Abstract
Dramatic advancements in Geographic Information Systems (GIS) and computer technologies resulted in a wide availability of rich-knowledge GIS digital vector maps that are easily accessible and downloadable through the world wide web. This led to the need of copyright protection systems to protect the rights of the producers of these maps. Unlike the research on copyright protection for raster/image data types, the research for vector map data is less documented. This article surveys and classifies the GIS vector map copyright protection research papers published between 2000 and 2014, towards a thorough understanding of the-state-of-the-art, addressing significant limitations of previous review articles, and outlining effective recommendations for future research directions.
Similar content being viewed by others
1 Introduction
Developments in computer technologies and Geographic Information Systems (GIS), i.e. computer-based systems for managing and displaying locational data related to positions on Earths surface [89], increased the amount of digital vector maps that are available on the world wide web. GIS vector maps are highly accurate, they document attribute and topological information through the use of geometrical shapes, and are more compact in size compared with GIS raster maps such as satellite images. While these properties make GIS vector maps of high quality, their complexity and level of detail also means that they incur a high production cost.Footnote 1
GIS vector maps are widely used in environmental, social and economic applications such as disaster management, navigation, infrastructure and utilities allocation, and business planning. They are also used in military/security applications. Due to the value of these maps, their protection is necessary not only to prevent attackers gaining economic advantage (by using them without paying copyright fees), but also to prevent their unethical use in situations related to national and international security.
To prevent GIS vector maps being illegally modified and exchanged, different copyright techniques have been used, which fall mainly in two categories: encryption and information hiding. Encryption is part of a cryptographic system that has the purpose to protect the content of a message/file. Information hiding is used in several sub-disciplines, of which the most important are steganography and watermarking. In steganography, the purpose of information hiding is to keep secret the existence of information, while in watermarking, the purpose is to make the hidden information imperceptible. The interested reader can find a more detailed distinction between these fields in [90]. From these approaches, the watermarking approach is the most popular for marking the copyright of GIS vector maps.
A digital map watermarking system consists of three modules: embedding, evaluation and extraction, as shown in Fig. 1. The embedding module involves hiding the watermark bits inside the original map content and often involves the use of a secret key (which is needed in the extraction stage). The evaluation module is for judging the quality of the map watermarking approach through particular evaluation metrics. The extraction module involves the extraction of the watermark and is important for making assertions about the data ownership.
The general system of digital vector map watermarking
GIS maps of raster data format (e.g. image) received more attention than digital GIS vector maps in watermarking research, e.g. [1, 178, 205]; however, due to the importance of vector maps, the research for watermarking this type of maps has increased in the last decade. This article surveys and classifies the GIS vector map watermarking research articles published between 2000 and 2014, towards a thorough understanding of the-state-of-the-art, addressing significant limitations of previous review articles, highlighting the key differences between images and GIS vector maps, and giving recommendations for future research directions the research community should address.
The rest of the paper is organized as described in the following. The next section gives an overview and critical appraisal of previous review papers in the field of vector maps watermarking. Section 3 explains the methodology used for collecting the research articles that have been reviewed in this paper. Section 4 describes GIS vector data models, entities and formats. Section 5 classifies existing GIS watermarking methods and gives an overview of the distribution of published papers according to the categories of this classification. Section 6 discusses the limitations in the current approaches and outlines directions for future GIS watermarking research. Finally, Section 7 concludes this paper.
2 Previous reviews
A number of reviews were previously published in the area of digital map watermarking research. These reviews are discussed in the following.Footnote 2 Table 1 gives a summary of the review papers, including the number of references used and the period of time they covered.
In 2002, Lopez [90] presented a review article with 43 references covering work published until 2000 to analyze the state-of-the-art of digital watermarking research including images, vector, text and databases data formats. He highlighted some key differences between the watermarking research and other research work such as cryptography and steganography. He also reported some legal aspects in watermarking research for the United States and Europe regions.
In 2003, Chang et al. [19] reviewed digital image watermarking research by utilizing 26 references published until 2002 to highlight possible ways of extending some image watermarking techniques to the context of 2D/3D vector map watermarking research.
In 2006, Niu et al. [110], used 28 references published until 2004 to distinguish the features of vector map data from raster/ image data.
In 2007, Niu et al.[111] used 23 references published until 2004 to outline some key features of GIS vector maps, reviewed the state-of-the-art of the vector map watermarking research and classified this research into three sub-research areas: robust watermarking, reversible data hiding and fragile watermarking.
In 2008, Li et al. [77] used 23 references published until 2006 to summarize the status and prospects of watermarking research in GIS vector maps in terms of the basic concept, watermark generation, real-time detection and embedding strategies.
In 2009, Zheng et al. [205] used 30 references published until 2007 to classify digital map copyright protection schemes, and to propose some directions for further research. This review covered only the watermark embedding process.
In 2010, Zheng et al. [206] used 31 references published until 2007 and discussed some types of embedding techniques in the context of vector graphics. They highlighted some merits and drawbacks of a given set of image-based techniques with the purpose of suggesting some adaptations of these techniques for the vector map watermarking research context.
In 2013, two review articles are found in the literature. The first one [1] used 26 references published until 2012 to review a set of digital vector map watermarking techniques, and to define some possible attacks for removing the embedded watermark. The second review [178] used 27 references published until 2012 to classify the map watermarking components into two modules: embedding location selection module and integrity decision module. Neither of the two reviews covered the entire watermarking process.
Although all previous review articles paid attention to either differentiating vector map data from raster image data or adapting some image-based watermarking techniques to the context of GIS vector maps, nevertheless, they suffer from two major drawbacks: (a) they do not cover the entire watermarking process and (b) they do not outline their search method, nor give an indication of their coverage in relation to the total number of published articles.
The watermarking system is composed of three main components: embedding, evaluation and extraction. A comprehensive overview of our current knowledge of the digital map watermarking research progress can only be obtained by reviewing all three components of the process. In addition, without a documented search method used for the selection of the articles to review, we cannot be confident about the coverage and relevance of the reviewed research.
In this survey, we attempt to address these two major drawbacks of the current surveys by considering the three components of the watermarking system, and providing details of the methodology used for selecting the articles included in this review work. This survey article covers 215 articles published between 2000 and 2014, thus being more comprehensive than any of the previous surveys on the subject.
3 Search methodology
The search for relevant publications was performed using the following electronic libraries and databases: (i) Springer Digital Library, (ii) IEEE Xplore Digital Library, (iii) ACM digital library, (iv) Google Scholar, and (v) Elsevier Digital Library.
The search was limited to articles that have been published in English in the period between 1 January 2000 and 31 December 2014. It was done using a Boolean search containing the following terms: “GIS watermark” OR “zero watermark” OR “2D map watermark” OR “copyright protection” OR “vector data” OR “geospatial watermark” OR “vector data” OR “graph watermarking”.
Initially, any article containing the search terms was considered as a potential candidate for including into the database of the GIS map watermarking publications. To supplement the automated search, a manual search was also done. The manual procedure involved searching the reference sections of the papers identified by the automated search. Any relevant references within those articles were followed up. Inclusion criteria for the review were any theoretical or applied work concerning an integration of the GIS vector data and watermarking/ copyright protection methods.
A number of papers were identified in the search as title-only papers without access to the full text [12, 57, 99, 136, 202, 218]. These were included in the count of published papers, but were not included in the classifications discussed in Section 5.
Through the search methodology described above, 215 papers were identified. Figure 2 presents the distribution of these papers by year, indicating a trend of growth in the number of publications.
Publications in watermarking from 2000 to 2014
4 GIS vector data structure
Geographic information systems (GIS) are computer-based systems that facilitate the input, storage, manipulation and output of geographic location-based data. GIS data models are classified into two categories: raster and vector data models. In GIS context, satellite images are the most known example of the raster model. GIS vector data, which is the focus on this paper, has three components: spatial data, attribute data and index data. Spatial data describes the map itself and always takes the form of three basic geometrical entities, which are:
-
Points – point entities are used to define a single location of an object; they are used to represent real-world objects, such as bus stops, traffic lights and street lights.
-
Polylines – line entities define linear objects; they can range from two-point lines to complex strings that have many vertices; lines are used to represent real-world objects, such as rivers and roads.
-
Polygons – polygon entities define area-based objects; they can range from rectangles to multi-sided shapes with many vertices; polygons are used to represent real-world objects, such as lakes, shopping areas, buildings and city boundaries.
All these map entities are formed by many organized vertices; spatial data is actually a sequence of coordinates of these vertices based on a certain geographical coordinate system. The most used formats of GIS spatial data are:
-
1.
ESRI (Environmental Systems Research Institute) shape file. The ESRI shape file [31] has become an industry standard in geospatial data format due to its compatibility, to some extent, with recently released GIS software products.
-
2.
CAD (Computer Aided Design) drawing. CAD drawings are used in many disciplines such as engineering, architecture, surveying, and mapping to define real-world objects in the context of geographic information systems. DXF (Drawing Interchange File) [5] files are a popular format for storing and exchanging vector-based spatial information.
The attribute data describes the properties of map entities through links to the location data. Attributes can be, for example, names or matching addresses. The most known example of GIS attribute data format is the ESRI database file that is associated with the ESRI shape file and needs to have the same prefix as the shape file [31].
Last but not least, in the GIS context, the index data describes a file structure, such as total file length, for either spatial or attribute data. The ESRI index file [31] is the best known example of index files.
The distinguishable structure of vector data from image data adds more challenges to be taken into account in the research field of digital watermarking. Table 2 outlines the major differences between vector data and image data in the context of digital watermarking applications [84, 89, 111, 169].
The main challenges for watermarking vector map data are related to the embedding locations and the evaluation of the watermarking approach. Selecting embedding locations is a crucial issue in the watermarking field because of the small redundancy to hide the watermark due to the need to preserve the coordinates precision of points/vertices. The evaluation of the watermarking approach includes several challenges, such as the preservation of map quality and the robustness to attacks, which will be discussed in detail in Section 5.2.
5 Digital map copyright protection algorithms
Digital map copyright protection schemes are composed of three main modules: embedding, evaluation and extraction. Before describing in detail each of these modules, an overview of different terms used for different watermarking approaches is given in Table 3. Not all the reviewed papers explicitly stated which of these approaches they used - the table includes only the publications that explicitly stated their approach.
5.1 Watermark embedding module
The embedding module involves hiding the watermark bits inside the original map content without affecting the visual quality of the host map. The secret key (see Fig. 1 in Section 1) should be used to enforce security and to prevent unauthorized parties from recovering and manipulating the watermark. This module involves both the embedding domains and the embedding strategies, which are discussed in the following subsections.
According to the embedding domain, a digital watermark can be embedded into two domains: space and transform domains. In the space domain, the watermark is embedded directly by modifying the values of vertices coordinates. In the transform domain, the watermark data is embedded not by directly modifying the coordinates of the vertices, but their transform coefficients instead. Space and transform domains are discussed in Sections 5.1.1 and 5.1.2, respectively.
5.1.1 Space-domain approaches
Space-domain watermarking approaches are applied to shift map’s vertices within a predefined tolerance, and to embed the watermark based on different embedding strategies (see the next subsection). As shown in Fig. 3, the embedding space could be represented by polar coordinates, blocks, topological relations or Cartesian coordinates. Table 4 shows the distribution of the published articles according to the different embedding spaces.
The classification of space-domain approaches
As shown in Table 4, the most popular approaches are the topological relations (35.5 %) and the Cartesian coordinates (40 %); 17.25 % of the papers use blocks, while the least popular approach is the use of polar coordinates or angles (7.25 %).
The topological relations embedding approaches refer to the process of inserting the watermark into map topologies instead of vertices’ coordinates values (e.g. distance between the map vertices) to gain the advantage of preserving GIS data quality against rotation and translation attacks [48, 181]; details about these and other attacks are given in Section 5.2.2. Mean/ average distance length is the best known research example of topological relations embedding space, e.g. [4, 48, 181].
The Cartesian coordinates embedding approaches use directly the vertices’ coordinates values for inserting the watermark [203]. Most of these approaches utilize a specified digit place after the decimal point in the vertex coordinate value for adding the watermark bits, also defined as additive watermarking [62] and related to the Least Significant Bit embedding strategy (see the next subsection).
The blocks-based embedding approaches divide the vector map into a number of parts (blocks) which help in achieving more robustness against noise and simplification attacks [111]. These approaches can maintain the fidelity of the watermarked vector map to some extent, and relatively locate the watermark bits in a certain block [204].
The polar coordinates embedding approaches involve the use of another form of vertices’ coordinates values for directly embedding the watermark. These approaches like Cartesian coordinates-based approaches achieve good robustness to attacks such as translation, rotation and equal scaling [102, 174].
The advantages of space-domain schemes are: (a) simplicity ; (b) low computational complexity; (c) potential for high capacity of the watermark (i.e. the size of the watermark). The main disadvantage of space-domain schemes is the vulnerability to certain attack, i.e. low robustness.
5.1.2 Transform-domain approaches
Unlike the space domain, in the transform-domain embedding schemes the watermark is not embedded by modifying the coordinates of the vertices, but their transform coefficients. As shown in Fig. 4, the most frequent types of transforms are: wavelet transform (WT), Fourier transform (FT) and cosine transform (CT). Table 5 shows the distribution of the published papers according to the transform domain.
The classification of transform-domain approaches
WT is a kind of transform that analyzes the digital vector map into different bands and levels. The wavelet-based method is robust against noise, rotation and scaling [75].
FT is a digital transform that offers the possibility of controlling the frequencies of the host vector map, which helps in selecting the adequate positions for embedding the watermark bits into the vector map to meet the best compromise between invisibility and robustness. The main advantage of FT is its invariance property against some geometric attacks like translation, scaling and rotation [56, 91].
CT is another digital transform that separate the vector map into parts of different frequency with respect to the vector map visual quality. The basic characteristic of CT is the high concentration of energy in low frequency coefficients with relative low computational cost [98, 191].
As shown in Table 5, the WT approach is the most popular approach used in 41 % of the papers. CT is the second most popular at 36 %, while FT is the least popular with 23 % of papers reporting the use of this approach.
Transform-domain approaches are robust against geometric attacks such as rotation, translation and scaling; however, they have the disadvantages of being hard to implement and of having high computational complexity.
5.1.3 Embedding strategies
There are a variety of strategies that have been used for the embedding process. These strategies are: significant bits, difference expansion, and quantization modulation. Table 6 lists the published papers according to the use of embedding strategies.
The significant bits embedding strategy refers to the process of selecting appropriate digits within the vertex coordinate value for inserting the watermark bit. This approach represents 43 % of the published papers, and can be used in two different ways: least significant bits (LSB) (30 %) or most significant bits (13 %) (MSB).
LSB deals with the digits after the decimal point, and can be a useful hiding strategy in terms of: simplicity, invisibility, low computational time and allowing a large amount of watermark bits. LSB, however, is vulnerable to geometric distortion. LSB is mostly used in space-domain schemes with the exemption of the proposed scheme of [84] that used a LSB strategy in the wavelet transform-domain.
Some existing schemes used the MSB strategy that deals with the digits before the decimal point to control the modification of vertices’ coordinate according to the precision tolerance. More precisely, this approach should meet two conditions: small modifications of the coordinates should not change the shape, and two adjacent shapes should not share the same identifier.
Difference expansion is a method for inserting the watermark into any kind of high correlation data [162]. Digital vector maps consist of a sequence of the coordinates of the vertices. Due to the density of the vertices, the positions of two adjacent vertices are usually very close and the differences between their coordinates are very small. Consequently, the sequence of vertices’ coordinates can also be considered high correlation data [83]. Since higher correlation means lower distortions and higher capacity, the difference between two adjacent vertices is used as embedding space [111].
The quantization modulation strategy is a nonlinear method used to hide the watermark and scale some map objects to derive the watermarked data [68]. This embedding strategy offers a good performance in balancing the trade-off between watermark fidelity, robustness and capacity [36]. An example of using the quantization modulation method is the watermark embedding according to odd-even index of map coordinates or topological relations [48, 119, 167].
5.2 Watermarking evaluation module
The evaluation module assesses the quality of the watermarking approach by measuring several aspects: (a) the quality of the map after the insertion of the watermark (fidelity); (b) the resistance of the watermarked map to attacks (robustness); (c) the coverage of the watermark (capacity); (d) the computational complexity of the approach (complexity) and (e) the security of the watermark locations within the map (security). These aspects are discussed in the following subsections.
5.2.1 Fidelity
Fidelity is defined as the relative similarity between the non-watermarked host object and the one after the watermarking operation [3] and refers to the perceptual similarity between the watermarked data and its original data [106]. The fidelity issue is a crucial problem in the digital maps watermarking research, as the watermarked maps need to preserve their quality.
Several metrics has been proposed in the literature, as shown in Table 7. Such metrics are: Root Mean Square Error (RMSE), Peak Signal to Noise Ratio (PSNR) (based on RMSE), Bit Error Rate (BER), Normalized Correlation (NC), Correspondence Ratio (CR) and Likelihood Ratio (LR), as well as Horizontal and vertical shift (HV shift).
The use of RMSE metric represents 48 % of the published research, while the PSNR metric is used in 20 % of the published research. 12 % of the research approaches use the BER metric, and 8 % use the NC metric. The least popular metrics in the published literature are CR (7 %), LR (3 %) and HV shift (2 %).
Most of these metrics are borrowed from image watermarking and are based on theories of signal processing. These are not necessarily the most appropriate metrics for measuring the quality of the watermarked map, as discussed in Section 6.
5.2.2 Robustness
Robustness is the resilience of the inserted watermark to any processes (attacks) aimed at either removing or distorting it [3, 87]. Regarding the robustness requirements, watermarking schemes can be categorized into three categories: robust, fragile and semi-fragile schemes, as shown in Table 8.
The digital watermark is robust if it withstands a designated manipulation on the vector map data [3, 177, 181]. Fragile watermarking allows the detection of any tampering with the vector map data [158, 159]; however, any small change in the watermark would make it undetectable. This approach has a wide range of applications such as authentication and integrity protection of the vector maps [204, 205]. Semi-fragile schemes allow the detection of malicious tampering with the vector map data [36, 118, 191]; in these schemes, the watermark is still detectable after non-malicious transformations, however, it is not detectable after malicious attacks.
A successful attack refers to the success in removing the embedded watermark while preserving the validity of the vector map data [111]. In literature, the attacks can be classified in two categories: (a) geometric attacks [30, 170, 181], and (b) signal operation attacks [158, 169].
The most known geometric attacks are rotation, translation, scaling and cropping – see Table 9. Rotation means turning the vector map around its center by a specific angle [72]. Translation means moving the whole map by a specific distance towards a specific direction [181]. Scaling refers to altering the size of the map, in both axes by a specific value [72]. Cropping refers to the process of cutting some parts of the map. For vector maps, such attacks are virtually reversible transformations of coordinates where almost little or no information would be lost [111].
Signal operation attacks can be simplification, interpolation and reordering operations, or noise addition [158, 169] – see Table 10. Simplification, also known as Douglas compression, is the process of removing some vertices. This is often used to enhance the speed of handling the vector map data [111]. Interpolation is the process of adding new vertices into a digital vector map [111]. The reordering operation involves changing the order of entities (i.e. points, polylines and polygons) in the map. This could be implemented by changing the order of points within a polyline/ polygon, or by changing the order of polylines/ polygons [111]. Noise addition is used intentionally by the attacker to destroy the embedded watermark. Noise can also be added unintentionally by converting the map file into different formats [1].
The resilience to both geometric and operational attacks is measured by comparing the extracted watermark with the original watermark by using the metrics that are shown in Table 11. These are different from the fidelity metrics, which compare the watermarked map with the original map. Thus, although the same metric could be used for both purposes, the robustness metrics focus on the watermark, while the fidelity ones focus on the map.
Many researchers use the same metrics for measuring both the robustness and the fidelity, as it can be seen by the overlap between Tables 7 and 11, i.e. all metrics from Table 11 are also in Table 7 and several papers are in both tables, thus indicating that the same metric is used for the two different purposes.
From the robustness metrics, the use of the NC metric represents 47 % of the published research. 27 % of the published research are approaches that use the BER metric, while the use of PSNR metric is represented by 13 % of the published research. The least popular metrics in the published literature are CR (8 %) and RMSE (5 %).
5.2.3 Capacity, complexity and security
The watermark capacity refers to the amount of embedded bits within the digital vector map [3, 17], or the total number of vertices that carry the watermark bits [4, 53, 98]. Computational complexity refers to a specific formula for measuring the embedding algorithm complexity [126]. In other words, it stands for measuring the required time for implementing the watermark embedding approach [4, 25]. The security of a watermarking technique is defined as the level of unpredictability in identifying the watermark bits positions that are used to perform the watermark embedding process. A highly secure watermarking process would produce an output that does not contain any specific signatures that can be used to identify the watermark bits positions [3]. The secure watermarking approach should have a secret key for the embedded bits locations in the vector map vertices, to make it more difficult for an attacker to trace the distribution of the embedded watermark bits [103].
Table 12 lists the published papers that discussed these aspects in their evaluation.
5.3 Watermark extraction module
The extraction module is important for data ownership verification. It is a very complicated task because of two main factors: (a) the wide variety of possible attacks that could take place before extraction (details on attacks are given in Section 5.2.2), and (b) the (un)availability of the original map. According to the second factor, the watermarking approaches can be classified into three main categories: blind, semi-blind and non-blind approaches [87]. Table 13 lists the published papers according to these categories.
Blind/public approaches mean that the original map is not needed in the watermark extraction process, and this category represents 86 % of published work. Semi-blind approaches refer to those approaches that do not use the original map, but use the original watermark in the watermark extraction process, and represent 3.5 % of published work. Non-blind/private approaches mean that the original host data is needed in the watermark extraction process, and represent 10.5 % of published work.
6 Overview and directions for future work
In this paper we reviewed the state-of-the-art of GIS vector maps copyright protection, with a focus on watermarking as the most popular approach to mark the copyright of GIS vector maps. The relevant work in this area has been organised according to the three modules of watermarking systems: embedding, evaluation and extraction. In the following, for each of these a brief overview is given and directions for future work are outlined.
6.1 The embedding module
The embedding module involves hiding the watermark inside the original map. The embedding can be done through a space-domain or a transform-domain scheme. The advantages of space-domain schemes are: (a) simplicity ; (b) low computational complexity; (c) potential for high capacity of the watermark (i.e. the size of the watermark). The main disadvantage of space-domain schemes is the vulnerability to certain attack, i.e. low robustness. While transform-domain schemes are robust against geometric attacks such as rotation, translation and scaling, they have the disadvantages of being hard to implement and of having high computational complexity. In the transform-domain, the capacity aspect can be less controlled compared with the space-domain, making it difficult to experiment with different levels of capacity and observe their influence on other aspects such as fidelity and robustness.
Several aspects related to the embedding module need to be addressed by the research community: (a) which attacks are relevant for vector data to satisfy the robustness of the watermarked map? (b) the trade-off between capacity and fidelity, and their implications when choosing embedding locations. These are tightly related to the evaluation module and are discussed below because they have an influence on the choice of embedding locations.
Several types of attacks can distort the watermarked map by distorting either the watermark (which would prevent the establishment of the rightful owner) or of the map (which would prevent it from being useful). There are two broad categories of attacks: geometric and signal operations attacks. The transformations done through geometrics attacks (e.g. rotation, translation) can be easily reversed on vector data with minimal data loss, which has already been pointed out [110]. Consequently, the focus should be on the signal operations attacks (e.g. simplification, noise addition, interpolation). To allow a fair comparison between different approaches proposed for watermarking GIS vector data, a common framework for reporting the robustness to these types of attacks should be developed.
Capacity and fidelity are two important metrics in the evaluation of the watermarking approach. The capacity is about the coverage of the watermark, and is thus, related to robustness, while fidelity is about the quality of the map after inserting the watermark. These two metrics need to be balanced, as the higher the capacity, the higher the noise introduced in the map, which means lower fidelity. Low fidelity means that the watermarked map is not usable because some of the properties of the map are lost, especially with regards to the precision of points/vertices. The precision in vector data is one of the aspects that makes the vector maps most valuable, especially for applications where precision is key, such as military operations. Consequently, the balance between these two metrics is very important and should be reported in watermarking research on vector map data.
6.2 The evaluation module
The evaluation module is the most challenging module in GIS map watermarking research due to the lack of appropriate metrics to define the quality of the watermarking approach. This module involves the use of metrics for judging the quality aspects of the given approach.
The current research on GIS map watermarking suffers from the lack of appropriate metrics, and it is mainly focused on the error analysis quality aspect that has been borrowed from the research on image watermarking. Huang et al. [44] outline the need for considering some topological aspects in addition to the error analysis. However, the problem of measuring the quality of the GIS map watermarking approach has not been addressed yet, except for the introduction of a metric that checks for unwanted intersections between lines introduced by the watermark, which is referred to as the intersection test [63, 64].
The topological aspects are important for vector map data because the insertion of the watermark or some attacks may introduce changes in the shapes of the map (distortions), which may violate the constraints of the vector format, such as overlaps between polygons and gaps between polygons. An error metric can only measure the difference between the original map and the watermarked map in terms of the “noise” introduced by the watermark, without an indication of the presence of distortions. In fact, a watermarking approach with a higher error but little distortion is more useful that a watermarking approach with low error and large distortion. Consequently, a metric that indicates the level of distortion is needed.
As pointed out previously, some of the metrics used to measure fidelity are also used to measure the robustness of the watermark to attacks. As the watermark does not have the topological properties of the vector data, the metrics borrowed from image watermarking are suitable for this purpose.
Furthermore, as pointed out previously when discussing the embedding aspect, there is a demand for defining a specific set of attacks in order to address the robustness issue. Two examples of operations that could be used for this purpose are: (a) merging two adjacent polygons into one polygon and (b) cutting a polygon by another polygon neighbour.
Another issue tightly related to the evaluation module is that there is no benchmark data that could help the researchers to reliably compare different approaches without the need to re-implement them for this purpose.
This issue can be addressed within the GIS map watermarking research community by using free map data that is available on the Internet. For instance, some map data are freely available from the Map LibraryFootnote 3 and DIVA-GISFootnote 4 websites.
6.3 The extraction module
In relation to the extraction module, most of the current approaches seek the blind-based extraction especially for the application of copyright protection, where the original map is not available at the detector side. This is in line with the applicability of these approaches and the need for obtaining the original map in an easy way.
6.4 Milestones for future work
Although there are significant issues to be addressed for the field of vector map watermarking, we can learn from other communities by focusing on the most important aspects that would advance the field. For example, the audio watermarking research community started with benchmark datasets and developed appropriate metrics that enables comparison between different approaches [23, 155].
To advance the field of vector map watermarking, as a research community, we recommend addressing the following aspects:
-
1.
use of freely available datasets; this would enable replication of research and reliable comparisons between different approaches;
-
2.
development of appropriate metrics for judging map quality, as well as reporting results on both capacity and fidelity;
-
3.
definition of relevant attacks and reporting robustness metrics for each of the relevant attacks.
These would enable comparisons between different approaches, which, in turn, would allow the emergence of promising techniques that can then be further refined. In this way, the research community would be able to judge the potential of different approaches and build on each other’s work, in a unified effort to advance the field.
7 Conclusions
This paper is a review of the state-of-the-art with respect to GIS vector map watermarking; it covers the most relevant work in this area from 2000 to 2014. The distinct features of GIS map data compared with other general multimedia data were highlighted and discussed in terms of their implication for watermarking approaches.
The published papers were classified according to the three main components of watermarking systems, i.e. embedding, evaluation and extraction. Within the embedding module, the different approaches were classified according to embedding domains (space and transform) and embedding strategies. Within the evaluation module, the papers were classified according to the different metrics used for measuring fidelity and robustness. In addition, papers were classified according to weather they looked into other important aspects such as capacity, security and complexity. With respects to the extraction module, the papers were classified in accordance with the use of one of three possible approaches: blind, semi-blind and non-blind watermarking.
Finally, the paper discussed several directions for further advancing this field of research and enabling a more robust evaluation of watermarking approaches by: (a) the use of freely available benchmark datasets; (b) defining appropriate metrics for map quality and reporting metrics of both capacity and fidelity; and (c) defining a set of relevant attacks to be used consistently when reporting robustness metrics.
Notes
References
Abbas TA, Jawad MJ (2013) Digital vector map watermarking: applications, techniques and attacks Oriental. J Comput Sci Technol 6(3):333–339
Abbas TA, Jawad MJ (2013) Proposed an intelligent watermarking in gis environment. J Earth Sci Res 1(1):1–5
Abbas T, Jawad M, Sudirman S (2013) Robust watermarking of digital vector maps for copyright protection. In: 14th annual postgraduate symposium on the convergence of telecommunications, networking and broadcasting. 978-1-902560-27-4. Liverpool
Abubahia A, Cocea M (2014) Partition clustering for gis map data protection. In: IEEE 26th international conference on tools with artificial intelligence, pp 830–837
AutoCAD (2007) Dxf reference. Tech. rep., Autodesk
Aybet J, Al-Saedy H, Farmer M (2009) Watermarking spatial data in geographic information systems. In: Jahankhani H, Hessami A, Hsu F (eds) Global security, safety, and sustainability, communications in computer and information science, vol 45. Springer, Berlin Heidelberg, pp 18–26
Baiyan W, Wei W, Dandan M (2008) 2d vector map watermarking based on spatial relations. SPIE 7285:32–37
Bazin C, Le Bars JM, Madelaine J (2007) A blind, fast and robust method for geographical data watermarking. In: 2nd ACM symposium on information, computer and communications security, pp 265–272
Bhanuchandar P, Prasad M, Srinivas K (2013) A survey on various watermarking methods for gis vector data. Int J Comput Electron Res 2(3)
Bird S, Bellman C, Van Schyndel R (2009) A shape-based vector watermark for digital mapping. In: The conference on digital image computing: techniques and applications, pp 454–461
Bisher M, Wytzisk A, Morales J (2007) Geodrm: Towards digital management of intellectual property rights for spatial data infrastructures. Research and theory in advancing spatial data infrastructure concepts, pp 245–260
Calagna M, Mancini L (2007) Information hiding for spatial and geographical data. In: Belussi A, Catania B, Clementini E, Ferrari E (eds) Spatial Data on the Web. Springer, Berlin, pp 235–258
Cao J, Li A, Lv G (2010) Study on multiple watermarking scheme for gis vector data. In: 18th international conference on geoinformatics, pp 1–6
Cao L, Men C, Li X (2010) Iterative embedding-based reversible watermarking for 2d-vector maps. In: 17th IEEE international conference on image processing, pp 3685–3688
Cao L, Men C, Sun J (2011) A double zero-watermarking algorithm for 2d vector maps. J Harbin Eng Univ 340–344
Cao L, Men C, Ji R (2013) Nonlinear scrambling-based reversible watermarking for 2d-vector maps. Vis Comput 29(3):231–237
Cao L, Men C, Gao Y (2013) A recursive embedding algorithm towards lossless 2d vector map watermarking. Digital Signal Process 23(3):912–918
Cao L, Men C, Ji R (2014) High-capacity reversible watermarking scheme of 2d-vector data. SIViP:1–8
Chang HH, Chen T, Kan KS (2003) Watermarking 2d/3d graphics for copyright protection. In: IEEE international conference on acoustics, speech, and signal processing, vol 4, pp 720–723
Che S, Deng SJ (2008) Watermarking arithmetic of 2d vector maps based on two-tier grids. Hydrographic surveying and charting, p 1
Cheng FJ, Yin H, Zhang XP, Zhang DX (2010) A digital watermarking algorithm for vector map. In: International conference on challenges in environmental science and computer engineering, vol 2, pp 101–103
Chuanjian W, Bin L, Qingzhan Z, Zuqi Q, Yuwei P, Liang Y (2009) A 2d vector map watermarking algorithm resistant to simplication attack. SPIE 7651:4–8
Craver S, Wu M, Liu B, Stubblefield A, Swartzlander B, Wallach DS, Dean D, Felten EW (2001) Reading between the lines: lessons from the sdmi challenge. In: USENIX security symposium
Cui H, Zhu C, Ren N, Wang D (2013) A multiple watermarking algorithm for vector geographic data based on watermarking information segmentation. J Geom Sci Technol 2
Dakroury Y, El-ghafar IA, Tammam A (2010) Protecting gis data using cryptography and digital watermarking. Int J Comput Sci Netw Secur 10(1):75–84
Davydov A, Kovalev A, Izyurov K (2011) Distortion measure of watermarking 2d vector maps in the mesh-spectral domain. In: 17th International Conference on Digital Signal Processing (DSP), 2011, pp 1–6
Deng LP, Xiao H (2010) A lossless watermarking algorithm for vector graphics based on wavelet transform. Comput Knowl Technol 4
Dollner J (2005) Geospatial digital rights management in geovisualization. Cartogr J 42(1):2734
Doncel V, Nikolaidis N, Pitas I (2007) An optimal detector structure for the fourier descriptors domain watermarking of 2d vector graphics. IEEE Trans Vis Comput Graph 13(5):851–863
Du Q, Peng F (2008) A zero-watermark algorithm with real-mean for 2d engineering graphic. In: International symposium on electronic commerce and security, pp 890–893
ESRI (1998) Esri shapefile technical description. Tech. rep., Environmental Systems Research Institute, USA
Fei P, Li C, Min L (2013) A reversible watermark scheme for 2d vector map based on reversible contrast mapping. Secur Commun Netw 6(9):1117–1125
Fu H, Zhu C, Yuan J, Xu H (2013) A new watermarking algorithm for geo-spatial data. In: Lu W, Cai G, Liu W, Xing W (eds) The international conference on information technology and software engineering, LNEE, vol 210. Springer, Berlin, pp 945–951
Geng M, Yu P, Han H, Teng Z, Hu J, Gao Y (2012) Reversible watermarking based on invariant sum value for 2d vector maps. In: 3rd IEEE international conference on network infrastructure and digital content, pp 521–525
Giannoula A, Nikolaidis N, Pitas I (2002) Watermarking of sets of polygonal lines using fusion techniques. In: IEEE international conference on multimedia and expo, vol 2, pp 549–552
Guo RS, Peng F (2010) Semi-fragile watermarking algorithm for 2d engineering graphics based on improved odd-even quantization. J Chin Comput Syst 2096–2100
Haowen Y (2011) Watermarking algorithm for vector point clusters. In: 7th international conference on wireless communications, networking and mobile computing, pp 1–4
He X, Zhu C, Wang Q (2009) The blind watermarking model of the vector geospatial data based on dft of qim. In: IEEE international conference on network infrastructure and digital content, pp 1039– 1044
Horness E, Nikolaidis N, Pitas I (2007) Blind city maps watermarking utilizing road width information. In: 15th European signal processing conference, Poland, pp 2291–2295
Hou H, Li J, Qi J, Guo J (2014) A blind watermarking for 2d-vector engineering graphics. Inf Technol J 869–873
Hu J, Geng M (2013) A reversible watermarking algorithm for 2d vector maps. In: 2nd international symposium on instrumentation and measurement, sensor network and automation, pp 1101–1104
Huan Y, Yufeng G (2009) A digital watermarking algorithm for cad two-dimensional graphics 4
Huang XS, Gu JW (2006) A non-blind detection watermarking algorithm for 2-dimensional engineering drawings. J Eng Graph 158–161
Huang L, Zhou W, Jiang R, Li A (2010) Data quality inspection of watermarked gis vector map. In: 18th international conference on geoinformatics, pp 1–5
Huber S, Kwitt R, Meerwald P, Held M, Uhl A (2010) Watermarking of 2d vector graphics with distortion constraint. In: IEEE international conference on multimedia and expo, pp 480– 485
Huo XJ, Seung TY, Jang BJ, Lee SH, Kwon SG (2010) A watermarking scheme using polyline and polygon characteristic of shapefile. In: 3rd international conference on intelligent networks and intelligent systems, pp 649–652
Huo XJ, Lee SH, Kwon SG, Moon KS, Kwon KR (2011) A watermarking scheme for shapefile-based gis digital map using polyline perimeter distribution. J Korea Multimeadia Soc 14(5):595– 606
Huo XJ, Moon KS, Lee SH, Seung TY, Kwon SG (2011) Protecting gis vector map using the k-means clustering algorithm and odd-even coding. In: 17th Korea-Japan joint workshop on frontiers of computer vision, pp 1–5
Im DH, Lee HY, Ryu SJ, Lee HK (2008) Vector watermarking robust to both global and local geometrical distortions. IEEE Signal Process Lett 15:789–792
Jia P, Chen Y, Ma J, Zhu D (2006) Digital watermark-based security technology for geo-spatial graphics data. Chin Geogr Sci 16(3):276–281
Jian-Guo S, Guo-Yin Z, Ai-Hong Y, Jun-Peng W (2014) A reversible digital watermarking algorithm for vector maps. Int J Netw Secur 16(1):40–45
Jiang K, Zhu KQ, Huang Y, Ma X (2013) Watermarking road maps against crop and merge attacks. In: 1st ACM workshop on information hiding and multimedia security, IHMMSec ’13, New York, pp 221–230
Jianguo S, Songzhu X, Guoyin Z (2012) Vector map watermarking evaluation based on certainty factor. J Theor Appl Inf Technol 46(1):67–72
Jianguo S, Liang K, Songzhu X (2013) Research of lossless digital watermarking technology. Appl Mech Mater 333:1219–1223
Jianguo S, Chonghui Z, Di G (2014) Lossless digital watermarking scheme for image maps. Commun China 11(8):125–130
Junfeng Z, Bing X (2011) Research on digital watermarking algorithms for 2d graphics. In: IEEE 3rd international conference on communication software and networks, pp 179–183
Kan YH, Yang CS, Cui HC, Wang YY, Liu R (2010) High-fidelity digital watermarking algorithm for vector geospatial data. J Geom Sci Technol 2
Kang JJ, Zhang HL (2009) Blind watermarking algorithm for 2d engineering graphics based on fractional fourier transform. J Comput Appl 1648–1650
Kang H, Kim K, Choi J (2001) A vector watermarking using the generalized square mask. In: International conference on information technology: coding and computing, pp 234–236
Kang HI, Kim KI, Choi JU (2001) A map data watermarking using the generalized square mask. In: IEEE international symposium on industrial electronics, vol 3, pp 1956–1958
Kang H, Kim K, Choi J (2002) Map data watermarking using generalised square mask. Electron Lett 38:1645–1646
Katzenbeisser S, Petitcolas F (2000) Information hiding techniques for steganography and digital watermarking. Computer Security Series. Artech House
Kim J (2010) Robust vector digital watermarking using angles and a random table. Adv Inf Sci Serv Sci 2(4):79–90
Kim J (2010) Vector map digital watermarking using angles. In: 6th international conference on networked computing and advanced information management, pp 417–423
Kim J, Hong S (2009) Development of digital watermarking technology to protect cadastral map information. In: 2nd international conference on interaction sciences: information technology, culture and human, pp 923–929
Kim J, Won S, Zeng W, Park S (2011) Copyright protection of vector map using digital watermarking in the spatial domain. In: 7th international conference on digital content, multimedia technology and its applications, pp 154–159
Kitamura I, Kanai S, Kishinami T (2001) Copyright protection of vector map using digital watermarking method based on discrete fourier transform. In: International symposium on geoscience and remote sensing, vol 3, pp 1191–1193
Lafaye J, Béguec J, Gross-Amblard D, Ruas A (2007) Geographical database watermarking by polygon elongation. Tech. rep., HAL
Lafaye J, Béguec J, Gross-Amblard D, Ruas A (2007) Invisible graffiti on your buildings: Blind and squaring-proof watermarking of geographical databases. In: Papadias D, Zhang D, Kollios G (eds) Advances in spatial and temporal databases, LNCS, vol 4605. Springer, Berlin, pp 312– 329
Lafaye J, Béguec J, Gross-Amblard D, Ruas A (2012) Blind and squaring-resistant watermarking of vectorial building layers. GeoInformatica 16 (2):245–279
Lee SH, Kwon KR (2010) Cad drawing watermarking scheme. Digital Signal Process 20(5):1379–1399
Lee SH, Kwon KR (2013) Vector watermarking scheme for gis vector map management. Multimedia Tools Appl 63(3):757–790
Lele W, Wei L, Yinghong D (2013) A good anti-robust algorithm with map watermarking. In: Zhang W (ed) Advanced technology in teaching. Advances in intelligent and soft computing, vol 163. Springer, Berlin, pp 789–794
Lee SH, Hwang WJ, Kwon KR (2014) Polyline curvatures based robust vector data hashing. Multimedia Tools Appl 73(3):1913–1942
Li Y, Xu L (2003) A blind watermarking of vector graphics images. In: 5th international conference on computational intelligence and multimedia applications, pp 424–429
Li Y, Xu L (2004) Vector graphical objects watermarking scheme in wavelet domain. Acta Photon Sin 97–100
Li A, Chen Y, Lin B, Zhou W, Lu G (2008) Review on copyright marking techniques of gis vector data. In: International conference on intelligent information hiding and multimedia signal processing, pp 989–993
Li A, Lin BX, Chen Y, Lu G (2008) Study on copyright authentication of gis vector data based on zero-watermarking. Int Arch Photogramm Remote Sens Spat Inf Sci 37:1783–1786
Li A, Zhou W, Lin B, Chen Y (2008) Copyright protection for gis vector data production. In: Geoinformatics 2008 and joint conference on GIS and built environment: geo-simulation and virtual GIS environments, vol 7143, pp 71,432–71,439
Li A, Lv G, Zhou L, Lin B, Gu Z (2009) Real-time copyright protection for spatial data files. J Geo-Inf Sci 1
Li Q, Min LQ, Wu B, Yang YQ (2010) A practical blind digital watermarking scheme for vector map data. Eng Surv Mapp 4
Li Q, Min LQ, Wang F, Yang YQ, He HZ (2011) A watermarking algorithm of anti douglas compression for vector map data. Sci Surv Mapp 3
Li AB, Li SS, Lv GN (2012) Disguise and reduction methods of gis vector data based on difference expansion principle. Procedia Eng 29:1344–1350
Li SS, Zhou W, Li AB (2012) Image watermark similarity calculation of gis vector data. Procedia Eng 29:1331–1337
Li B, Zhang X, Jiang X, Ai Q (2014) A selective authentication watermarking algorithm for 2d cad engineering drawings based on entity localization. In: Proceedings of the 2014 international conference on innovative design and manufacturing (ICIDM), pp 82–87
Liang B, Rong J, Wang C (2010) A vector maps watermarking algorithm based on dct domain. In: The Canadian geomatics conference and symposium of commission, vol 38
Lin B, Li A (2010) Study on benchmark system for copyright marking algorithms of gis vector data. In: 18th international conference on geoinformatics, pp 1–5
Ling Y, Lin CF, Zhang ZY (2012) A zero-watermarking algorithm for digital map based on dwt domain. In: He X, Hua E, Lin Y, Liu X (eds) Computer, informatics, cybernetics and applications, LNEE, vol 107. Springer, Netherlands, pp 513–521
Longley PA, Goodchild MF, Maguire DJ, Rhind DW (2005) Geographic information systems and science, 2nd edn. Wiley
Lopez C (2002) Watermarking of digital geospatial datasets: a review of technical, legal and copyright issues. Int J Geogr Inf Sci 16(6):589–607
Lucchese C, Vlachos M, Rajan D, Yu P (2010) Rights protection of trajectory datasets with nearest-neighbor preservation. VLDB J 19(4):531–556
Magalhaes K, Dahab R (2009) Sb-rawvec - a semi-blind watermarking method for vector maps. In: IEEE international conference on communications, pp 1–6
Marques D, Magalhaes K, Dahab R (2007) Rawvec: a method for watermarking vector maps. In: VII Brazilian symposium of information security and computer systems
Matheus A (2005) Authorization for digital rights management in the geospatial domain. In: The 5th ACM workshop on digital rights management, pp 55–64
Men CG, Cao LJ, Sun JG (2009) Reversible watermarking for 2d-vector maps based on graph spectral domain. J Harbin Inst Technol 83–87
Men C, Cao L, Li X (2010) Perception-based reversible watermarking for 2d vector maps. SPIE 7744:34–38
Men C, Cao L, Li X, Wang N (2010) Global characteristic-based lossless watermarking for 2d-vector maps. In: International conference on mechatronics and automation, pp 276–281
Men C, Cao L, Sun J (2010) A perception-based reversible watermarking algorithm for 2d-vector maps. Chin High Technol Lett 342–348
Min LQ (2007) The digital watermark of vector geo-data, Bull Surv Mapp 43–46
Min LQ, Li Q, Yang YB, Yu QH (2009) A survey of watermarking techniques for vector map data 2(110162)
Min LQ, Zhu XZ, Li Q (2012) A robust blind watermarking of vector map. In: Zhang T (ed) Instrumentation, measurement, circuits and systems, advances in intelligent and soft computing, vol 127. Springer, Berlin, pp 51–59
Mouhamed M, Rashad AM, ella Hassanien A (2012) Blind 2d vector data watermarking approach using random table and polar coordinates. In: 2nd international conference on uncertainty reasoning and knowledge engineering, pp 67–70
Murti KCS, Tadimeti VR (2011) A simplified geodrm model for sdi services. In: International ACM conference on communication, computing and security, ICCCS ’11, pp 545–548
Mustafa AS (2011) Copyright protection for gis vector map based on wavelet transform. In: The European conference on information management
Muttoo SK, Kumar V (2012) Watermarking digital vector map using graph theoretic approach. Ann GIS 18(2):135–146
Neyman S, Sitohang B, Cahyono F (2013) An improvement technique of fragile watermarking to assurance the data integrity on vector maps. In: International conference on computer, control, informatics and its applications, pp 179–184
Neyman SN, Sitohang B, Sutisna S (2013) Reversible fragile watermarking based on difference expansion using manhattan distances for 2d vector map. Procedia Technol 11:614–620
Neyman SN, Pradnyana INP, Sitohang B (2014) A new copyright protection for vector map using fft-based watermarking. TELKOMNIKA Telecommunication, Computing. Electron Control 12(2):367–378
Neyman S, Wijaya Y, Sitohang B (2014) A new scheme to hide the data integrity marker on vector maps using a feature-based fragile watermarking algorithm. In: International conference on data and software engineering (ICODSE), 2014, pp 1–6
Niu X, Shao C, Wang X (2006) A survey of digital vector map watermarking. Int J Innov Comput Inf Control 2(6):1301–1316
Niu XM, Shao CY, Wang XT (2007) Gis watermarking: hiding data in 2d vector maps. In: Pan JS, Huang HC, Jain L, Fang WC (eds) Intelligent multimedia data hiding, studies in computational intelligence, vol 58. Springer, Berlin, pp 123–155
Ohbuchi R, Ueda H, Endoh S (2002) Robust watermarking of vector digital maps. In: IEEE international conference on multimedia and expo, vol 1, pp 577–580
Ohbuchi R, Ueda H, Endoh S (2003) Watermarking 2d vector maps in the mesh-spectral domain. In: International conference on shape modeling, pp 216–225
Pan J, Zheng J, Zhao G (2013) Blind watermarking of nurbs curves and surfaces. Comput Aided Des 45(2):144–153
Park K, Kim K, Kang H, Han S (2002) Digital geographical map watermarking using polyline interpolation. In: Chen YC, Chang LW, Hsu CT (eds) Advances in multimedia information processing, LNCS, vol 2532. Springer, Berlin, pp 58–65
Peng YL (2010) Review of digital watermarking for vector digital map. J Xiangnan Univ 2
Peng H, Jianya G, Liang C (2006) An improved adaptive watermarking algorithm for vector digital maps. In: IEEE international conference on geoscience and remote sensing symposium, pp 2844– 2847
Peng F, Guo RS, Li CT, Long M (2010) A semi-fragile watermarking algorithm for authenticating 2d cad engineering graphics based on log-polar transformation. Comput Aided Des 42(12):1207–1216
Peng F, Lei Y, Sun X (2011) Reversible watermarking algorithm in wavelet domain for 2d cad engineering graphics. J Image Graph 7
Peng F, Liu Y, Long M (2014) Reversible watermarking for 2d {CAD} engineering graphics based on improved histogram shifting. Comput Aided Des 49:42–50
Peng Y, Wang C, Fang Y, Li W (2012) Anonymous watermarking protocol for vector spatial data. In: International conference on computer science and service system, pp 2095–2098
Peng Z, Yue M, Wu X, Peng Y (2014) Blind watermarking scheme for polylines in vector geo-spatial data. Multimedia Tools Appl 1–19
Pu YC, Du WC, Jou IC (2006) Toward blind robust watermarking of vector maps. In: 18th international conference on pattern recognition, vol 3, pp 930–933
Pu YC, Jou IC et al (2009) Blind and robust watermarking for street-network vector maps. Inf Technol J 8(7):982–989
Raafat MM, Hossam MZ, Al-Shammari E, Hassanien A, Snasel V (2013) Blind watermark approach for map authentication using support vector machine. In: Awad AI, Hassanien A, Baba K (eds) Advances in security of information and communication networks, vol 381. Springer, Berlin, pp 84–97
Ramaswmay G, Srinivasarao V (2010) A novel approach of cryptography and watermarking using to protect gis data. J Theor Appl Inf Technol 16(2):116–128
Ren N, Sheng Wang Q, Qing Zhu C (2014) Selective authentication algorithm based on semi-fragile watermarking for vector geographical data. In: 22nd international conference on geoinformatics (GeoInformatics), 2014, pp 1–6
Ren N, Zhu CQ, Ren SJ, Zhu YS (2014) A digital watermark algorithm for tile map stored by indexing mechanism. In: Buchroithner M, Prechtel N, Burghardt D (eds) Cartography from pole to pole, lecture notes in geoinformation and cartography. Springer, Berlin Heidelberg, pp 79–86
Sangita ZC, Venkatachalam P (2012) Evaluation of spatial relations in watermarked geospatial data. In: 3rd ACM SIGSPATIAL and international workshop on GeoStreaming, IWGS ’12, New York, pp 78–83
Sangita ZC, Venkatachalam P (2012) Protecting geospatial data using digital watermarking. In: International conference on computer and communication engineering, pp 594–598
Sangita ZC, Venkatachalam P (2012) Robust watermarking for protection of geospatial data. Acad J 29
Sangita ZC, Venkatachalam P (2013) Conceptual framework for geospatial data security. Int J Database Manag Syst 5(5):29–35
Schulz G, Voigt M (2004) A high capacity watermarking system for digital maps. In: The ACM workshop on multimedia and security, pp 180–186
Shao C, Wang H, Niu X, Wang X (2005) Shape-preserving algorithm for watermarking 2-d vector map data. In: IEEE 7th workshop on multimedia signal processing, pp 1–4
Shao CY, Wang HL, Niu X, Wang XT (2006) A shape-preserving method for watermarking 2d vector maps based on statistic detection. IEICE Trans Inf Syst 89-D(3):1290–1293
Shi Xl, Yang Wn (2008) Research on digital watermarking of gis small data layer. Surv Mapp Sichuan 4
Shujun D, liang L, Shujun D, Sen C (2007) Research on a digital watermarking algorithm suitable to vector map. In: IEEE international conference on automation and logistics, pp 1236–1240
Solachidis V, Pitas I (2004) Watermarking polygonal lines using fourier descriptors. IEEE Comput Graph Appl 24(3):44–51
Solachidis V, Nikolaidis N, Pitas I (2000) Fourier descriptors watermarking of vector graphics images. In: International conference on image processing, vol 3, pp 9–12
Solachidis V, Nikolaidis N, Pitas I (2000) Watermarking polygonal lines using fourier descriptors. In: IEEE international conference on acoustics, speech, and signal processing, pp 1955–1958
Sonnet H, Isenberg T, Dittmann J, Strothotte T (2003) Illustration watermarks for vector graphics. In: 11th pacific conference on computer graphics and applications, pp 73–82
Suk-Hwan L, Xiao-Jiao H, Ki-Ryong K (2014) Vector watermarking method for digital map protection using arc length distribution. IEICE Trans Inf Syst 34–42
Sun G, Shen Z, Chen H (2009) Vector polygon blind watermarking based on canonical correlation analysis. In: International conference on multimedia information networking and security, vol 1, pp 544–548
Sun JG, Men CG, Yu LF, Cao LJ (2009) Survey of digital watermarking for the vector maps. Comput Sci 9
Sun JG, Men CG, Cao LJ, Li CM (2010) Digital watermarking of vector maps based on structure features. J Cent South Univ (Science and Technology) 4
Sun JG, Men CG, Ma CG, Cao LJ (2010) Digital watermarking with authentication for vector maps. J Electron Inf Technol 5
Tao S, Dehe X, Chengming L, Jianguo S (2009) Watermarking gis data for digital map copyright protection. In: 24th international cartographic conference
Tian Z, Chen G, Zhang X, Zheng Y, Li G (2004) Digital watermark: technique, application and improvement as a copyright-protecting method for rs and cartographic data. In: MTTS/IEEE TECHNO-OCEAN conference, vol 2, pp 776–780
Tie X, Zou J, Zhong W, Qi D (2007) Watermarking polygonal lines using v-descriptors. In: 2nd international conference on pervasive computing and applications, pp 442–446
Vlachos M, Lucchese C, Rajan D, Yu PS (2008) Ownership protection of shape datasets with geodesic distance preservation. In: 11th international conference on extending database technology: advances in database technology, EDBT ’08, pp 276–286
Voigt M, Busch C (2002) Watermarking 2d-vector data for geographical information systems. SPIE 4675:621–628
Voigt M, Busch C (2003) Feature-based watermarking of 2d vector data. In: Security and watermarking of multimedia contents, vol 5020, pp 359–366
Voigt M, Yang B, Busch C (2004) Reversible watermarking of 2d-vector data. In: The 2004 workshop on multimedia and security, pp 160–165
Voigt M, Yang B, Busch C (2005) High-capacity reversible watermarking for 2d vector data. SPIE 5681:409–417
Voloshynovskiy S, Pereira S, Pun T, Eggers J, Su J (2001) Attacks on digital watermarks: classification, estimation based attacks, and benchmarks. IEEE Commun Mag 39(8):118–126. doi:10.1109/35.940053
Wang DM (2008) Application of digital watermarking in copyright protection of engineering drawing. Manufacture Inf Eng China 17
Wang SM, Chiu CS (2012) A reversible information hiding algorithm for 2d vector maps. In: International symposium on intelligent signal processing and communications systems, pp 424–429
Wang N, Men C (2012) Reversible fragile watermarking for 2-d vector map authentication with localization. Comput Aided Des 44(4):320–330
Wang N, Men C (2013) Reversible fragile watermarking for locating tampered blocks in 2d vector maps. Multimedia Tools Appl 67(3):709–739
Wang YS, Xu MZ (2003) Scale digital watermarking algorithm based on two-dimensional engineering graphics. J Nanchang Univ Eng Technol 4
Wang Q, Zhu C (2012) Fragile watermarking algorithm for vector geographic data exact authentication. J Geom Sci Technol 3
Wang X, Shao C, Xu X, Niu X (2007) Reversible data-hiding scheme for 2-d vector maps based on difference expansion. IEEE Trans Inf Forensics Secur 2 (3):311–320
Wang C, Peng Z, Peng Y, Yu L (2009) Watermarking 2d vector maps on spatial topology domain. In: International conference on multimedia information networking and security, vol 2, pp 71–74
Wang C, Wang W, Wang Q, Qin Q (2009) A watermarking algorithm for vector maps in spatial domain. Wuhan Univ J Geom Inf Sci 2
Wang C, Wang W, Wu B, Qin Q (2009) A watermarking algorithm for vector data based on spatial domain. In: 1st international conference on information science and engineering, pp 1959–1962
Wang C, Cheng L, Zhao Q, Zhang L, Guo L (2010) A geographical data copyright protection algorithm based on discrete cosine transform. J Shihezi Univ Nat Sci 4
Wang C, Zhao Q, Zhong F (2010) A shape-preserving and robust watermarking algorithm for vector maps. In: International conference on computational and information sciences, pp 590–593
Wang C, Zhang L, Liang B, Zheng H, Du W, Peng Y (2011) Watermarking vector maps based on minimum encasing rectangle. In: International conference on intelligent computation technology and automation, vol 2, pp 1243–1246
Wang C, Peng Z, Peng Y, Yu L, Wang J, Zhao Q (2012) Watermarking geographical data on spatial topological relations. Multimedia Tools Appl 57(1):67–89
Wang X, Huang D, Zhang Z (2012) A robust zero-watermarking algorithm for vector digital maps based on statistical characteristics. J Softw 7(10):2349–2356
Wang N, Zhang H, Men C (2014) A high capacity reversible data hiding method for 2d vector maps based on virtual coordinates. Comput Aided Des 47:108–117
Wu D (2012) A reversible watermarking scheme for 2d vector maps. In: Wu Y (ed) Software engineering and knowledge engineering: theory and practice, advances in intelligent and soft computing, vol 115. Springer, Berlin, pp 197–203
Wu D, Wang GZ (2009) Reversible digital watermarking scheme for 2-d vector maps based on difference expansion and shifting. J Optoelectron Laser 7
Wu B, Wang W, Peng Z, Du D (2009) A new algorithm for watermarking building polygons. In: International conference on digital image processing, pp 366–370
Wu D, Wang G, Gao X (2009) Reversible watermarking of svg graphics. In: International conference on communications and mobile computing, vol 3, pp 385–390
Wu B, Wang W, Peng Z, Du D, Wang C (2010) Design and implementation of spatial data watermarking service system. Geo-spatial Inf Sci 13 (1):40–48
Wu J, Liu Q, Wang J, Gao L (2013) A robust watermarking algorithm for 2d cad engineering graphics based on dct and chaos system. In: Tan Y, Shi Y, Mo H (eds) Advances in swarm intelligence, LNCS, vol 7929. Springer, Berlin, pp 215–223
Wu J, Yang F, Wu C (2013) Review of digital watermarking for 2d-vector map. In: IEEE international conference on green computing and communications, internet of things and cyber, physical and social computing, pp 2098–2101
Xu DH, Zhu CQ, Wang QS (2007) A survey of the research on digital watermarking for the vector digital map. Geom World 6
Xun W, Hai L, Hujun B (2004) A robust watermarking algorithm for vector digital mapping. J Comput Aided Des Comput Graph 1377–1381
Xun W, Ding-jun H, Zhi-yong Z (2012) A robust zero-watermarking algorithm for 2d vector digital maps. In: He X, Hua E, Lin Y, Liu X (eds) Computer, informatics, cybernetics and applications, LNEE, vol 107. Springer, Netherlands, pp 533–541
Yamada T, Fujii Y, Tezuka S, Komoda N (2006) Evaluation of digital watermarking system for vector map content distribution. In: International conference on service systems and service management, vol 2, pp 1637–1642
Yan H, Li J (2011) A blind watermarking approach to protecting geospatial data from piracy. Int J Inf Educ Technol 1(2):94–98
Yan H, Li J (2012) Blind watermarking technique for topographic map data. Appl Geom 4(4):225–229
Yan H, Li J, Wen H (2011) A key points-based blind watermarking approach for vector geo-spatial data. Comput Environ Urban Syst 35(6):485–492
Yang CS, Zhu CQ (2007) Watermarking algorithm for vector geo-spatial data on wavelet transformation. J Zhengzhou Inst Surv Mapp 1
Yue M, Peng Z, Peng Y (2014) A fragile watermarking scheme for modification type characterization in 2d vector maps. In: Chen L, Jia Y, Sellis T, Liu G (eds) Web technologies and applications, lecture notes in computer science, vol 8709. Springer International Publishing, pp 129–140
Yun H, Hongtao W, Hanyu Z, Xinxin N, Yixian Y (2004) A digital watermark scheme in vector data. Comput Eng Appl 21
Zhanchuan C, Wei S, Changzhen X, Dongxu Q (2005) Watermarking of two-dimensional engineering graph based on the orthogonal complete u-system. In: 9th international conference on computer aided design and computer graphics, pp 205–209
Zhang ZL (2010) Anti-compression watermark algorithm for vector map. Comput Eng 20
Zhang HL, Gao MM (2009) A semi-fragile digital watermarking algorithm for 2d vector graphics tamper localization. In: International conference on multimedia information networking and security, vol 1, pp 549–552
Zhang H, Li Y (2009) Toward a 2d vector map with a feature nodes-based watermarking method. SPIE 7146:1–10
Zhang Y, Wang Q (2011) Digital watermarking algorithm of vector map based on feature points. In: Cross strait quad-regional radio science and wireless technology conference, vol 2, pp 1430–1433
Zhang D, Qian D, Han P (2007) A new attributes-priority matching watermarking algorithm satisfying topological conformance for vector map. In: 3rd international conference on intelligent information hiding and multimedia signal processing, vol 2, pp 469–472
Zhang L, Li A, Lv G, Lin B (2008) Study on adaptive watermark of gis vector data. Geo-Inf Sci 6
Zhang C, Zhang X, Zhang D, Jiao Y (2008) Digital watermarking of vector map based on vector angle. In: International conference on intelligent computation technology and automation, vol 2, pp 127–130
Zhang Z, Wang Y, Sun S (2009) An anti-compression watermarking scheme for vector map based on improved douglas-peucker algorithm. In: 1st international workshop on education technology and computer science, vol 2, pp 1075–1079
Zhang ZL, Sun SS, Wang YM, Zheng KB (2009) Zero-watermarking algorithm for 2d vector map. Comput Eng Des 1473–1475
Zhang L, Yan D, Jiang S, Shi T (2010) A new robust watermarking algorithm for vector data. Wuhan Univ J Nat Sci 15(5):403–407
Zhao H, Yuan W, Wang Z (2008) A new watermarking scheme for cad engineering drawings. In: 9th international conference on computer-aided industrial design and conceptual design. IEEE, pp 518– 522
Zhao H, Du S, Zhang D (2010) A reversible watermarking scheme for 2d vector drawings based on difference expansion. In: 11th international conference on computer-aided industrial design conceptual design, vol 2, pp 1441–1446
Zhao J, Lin H, Wang F (2010) Study on data quality evaluation of vector map watermarking. J Image Graph 1121–1125
Zhao Q, Sui L, Wang C, Yin X (2013) Publicly verify the integrity of the geographical data using public watermarking scheme. In: Bian F, Xie Y, Cui X, Zeng Y (eds) Geo-informatics in resource management and sustainable ecosystem, communications in computer and information science, vol 398. Springer, Berlin, pp 646–652
Zheng L, You F (2009) A fragile digital watermark used to verify the integrity of vector map. In: International conference on e-business and information system security, pp 1–4
Zheng L, Jia Y, Wang Q (2009) Research on vector map digital watermarking technology. In: 1st international workshop on education technology and computer science, vol 1, pp 304– 307
Zheng L, Chen R, Li L, Li Y (2010) Study on digital watermarking for vector graphics. In: 2nd international workshop on education technology and computer science, vol 2, pp 535–538
Zheng L, Feng L, Li Y, Cheng X (2010) Research on digital rights management model for spatial data files. In: 2nd international conference on information engineering and computer science , pp 1–4
Zheng L, Li Y, Feng L, Liu H (2010) Research and implementation of fragile watermark for vector graphics. In: 2nd international conference on computer engineering and technology, vol 1, pp 522– 525
Zheng L, Xie K, Li Y, Liu H, Li T (2010) A digital watermark scheme for vector graphics. In: International conference on image analysis and signal processing, pp 699–702
Zheng L, Chen R, Cheng X (2011) Research and implementation of digital rights management model for vector graphics. In: International conference on uncertainty reasoning and knowledge engineering, vol 2, pp 17–20
Zhong S, Hu Y, Lu J (2006) A new geometric-transformation robust and practical embedding scheme for watermarking 2d vector maps in the graph spectral domain. In: International conference on communications, circuits and systems, vol 1, pp 24–30
Zhou X, Bi DY (2004) Use digital watermarking to protect gis data by chinese remaindering. J Image Graph 611–615
Zhou X, Pan X (2006) Watermark-based scheme to protect copyright of svg data. In: International conference on computational intelligence and security, vol 2, pp 1199–1202
Zhou X, Ren Y, Pan X (2006) Watermark embedded in polygonal line for copyright protection of contour map. Int J Comput Sci Net Secur 6(7):202–205
Zhou Y, Li A, Lv G (2010) Research of robustness evaluation method for gis vector data digital watermarking algorithm. In: 18th international conference on geoinformatics, pp 1– 6
Zhu C, Yang C, Ren N (2010) Application of digital watermarking to geospatial data security. Bull Surv Mapp 1–3
Zhu CQ, Yang CS, Wang QS (2008) A watermarking algorithm for vector geo-spatial data based on integer wavelet transform. Int Arch Photogramm Remote Sens Spat Inf Sci 37:15– 18
Zhu JF, Deng SH, Xu WZ (2011) Integration of a variety of algorithms in high robustness watermarking for vector map data. Sci Surv Mapp
Zuo C, Li A, Meng C (2010) Gis vector data automatic watermark detection based on mobile agent technology. In: Geoinformatics, pp 1–4
Author information
Authors and Affiliations
Corresponding author
Additional information
Open Access
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Abubahia, A., Cocea, M. Advancements in GIS map copyright protection schemes - a critical review. Multimed Tools Appl 76, 12205–12231 (2017). https://doi.org/10.1007/s11042-016-3441-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-016-3441-z