An Efficient Robust Multiple Watermarking Algorithm for Vector Geographic Data

Abstract

Vector geographic data play an important role in location information services. Digital watermarking has been widely used in protecting vector geographic data from being easily duplicated by digital forensics. Because the production and application of vector geographic data refer to many units and departments, the demand for multiple watermarking technology is increasing. However, multiple watermarking algorithm for vector geographic data draw less attention, and there are many urgent problems to be solved. Therefore, an efficient robust multiple watermark algorithm for vector geographic data is proposed in this paper. The coordinates in vector geographic data are first randomly divided into non-repetitive sets. The multiple watermarks are then embedded into the different sets. In watermark detection correlation, the Lindeberg theory is used to build a detection model and to confirm the detection threshold. Finally, experiments are made in order to demonstrate the detection algorithm, and to test its robustness against common attacks, especially against cropping attacks. The experimental results show that the proposed algorithm is robust against the deletion of vertices, addition of vertices, compression, and cropping attacks. Moreover, the proposed detection algorithm is compatible with single watermarking detection algorithms, and it has good performance in terms of detection efficiency. Therefore, multiple watermarking technology can effectively solve the above information security problems of vector geographic data.Currently, many scholars have been devoted to developing digital watermark technology, and they have proposed many algorithms [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. However, these algorithms focus on embedding only one watermark in the cover data, which then lacks multi-copyright protection. Multiple watermarking draws less attention than single watermarking, and it does not simply involve the embedding of different watermarks by using the single watermarking algorithm. The multiple watermarking algorithm commonly focuses on images and videos. There are three main methods for addressing the impact of multiple watermarks, as described in References [17][18][19][20][21][22][23][24][25][26][27][28][29][30]. The first is dividing the images into multiple blocks for multiple watermarks [17,18,27,29]. The second is embedding multiple watermarks into different frequency domains or channels [19][20][21][22][23]26,30]. The last is merging multiple watermarks into one [24,25,27]. Usually multiple methods are combined in one algorithm. In the above references, only a few previous works have been proposed for vector geographic data; for instance, References [24-29]. Sun et al. combined a child copyright watermark with another child watermark consisting of features selected by fuzzy clustering from the vector map. The new watermark was then embedded into the vector map [24]. Li et al. proposed a multiple watermark embedding solution through the generation of additional information with waterma...

Blind Digital Watermarking Algorithm against Projection Transformation for Vector Geographic Data

“…Table 1 shows the detailed information of four vector maps. In the step of watermark generation, the meaningless binary watermark [11] w 0 presents the copyright of "OWNERSHIP IS GEOMARK". The length of the watermark is 130 bits.…”

“…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].…”

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

“…At present, digital watermarking technology is widely used for copyright protection and traceability of vector geographic data [6][7][8][9]. Traditional digital watermarking techniques embeds watermark information by modifying coordinate values in the spatial domain [10][11][12][13] or frequency domain [14][15][16][17], which will reduce the accuracy and is not suitable for high-fidelity vector geographic data [18][19][20]. The emergence of zero-watermarking technology has solved this problem very well.…”

Copyright Protection Based on Zero Watermarking and Blockchain for Vector Maps

“…Digital watermark technology provides good technical support for protecting the copyrights of vector data [1]. The existing digital watermark algorithms for vector data are mainly divided into spatial domain [2][3][4] and frequency domain [5,6] algorithms. These two types of methods embed watermark information by modifying coordinate values directly or indirectly.…”