A high-precision map zero-watermark encryption method, device and electronic device

Abstract

The present application relates to the field of geographic information security technology, and in particular to a high-precision map zero-watermark encryption method, device and electronic device. The method includes: based on the one-dimensional binary sequence of the map image, obtaining the binary copyright information of the map image; for each block divided by the map image, based on the geometric features and attribute features of the block, obtaining the block signal sequence of the block; dividing the block signal sequence into multiple intervals according to a preset segmentation method, and calculating the signal occurrence frequency in each interval; normalizing the signal occurrence rate, and obtaining zero watermark information based on the normalized data and the column pixels of the map image; completing the zero watermark encryption operation of the map image based on the binary copyright information and the zero watermark information. This method can simultaneously construct a zero watermark algorithm with geometric attributes and attribute characteristics.

Description

Technical Field

[0001] The present application relates to the field of geographic information security technology, and in particular to a high-precision map zero-watermark encryption method, device and electronic equipment. Background Art

[0002] High-precision maps are characterized by high precision, more detailed map elements, and richer attributes. Because their absolute coordinate accuracy reaches the sub-meter level, and the road traffic information and attribute characteristics they contain are richer and more detailed, they are widely used in unmanned vehicle positioning, navigation, and road network control. However, while they are widely used, problems such as illegal theft and illegal leakage occur frequently. Therefore, how to effectively protect the data copyright of high-precision maps has become a hot issue.

[0003] As a cutting-edge technology for protecting high-precision vector geographic data, zero watermark constructs watermark information through the important features of the original data itself. No modification is made to the original data during the watermark construction process, which effectively solves the contradiction between the imperceptibility and robustness of traditional watermarks and has good practicality.

[0004] Existing zero watermarking technologies can be divided into two types based on attribute features and based on spatial features. However, zero watermarking based on attribute features is often used for text data types. Figure 1 There is a lack of effective consideration for such data. Moreover, the zero watermark algorithm based on spatial features constructs watermark information based on data geometric features, which can only solve the applicability of data with vector features.

[0005] Therefore, no matter which of the above methods is used, the existing zero watermark algorithms for text and vector geographic data only consider a single geometric feature or attribute feature, while high-precision maps have rich geometric attributes and attribute features at the same time. It is difficult for existing algorithms to simultaneously consider constructing a zero watermark algorithm with common features of both. Summary of the invention

[0006] The embodiment of the present invention provides a method, device and equipment for zero-watermark encryption of high-precision maps, which is used to solve the problem that existing algorithms are difficult to simultaneously construct a zero-watermark algorithm with geometric attributes and attribute characteristics. The method includes:

[0007] Based on the one-dimensional binary sequence of the map image, obtaining binary copyright information of the map image;

[0008] For each block divided from the map image, a block signal sequence of the block is obtained based on the geometric features and attribute features of the block;

[0009] Divide the block signal sequence into multiple intervals according to a preset division method, and calculate the signal occurrence frequency in each interval;

[0010] Normalizing the signal occurrence rate, and obtaining zero watermark information based on the normalized data and the column pixels of the map image;

[0011] A zero watermark encryption operation on the map image is completed based on the binary copyright information and the zero watermark information.

[0012] Specifically, the one-dimensional binary sequence based on the map image is used to obtain the binary copyright information of the map image, including:

[0013] Performing binary conversion on the pixels of the map image respectively to obtain a binary copyright image corresponding to the map image, and sequentially arranging the binary values ​​corresponding to each pixel value in the binary copyright image in a preset order into the one-dimensional binary sequence;

[0014] The binary copyright information is obtained by performing an XOR operation on the one-dimensional binary sequence using a pre-generated random sequence.

[0015] Specifically, the geometric features include the number of buildings, the length of the road, and the area value; the geometric features include the road type and the surface type; the block signal sequence of the block is obtained based on the geometric features and attribute features of the block, including:

[0016] Extracting the number of buildings, road length, area value, road type, and surface type from the block;

[0017] Get an integer value according to the number of buildings;

[0018] Obtaining a proportional value according to the road length and the area value;

[0019] Obtaining an attribute value according to the road type and the surface type;

[0020] The integer values, the ratio values ​​and the attribute values ​​are arranged in a preset arrangement order to obtain the block signal sequence.

[0021] Specifically, the normalizing the signal occurrence rate includes:

[0022] The ratio of the signal occurrence rate to the total number of blocks in the map image is calculated, and the ratio result is used as the result of the normalization processing.

[0023] Specifically, the step of obtaining zero watermark information based on the normalized data and the column pixels of the map image includes:

[0024] For each interval, in the map image, a column of pixels corresponding to the interval is determined; and a brightness value of the column of pixels is determined according to a signal occurrence rate of the interval;

[0025] Obtaining a grayscale value based on the determined brightness value and the normalized data;

[0026] The grayscale image corresponding to the grayscale value is binarized and encrypted to obtain zero watermark information.

[0027] Specifically, the zero-watermark encryption operation on the map image based on the binary copyright information and the zero-watermark information includes:

[0028] The binary copyright information is XORed with the zero watermark information to generate a zero watermark encryption operation for the map image.

[0029] An embodiment of the present invention provides a high-precision map zero-watermark encryption device, the device comprising:

[0030] A first acquisition module, used for obtaining binary copyright information of the map image based on a one-dimensional binary sequence of the map image;

[0031] A second acquisition module is used to obtain a block signal sequence of each block divided from the map image based on the geometric features and attribute features of the block;

[0032] A calculation module, used to divide the block signal sequence into multiple intervals according to a preset division method, and calculate the signal occurrence frequency in each interval;

[0033] A third acquisition module is used to normalize the signal occurrence rate and obtain zero watermark information based on the normalized data and the column pixels of the map image;

[0034] A confirmation module is used to complete the zero watermark encryption operation on the map image based on the binary copyright information and the zero watermark information.

[0035] Specifically, the first acquisition module is specifically used for:

[0036] Performing binary conversion on the pixels of the map image respectively to obtain a binary copyright image corresponding to the map image, and sequentially arranging the binary values ​​corresponding to each pixel value in the binary copyright image in a preset order into the one-dimensional binary sequence;

[0037] The binary copyright information is obtained by performing an XOR operation on the one-dimensional binary sequence using a pre-generated random sequence.

[0038] Specifically, the geometric features include the number of buildings, the length of the road and the area value; the geometric features include the road type and the surface type; the second acquisition module is specifically used for:

[0039] Extracting the number of buildings, road length, area value, road type, and surface type from the block;

[0040] Get an integer value according to the number of buildings;

[0041] Obtaining a proportional value according to the road length and the area value;

[0042] Obtaining an attribute value according to the road type and the surface type;

[0043] The integer values, the ratio values ​​and the attribute values ​​are arranged in a preset arrangement order to obtain the block signal sequence.

[0044] An embodiment of the present invention also provides an electronic device, comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction is executed by the processor to perform any of the steps of the high-precision map zero-watermark encryption method described above.

[0045] The method provided by the embodiment of the present invention has an algorithm that comprehensively considers the geometric features and attribute features of the high-precision map, and can realize the extraction and detection of watermark information without affecting the data accuracy. At the same time, the constructed watermark information has high uniqueness, can effectively distinguish different data sets, and has good robust performance to deal with common attacks. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A flow chart of a high-precision map zero-watermark encryption method provided in an embodiment of the present application;

[0047] Figure 2 A structural diagram of a high-precision map zero-watermark encryption device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present application, so the present application is not limited by the specific embodiments disclosed below.

[0049] In the description of the present application, it should be understood that if the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. appear, the orientation or position relationship indicated by these terms is based on the orientation or position relationship shown in the accompanying drawings, which is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application.

[0050] In addition, if the terms "first" or "second" appear, these terms are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, if the term "plurality" appears, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0051] In this application, unless otherwise clearly specified and limited, if the terms "installed", "connected", "connected", "fixed" and the like appear, these terms should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integrated connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to the specific circumstances.

[0052] In the present application, unless otherwise clearly specified and limited, if there is a description that a first feature is "above" or "below" a second feature, etc., or similar descriptions appear, it may mean that the first and second features are in direct contact, or that the first and second features are in indirect contact through an intermediate medium. Moreover, the first feature being "above", "above" and "above" the second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. The first feature being "below", "below" and "below" the second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0053] It should be noted that if an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or there may be a central element. If an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. If any, the terms "vertical", "horizontal", "upper", "lower", "left", "right" and similar expressions used in this application are for illustrative purposes only and do not represent the only implementation method.

[0054] The embodiment of the present invention provides a high-precision map zero-watermark encryption method, such as Figure 1 As shown, the method includes:

[0055] Step 11, based on the one-dimensional binary sequence of the map image, obtain the binary copyright information of the map image. This step specifically includes:

[0056] The pixels of the map image (the map image mentioned here can be a high-precision map or any other image) are converted into binary to obtain a binary copyright image, and the binary values ​​corresponding to each pixel value in the binary copyright image are arranged in a preset order to form the one-dimensional binary sequence. For example:

[0057] Get map image copyright information The binary copyright image is arranged row by row into a one-dimensional binary sequence , if the copyright information is other multimedia information, it is converted into a binary byte stream;

[0058] Use the pre-generated random sequence to perform an XOR operation with the one-dimensional binary sequence to obtain the encrypted binary copyright information, for example:

[0059] A two-dimensional Henon map is used to generate a random sequence, and the random sequence is XORed with the one-dimensional binary sequence of the map image to complete the encryption of the one-dimensional binary sequence; the binary ciphertext obtained after encryption is the encrypted binary copyright information;

[0060] The copyright information here is not only binary copyright information, but also copyright information provided by companies, institutions, and individuals, which can be understood as watermark information on PDF. Therefore, the binary copyright information mentioned in this application can also be any image rather than just the binarization of the map.

[0061] Step 12, for each block divided from the map image, based on the geometric features and attribute features of the block, obtain a block signal sequence of the block; this step specifically includes:

[0062] Usually, high-precision map images themselves are stored based on a block structure, and each block map (i.e. block) contains at least one or more geometric features and attribute features such as roads, buildings, landmarks, etc.

[0063] First, geometric features and attribute features are extracted from each block. Geometric features include: number of buildings, road edge information, length, and area. Attribute features include: road type, landmarks, and surface type. These features can be regarded as discrete signal samples. Therefore, the number of buildings, road length, area value, road type, and surface type can be extracted from the block in the end;

[0064] Then, the discrete geometric features and attribute features are quantized and encoded, including:

[0065] First, map the number of buildings into discrete integer values;

[0066] Second, standardize the road length and area into proportional values;

[0067] Third, the road type and surface type are mapped to corresponding attribute values ​​through a predefined dictionary;

[0068] In this way, the geometric features and attribute features of each block can be arranged in a preset order and combined into a one-dimensional signal sequence, namely the block signal sequence. The block signal sequence is expressed as:

[0069]

[0070] in, Refers to the size of the generated zero watermark image, The larger the value, the higher the uniqueness of the zero watermark information, but the corresponding robustness is also lower. Here it can be taken as 32.

[0071] The preset arrangement order may be arranged in order of distance or size to form a one-dimensional signal sequence, which can provide a basis for subsequent signal processing.

[0072] Step 13, dividing the block signal sequence into multiple intervals according to a preset division method, and calculating the signal occurrence frequency in each interval; including:

[0073] The block signal sequence is divided into multiple intervals, the frequency of signal occurrence in each interval is calculated, and a signal histogram is constructed. The number of intervals can be set to be the same as the size of the zero watermark image, that is, , here the value is 32. Count the frequency of signal occurrence in each interval and construct a histogram , expressed as:

[0074]

[0075] in Indicates that the signal value falls within the The frequency of the interval is the signal occurrence rate. The value is 32.

[0076] Step 14, normalizing the signal occurrence rate, and obtaining zero watermark information based on the normalized data and the column pixels of the map image. This step specifically includes:

[0077] First, in order to ensure consistency between blocks, the histogram needs to be normalized to have a uniform scale. The normalized histogram will not affect its watermark characteristics due to different data scales, ensuring the adaptability of zero watermark in map images of different resolutions or different data blocks. Specifically:

[0078] The ratio of the signal occurrence rate to the total number of blocks in the map image is calculated, and the ratio result is used as the result of the normalization process, that is, for each interval in the histogram, the ratio of the signal occurrence rate to the total number of blocks in the map image is calculated, and the ratio result is used as the result of the normalization process, so that the value of each interval is between [0, 1]. The ratio result Hnorm is specifically obtained by the following formula (1):

[0079] Formula (1)

[0080] in The value is 32, h is the signal occurrence rate, and T is the total number of blocks.

[0081] After normalization, each value of the histogram is in the range of [0, 1], ensuring the consistency of watermark features between different blocks.

[0082] Secondly, for each interval, in the map image, a column of pixels corresponding to the interval is determined; the brightness value of the column of pixels is determined according to the signal occurrence rate of the interval; for example, the normalized ratio result is directly mapped to the grayscale value (0-255) of the image.

[0083] Then, the grayscale value is obtained based on the determined brightness value and the normalized data; specifically:

[0084] The normalized ratio result Hnorm of each interval is mapped to the corresponding grayscale value through formula (2): :

[0085] Formula (2)

[0086] It is the first The gray value of the interval is A pixel value in the watermark image, here The value is 32. Finally, the grayscale image corresponding to the grayscale value is binarized and encrypted to obtain zero watermark information. Specifically, the grayscale zero watermark image obtained above is binarized and used to perform an XOR operation with the encrypted binary copyright information to generate zero watermark copyright information. Of course, the zero watermark copyright information generated here has higher uniqueness than the binarized zero watermark information, and can be stored in the registration system for subsequent verification.

[0087] The above process only generates zero watermark information for each block of the current map image, combines the feature vectors of multiple blocks into an overall zero watermark feature, which is the zero watermark information of the map image and the digital fingerprint of the data, and then performs an XOR operation with the encrypted copyright information to generate the zero watermark copyright information of the map. Integration can be the splicing of the zero watermark information of each block, or the superposition of the zero watermark information of each block, that is, each bit adopts a voting mechanism, and uses the block zero watermark information to determine the zero watermark information of the final map image.

[0088] The generated histogram zero watermark and the digital fingerprint of the map are registered and stored in a third-party or dedicated authentication system. When copyright verification is required, feature signals are extracted from the map image data again to generate a histogram, which is matched with the stored zero watermark to determine the integrity of the data and the ownership of the copyright. The specific copyright watermark information detection method is as follows:

[0089] The above method is used to generate a watermark sequence for each block and the zero watermark information of the map for the high-precision map image to be detected.

[0090] The watermark sequence and the binary encrypted copyright information are XORed to obtain the zero-watermark copyright information generated by the block data to be detected and the zero-watermark copyright information of the map image.

[0091] The zero-watermark copyright information generated with the original data is tested for similarity. If the similarity threshold is exceeded, it is considered to be the same data, otherwise the data is different.

[0092] like Figure 2 As shown, the embodiment of the present application provides a high-precision map zero-watermark encryption device, the device comprising:

[0093] A first acquisition module 21 is used to obtain binary copyright information of the map image based on a one-dimensional binary sequence of the map image;

[0094] The second acquisition module 22 is used to obtain a block signal sequence of each block divided from the map image based on the geometric features and attribute features of the block;

[0095] A calculation module 23, used to divide the block signal sequence into multiple intervals according to a preset division method, and calculate the signal occurrence frequency in each interval;

[0096] A third acquisition module 24 is used to normalize the signal occurrence rate and obtain zero watermark information based on the normalized data and the column pixels of the map image;

[0097] The confirmation module 25 is used to complete the zero-watermark encryption operation on the map image based on the binary copyright information and the zero-watermark information.

[0098] The first acquisition module 21 is specifically used for:

[0099] The pixels of the map image are respectively converted into binary to obtain a binary copyright image corresponding to the map image, and the binary values ​​corresponding to each pixel value in the binary copyright image are arranged in turn according to a preset order to form the one-dimensional binary sequence; a pre-generated random sequence is used to perform an XOR operation with the one-dimensional binary sequence to obtain the binary copyright information.

[0100] The second acquisition module 22 is specifically used for:

[0101] The number of buildings, road length, area value, road type and surface type are extracted from the block; an integer value is obtained according to the number of buildings; a proportional value is obtained according to the road length and the area value; an attribute value is obtained according to the road type and the surface type; the integer value, the proportional value and the attribute value are arranged in a preset order to obtain the block signal sequence.

[0102] The third acquisition module 24 is specifically used to calculate the ratio of the signal occurrence rate to the total number of blocks in the map image, and use the ratio result as the result of the normalization process. For each interval, in the map image, determine the column of pixels corresponding to the interval; determine the brightness value of the column of pixels according to the signal occurrence rate of the interval; obtain the gray value based on the determined brightness value and the data after the normalization process; perform binarization and encryption on the gray image corresponding to the gray value to obtain zero watermark information.

[0103] The confirmation module 25 is specifically used to perform an XOR operation on the binary copyright information and the zero watermark information to generate a zero watermark encryption operation for the map image.

[0104] The technical solution provided by the present invention first extracts the geometric features and attribute features of each block based on the block storage structure of the high-precision map itself, then combines such features into a one-dimensional signal sequence, performs statistical analysis on the signal sequence, generates a signal histogram of the features, normalizes the histogram and maps it to zero watermark information of the block data, and finally integrates all block watermark information to generate the overall zero watermark information of the map data. The purpose of the present invention is to propose a high-precision map zero watermark algorithm based on a feature matrix in response to possible illegal tampering and copyright ownership issues during the transmission, sharing and use of high-precision maps, as well as the lossless requirements for data accuracy. The proposed algorithm comprehensively considers the geometric features and attribute information of the high-precision map, and can realize the extraction and detection of watermark information without affecting the data accuracy. At the same time, the constructed watermark information has high uniqueness, can effectively distinguish different data sets, and has good robustness to deal with common attacks.

[0105] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0106] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A high-precision map zero-watermark encryption method, characterized in that: The method comprises: Based on the one-dimensional binary sequence of the map image, obtaining binary copyright information of the map image; For each block divided by the map image, the number of buildings, the road length, the area value, the road type and the surface type are extracted from the block; an integer value is obtained according to the number of buildings; a proportional value is obtained according to the road length and the area value; an attribute value is obtained according to the road type and the surface type; the integer value, the proportional value and the attribute value are arranged in a preset arrangement order to obtain the block signal sequence; Divide the block signal sequence into multiple intervals according to a preset division method, and calculate the signal occurrence frequency in each interval; Normalizing the signal occurrence rate, and obtaining zero watermark information based on the normalized data and the column pixels of the map image; A zero watermark encryption operation on the map image is completed based on the binary copyright information and the zero watermark information.

2. The method according to claim 1, characterized in that The one-dimensional binary sequence based on the map image is used to obtain the binary copyright information of the map image, including: Performing binary conversion on the pixels of the map image respectively to obtain a binary copyright image corresponding to the map image, and sequentially arranging the binary values ​​corresponding to each pixel value in the binary copyright image in a preset order to form the one-dimensional binary sequence; The binary copyright information is obtained by performing an XOR operation on the one-dimensional binary sequence using a pre-generated random sequence.

3. The method according to claim 1, characterized in that The normalizing process of the signal occurrence rate comprises: The ratio of the signal occurrence rate to the total number of blocks in the map image is calculated, and the ratio result is used as the result of the normalization processing.

4. The method according to claim 1, characterized in that The step of obtaining zero watermark information based on the normalized data and the column pixels of the map image includes: For each interval, in the map image, a column of pixels corresponding to the interval is determined; and a brightness value of the column of pixels is determined according to a signal occurrence rate of the interval; Obtaining a grayscale value based on the determined brightness value and the normalized data; The grayscale image corresponding to the grayscale value is binarized and encrypted to obtain zero watermark information.

5. The method according to claim 1, characterized in that The zero-watermark encryption operation on the map image based on the binary copyright information and the zero-watermark information includes: The binary copyright information is XORed with the zero watermark information to generate a zero watermark encryption operation for the map image.

6. A high-precision map zero-watermark encryption device, characterized in that: The device comprises: A first acquisition module, used for obtaining binary copyright information of the map image based on a one-dimensional binary sequence of the map image; The second acquisition module is used to extract the number of buildings, road length, area value, road type and surface type from each block divided by the map image; obtain an integer value according to the number of buildings; obtain a proportional value according to the road length and the area value; obtain an attribute value according to the road type and the surface type; and arrange the integer values, the proportional values ​​and the attribute values ​​in a preset arrangement order to obtain the block signal sequence; A calculation module, used to divide the block signal sequence into multiple intervals according to a preset division method, and calculate the signal occurrence frequency in each interval; A third acquisition module is used to normalize the signal occurrence rate and obtain zero watermark information based on the normalized data and the column pixels of the map image; A confirmation module is used to complete the zero watermark encryption operation on the map image based on the binary copyright information and the zero watermark information.

7. The high-precision map zero-watermark encryption device according to claim 6, characterized in that: The first acquisition module is specifically used for: Performing binary conversion on the pixels of the map image respectively to obtain a binary copyright image corresponding to the map image, and sequentially arranging the binary values ​​corresponding to each pixel value in the binary copyright image in a preset order to form the one-dimensional binary sequence; The binary copyright information is obtained by performing an XOR operation on the one-dimensional binary sequence using a pre-generated random sequence.

8. An electronic device, characterized in that: The electronic device includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction is executed by the processor to carry out the steps of a high-precision map zero-watermark encryption method as described in any one of claims 1 to 5.

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