on 3D wavelet multiresolution analysis
3D steganalysis aims to find the information hidden in 3D models and graphical objects. It is assumed that the information was hidden by 3D steganography or watermarking algorithms. A new set of 3D steganalysis features, derived by using multiresolution 3D wavelet analysis, is proposed in this research study. 3D wavelets relate a given mesh representation with its lower and higher graph resolutions by means of a set of Wavelet Coefficient Vectors (WCVs). The 3D steganalysis features are derived from transformations between a given mesh and its corresponding higher and lower resolutions. They correspond to geometric measures such as ratios and angles between various geometric measures. These features are shown to significantly increase the steganalysis accuracy when detecting watermarks which have been embedded by 3D wavelet-based watermarking algorithms. The proposed features, when used in combination with a previously proposed feature set, is shown to provide the best results in detecting the hidden information embedded by other information hiding algorithms