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

Yang, Cheng‐Hong; Zhu, Chenchen; Wang, Yingying; Rui, Ting; Zhu, Jingwei; Ding, Kaimeng

doi:10.1007/s11042-020-08916-4

Cited by 19 publications

(3 citation statements)

References 22 publications

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“…With the rapid development of geographic information science, vector geographic data plays an important role in the national economy, urban national security, and environmental protection [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

A zero-watermarking algorithm for vector geographic data based on feature invariants

Wang

Zhang

et al. 2022

Earth Sci Inform

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Most researches on zero-watermarking algorithms for vector geographic data focus on improving the robustness against geometrical attacks, compression attacks and object attacks. However, there are few zero-watermarking algorithms against projection transformation. We proposed a zerowatermarking algorithm for vector geographic data based on feature invariants. After any projection transformation of vector geographic data, the number of vertices and relative storage order of objects does not change. Therefore, the number of vertices and relative storage order of objects can be considered as the feature invariants. Firstly, according to relative storage order of objects, the watermark bit is determined by comparing the number of vertices between any two objects. Secondly, the watermark index is calculated by the number of vertices of two objects. Then, a feature matrix is constructed combining the watermark bit and the watermark index. Finally, the XOR operation is performed between the feature matrix and the scrambled watermark image to generate the zerowatermark image. The experiments show that the watermark can be detected from the vector geographic data after any projection transformation. And this algorithm can effectively against geometrical attacks, object attacks and precision reduction attacks, showing superior performance compared with previous algorithms.

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Section: Introductionmentioning

confidence: 99%

A zero-watermarking algorithm for vector geographic data based on feature invariants

Wang

Zhang

et al. 2022

Earth Sci Inform

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“…Vector maps are one of the most important geospatial data [1,2], which play a vital role in economic development and national security [3,4]. Currently, vector maps have been widely used in navigation, cadastral management, urban planning and many other fields [5].…”

Section: Introductionmentioning

confidence: 99%

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

Zhang

Wang

et al. 2021

IJGI

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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.

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“…Many research efforts have been devoted to improving the robustness of watermarking algorithms [11][12][13][14]. These efforts have led watermarking algorithms less vulnerable to compression, filtering, point addition and deletion [15][16][17][18][19][20]. However, as a common processing method of vector geographic data, projection transformation will cause the coordinate values and geometric shapes of vector geographic data to change [21].…”

Section: Introductionmentioning

confidence: 99%

Blind Digital Watermarking Algorithm against Projection Transformation for Vector Geographic Data

Zhou

Ren

Zhu

et al. 2020

IJGI

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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.

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

Cited by 19 publications

References 22 publications

A zero-watermarking algorithm for vector geographic data based on feature invariants

A zero-watermarking algorithm for vector geographic data based on feature invariants

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

Blind Digital Watermarking Algorithm against Projection Transformation for Vector Geographic Data

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