Watermarking has been suggested as a generic technique to solve various problems associated with topics in the areas of digital rights management and multimedia security. Most of the early methods were based on single watermark embedding, but there are great limitations when single watermark embedding algorithms are tried into practical applications. The multiple watermarks are intended to convey different information at the same time. Current approaches rely on adding many watermarks in different bands or channels by means of scaling factor and embedding locations that are mainly defined by experts. This brought many challenges in achieving equilibrium between security, robustness, and quality. The aim of this work is to introduce an intelligent dual watermarking model for colour images that ensure image security for copyright protection (dual watermarking for single purpose). To optimize the dual watermarking requirements, the proposed model that employs both successive (re-) and segmented watermarking techniques is to be implemented with a multi-purpose evolutionary algorithm. Genetic algorithm is adopted to determine the embedding locations and scaling factors for different watermarks according to the features of each host image to balance between imperceptibility and robustness. The wavelet transform is utilized for salient features extraction because of its excellent space-frequency localization of salient image features. In addition, the suggested model encrypts the watermarks with the aid of Walsh transform; so that it is difficult to handle the watermarks even after being extracted by the attackers. Experimental results show that the proposed model is more robust against common image manipulation attacks in terms of PSNR and NCC.

Dual Watermarking for Color Images: A New Image Copyright Protection Model based on the Fusion of Successive and Segmented Watermarking

A lot of watermarking algorithms for vector geographic data are presented in the literature. Due to widely application of digital watermarking, more demands are required, such as multiple watermarking algorithm. However, vector geographic data attracted less research focus on multiple watermarking. Consequently, a multiple watermarking algorithm for vector geographic data is proposed. In particular, the vertices are mapped to the logic domains firstly based on the constructed function. Then every domain is subdivided into blocks according to dichotomy and the number of embedding watermarks. Then, every watermark is embedded in the corresponding block. During the watermark detection, the watermarks are detected without the original vector geographic data. Finally, the experiments are made to test the multiple watermark capacity and robustness against attacks, with an emphasis on cropping attacks. The experimental results show that the proposed algorithm has good robustness against common attacks, such as, data simplification, vertex addition, vertex deletion, feature deletion, and cropping attacks. Moreover, the algorithm provides high multiple watermark capacity.

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A multiple watermarking algorithm for vector geographic data based on coordinate mapping and domain subdivision

Projection transformation is an important part of geographic analysis in geographic information systems, which are particularly common for vector geographic data. However, achieving resistance to projection transformation attacks on watermarking for vector geographic data is still a challenging task. We proposed a digital watermarking against projection transformation based on feature invariants for vector geographic data in this paper. Firstly, the features of projection transformation are analyzed, and the number of vertices, the storage order, and the storage direction of two adjacent objects are designed and used as the feature invariant to projection transformation. Then, the watermark index is calculated by the number of vertices of two adjacent objects, and the embedding rule is determined by the storage direction of two adjacent objects. Finally, the proposed scheme performs blind detection through the storage direction of adjacent features. Experimental results demonstrate that the method can effectively resist arbitrary projection transformation, which indicates the superior performance of the proposed method in comparison to the previous methods.

https://www.mdpi.com/2220-9964/9/11/692/pdf

Blind Digital Watermarking Algorithm against Projection Transformation for Vector Geographic Data

Commutative encryption and watermarking (CEW) is an emerging method that combines encryption technology with digital watermarking technology. It has the dual capability of secure transmission and copyright protection. However, the existing CEW methods for vector maps have good robustness in resisting geometric attacks but poor resistance to vertex attacks (e.g., addition, deletion, etc.). To solve this problem, here we propose a novel invariant-based CEW algorithm for vector maps, which consists of permutation-based encryption scheme and coordinates-based watermarking scheme. In the encryption scheme, the encryption key is generated via the Gaussian distribution method combined with the SHA-512 hash method; then, the double random position permutation strategy is applied to the vector map encryption. In watermarking embedding scheme, the original watermark image is scrambled via logistic chaotic encryption before embedding, and the coordinates of all the vertices are normalized. Then, the scrambled watermark image is embedded into the normalized coordinates. Results show that: proposed method is more robust to conventional attacks (e.g., vertex addition and deletion, reordering and data format conversion) and geometric attacks (e.g., scaling and translation). In addition, compared with the existing CEW methods for vector maps, the proposed method has higher security and stronger robustness against vertex attacks.

A Novel Invariant Based Commutative Encryption and Watermarking Algorithm for Vector Maps

The existing commutative encryption and watermarking (CEW) methods based on feature invariants can achieve both the robustness of the watermarking algorithm and the security of the encryption algorithm. However, they are only applicable to the raster data such as images, videos, etc. In particular, the organization structure and storage structure of vector map have not been considered in these methods. Therefore, they cannot be used for vector map. This paper derives two feature invariants to solve this problem, which are the sum of inner angles and the storage direction of two adjacent objects according to the inherent characteristics of vector map. Based on these two feature invariants, a new CEW method is proposed in this paper, which includes the feature invariants based watermarking algorithm and the perceptual stream cipher based encryption algorithm on coordinates. Since the coordinate values used in encryption and the feature invariants used in watermarking are independent of each other, the commutativity is achieved for the proposed CEW method. The experiments are given to verify that the proposed CEW method can achieve the commutativity between encryption and watermarking without deteriorating accuracy of data. Besides, it has been verified that the proposed method is more robust to rotate, scaling, translation, and projection transformation compared with the existing CEW methods and has high security. The proposed algorithm has good scalability of encryption, and arbitrary encryption methods based on encrypting the coordinate values can be applied without affecting the extracted feature invariants.

/pdf/commutative-encryption-and-watermarking-algorithm-based-on-4z1fqf4oku.pdf

Commutative Encryption and Watermarking Algorithm Based on Feature Invariants for Secure Vector Map

Vector geographic data are the fundamental achievements of national information infrastructure, and they play an important role in society’s development. How to protect the copyright of vector geographic data has become a popular issue in the age of big data, and digital watermarking technology can be used to solve this problem. In this paper, a robust and blind watermarking algorithm for vector geographic data is proposed based on the technology of coordinate mapping and matching detection. First, the basic principle for resisting data translation based on quantization index modulation (QIM) and matching detection was analyzed. Second, a watermarking algorithm for vector geographic data was designed based on coordinate mapping, QIM and matching detection. Finally, we performed experiments to test the robustness and adaptability of the proposed algorithm. The experimental results show that the proposed watermarking algorithm is not only robust against the watermarking attacks of data compression, data adding, data deleting, data cropping, feature deleting and data translation but also against composite attack. The proposed algorithm is also suitable for small vector geographic datasets such as point-based data.

A Robust Watermarking Algorithm for Vector Geographic Data Based on Qim and Matching Detection

The multiple watermarking algorithm is present for vector geographic data based on the characteristics of vector data. In the embedding progress multiple watermarks were embedded additively in the cover data following additivity rule. In the detection progress the additive watermarks were extracted and then the contents of watermarks were detected on the basis of correlation detection together with discriminant analysis. In the experiments the robustness and adaptability were analyzed. The results show that the proposed multiple watermarking algorithm is robust against common attacks and suit for the vector geographic data with small amount of vertexes.

A Novel Multiple Watermarking Algorithm Based on Correlation Detection for Vector Geographic Data

With the rapid development of computer and communication techniques, copyright protection of vector geographic data has attracted considerable research attention because of the high cost of such data. A novel adaptive watermark detection algorithm is proposed for vector geographic data that can be used to qualitatively analyze the robustness of watermarks against data addition attacks. First, a watermark was embedded into the vertex coordinates based on coordinate mapping and quantization. Second, the adaptive watermark detection model, which is capable of calculating the detection threshold, false positive error (FPE) and false negative error (FNE), was established, and the characteristics of the adaptive watermark detection algorithm were analyzed. Finally, experiments were conducted on several real-world vector maps to show the usability and robustness of the proposed algorithm.

An Adaptive Watermark Detection Algorithm for Vector Geographic Data

The invention discloses a strong-robustness watermark embedding and extraction method for original remote sensing images. Based on Contourlet transformation and an image normalization theory, the important region of a normalized image, which is suitable for the embedding of watermark, is selected; based on the characteristics of the Contourlet transformation and the stability of singular values, watermark modulation is carried out after a low-frequency sub-band singular value is decomposed; a pre-distortion compensation mechanism is introduced to complete watermark embedding; and when watermark detection is carried out, double detection mechanisms are adopted, when the detection fails, a detection process is implemented again after brightness contrast correction, and the watermark detection can be completed. As indicated by experiments, the method of the invention has strong robustness for conventional image processing, geometric attack, brightness contrast adjustment and the like.

Strong-robustness watermark embedding and extraction method for original remote sensing images

The present invention discloses a watermark-containing tile remote sensing image location method based on a location block mechanism. The method employs the blocking DCT transformation, and the size of the blocking is 8*8 compatible with the digital media compressed encoding to resist the common data compression processing of the tile remote sensing image. The design of the location mechanism takes the digital watermark technology as the core, 3 8*8 blockings at the upper left corner, the lower left corner and the lower right corner in the coefficient matrix generated of the watermark-containing tile remote sensing image after the blocking DCT transformation are selected as the location blockings, and the stable and cognizable location information is embedded in the location blockings. At the watermark detection, the position of the watermarking-containing tile remote sensing image is accurately located through searching the location blocks. The watermark-containing tile remote sensing image location method based on the location block mechanism calibrate the watermark-containing tile remote sensing image through the location blockings having the functions being similar to the QR code position detection graph, and the location information embedded in the location blockings can be accurately detected and identified through the JPEG compression attack, the splicing processing and the area cutting processing without influencing the availability of the tile remote sensing image, and the location process is effective and reliable.

Zhu Changqing

Papers

A Robust Watermarking Algorithm for Vector Geographic Data Based on Qim and Matching Detection

A Novel Multiple Watermarking Algorithm Based on Correlation Detection for Vector Geographic Data

An Adaptive Watermark Detection Algorithm for Vector Geographic Data

Strong-robustness watermark embedding and extraction method for original remote sensing images

Watermark-containing tile remote sensing image location method based on location block mechanism