A method for encrypting geographic information data

Abstract

The present application belongs to the technical field of encrypted transmission, and particularly relates to a kind of encrypted processing method of geographic information data, comprising: constructing different levels of encryption keys according to role permissions, each level of key contains a plurality of groups of chaotic mapping parameters, and the next level contains all parameters of the previous level. Each group of chaotic mapping parameters is used to encrypt geographic images, and the results of each group are used to form the ciphertext of the corresponding level. The specific process is as follows: S1, generate a chaotic sequence; S2, select pixel points in the image without replacement based on the chaotic sequence, encode the selected pixel points using AMBTC, obtain high quantization values, low quantization values, and binary masks, and concatenate the corresponding binary numbers to form the encoding result; S3, repeat S2 until all pixels are selected, and collect the encoding results to form the encryption result under this group of parameters. The present application combines permission management and chaotic characteristics, realizes hierarchical encryption of geographic images, and can resist statistical analysis attacks and brute force attacks.

Description

Technical Field

[0001] The present invention relates to the field of encrypted transmission technology, and more specifically, to an encryption processing method for geographic information data. Background Art

[0002] In the field of encryption and protection of geographic information data, traditional encryption methods such as the Advanced Encryption Standard (AES) and the Data Encryption Standard (DES) are widely used for secure data transmission and storage.

[0003] In practical applications, encryption algorithms such as AES and DES have certain limitations. They primarily focus on overall data confidentiality, emphasizing the complete encryption of raw data and ensuring its inaccessibility to unauthorized users. However, these algorithms fail to consider the need for tiered access based on different user permissions. In the field of geographic information, image data often contains multiple levels of sensitive information, such as terrain features and the location of critical facilities, requiring varying degrees of detail based on user permissions. However, traditional AES and DES encryption algorithms cannot directly differentiate data based on individual permissions. All users receive the complete raw data after decryption, potentially exposing unnecessary sensitive information.

[0004] To address this issue, image encryption technology based on chaotic mapping has become a research hotspot. Chaotic mapping uses simple mathematical formulas to generate highly random and unpredictable sequences, enabling efficient encryption while ensuring security. However, image encryption based on chaotic mapping lacks a permissions management mechanism and cannot provide differentiated decryption results based on user permissions. This limitation makes it difficult for image encryption based on chaotic mapping to meet the requirements of hierarchical access in the geographic information field in practical applications. Summary of the Invention

[0005] To address the technical problem that the existing encryption algorithms mentioned above cannot directly perform differentiated processing based on personnel permissions, which may expose sensitive information in geographic information data, the present invention provides an encryption processing method for geographic information data, including:

[0006] Encryption keys of different levels are constructed according to role permissions, and the encryption keys of different levels include several groups of chaotic mapping parameters, and the encryption keys of the next level include all groups of chaotic mapping parameters in the encryption keys of the previous level; each group of chaotic mapping parameters is used to encrypt the geographic image respectively to obtain the encryption result of the geographic image under each group of chaotic mapping parameters, and the encryption results corresponding to all groups of chaotic mapping parameters contained in the encryption keys of different levels constitute the ciphertext of the corresponding level; wherein, the encryption process includes: S1: for any group of chaotic mapping parameters, a chaotic sequence is generated according to the chaotic mapping parameters; S2: according to the chaotic sequence, several pixel points are selected in the geographic image without replacement; AMBTC encoding is performed on the selected pixel points to obtain a high quantization value, a low quantization value and a binary mask; the binary mask, the binary number corresponding to the high quantization value, and the binary number corresponding to the low quantization value are spliced ​​together to obtain an encoding result; S3: S2 is repeated until all pixels in the geographic image have been selected and the iteration is stopped, and all encoding results constitute the encryption result of the geographic image under the chaotic mapping parameters.

[0007] The present invention achieves multi-level security protection of geographic images by constructing hierarchical encryption keys by combining role permissions and chaotic mapping parameters. The encryption keys of different levels contain an increasing number of chaotic mapping parameter groups, ensuring that high-authority users can restore more detailed image information, while low-authority users can only obtain vague approximate content, effectively meeting the hierarchical access requirements. During the encryption process, the randomness and unpredictability of the chaotic sequence are used to select pixel points, and the data is encoded in combination with the AMBTC algorithm, thereby improving the security of the encryption result. Finally, by splicing the binary mask and the binary number corresponding to the quantization value to generate the ciphertext, the anti-attack capability of the encryption result is further enhanced, while retaining the core features of the geographic image, achieving a balance between security and efficiency.

[0008] Preferably, the chaotic mapping parameters are ,in Indicates the The bifurcation parameter in the group chaos map parameter, Indicates the Initial value parameters in the group chaos map parameters, Indicates the Number of dropout iterations in the group chaos map parameters.

[0009] Preferably, the generating of the chaotic sequence according to the chaotic mapping parameters comprises: for the first Group chaos mapping parameters, according to the bifurcation parameters And the initial value parameters , using the Logistic Chaotic Mapping algorithm to generate a length of sequence, the first The data are discarded and the remaining data constitute the chaotic sequences, where Indicates the The number of dropout iterations in the group chaos map parameters, Indicates the number of rows of geographic imagery, Represents the number of columns of the geographic image.

[0010] Preferably, the step of selecting a plurality of pixels in the geographic image without replacement according to the chaotic sequence comprises: mapping the first element in the chaotic sequence to [2, ] is an integer in the range of Indicates that the 2nd to 3rd in the chaotic sequence The elements are mapped to [1, ] within the range integers, the integers constitute a position sequence; among them, is the preset expansion multiple, Indicates the number of rows of geographic imagery, Indicates the number of columns in the geographic image; select pixels in the geographic image in sequence according to each element in the position sequence.

[0011] The present invention uses a chaotic sequence to generate a position sequence for pixel selection, resulting in a high degree of randomness and flexibility. First, the first element of the chaotic sequence is mapped to a target number, so that the number of pixels selected each time is not fixed, avoiding the regularity loopholes that may arise from selecting a fixed number. Next, the position sequence generated by the chaotic sequence is used. Due to the randomness and unpredictability of the chaotic sequence, it is difficult for attackers to infer the specific location or number of selected pixels, thereby significantly improving the encryption algorithm's anti-attack capabilities. Furthermore, the selection method without replacement ensures that each pixel is selected only once, further enhancing the uniformity and reliability of the encryption results.

[0012] Preferably, the step of selecting pixel points in the geographic image according to each element in the position sequence comprises: selecting the pixel points in the position sequence Elements are recorded as ,like and , then select the first pixel from the remaining pixels in the geographic image pixels; if and and , then select the first pixel from the remaining pixels in the geographic image pixels; if and and , then select the last pixel point from the remaining pixels in the geographic image; if , stop selecting;Wherein represents the remainder symbol, Indicates the number of remaining pixel points in the geographical image.

[0013] Preferably, the selected pixel points are AMBTC encoded to obtain high quantization values, low quantization values and binary masks, comprising: taking the selected pixel points as to-be-encoded pixel points, calculating the mean value of the gray values of all to-be-encoded pixel points, taking the to-be-encoded pixel points with a gray value greater than or equal to the mean value as high-luminance pixel points, and taking the to-be-encoded pixel points with a gray value less than the mean value as low-luminance pixel points;When the to-be-encoded pixel points belong to the high-luminance pixel points, the mask is set to 1, otherwise the mask is set to 0, and the masks corresponding to all to-be-encoded pixel points form a binary mask;The average value of the gray values of all high-luminance pixel points is rounded up to obtain the high quantization value;The average value of the gray values of all low-luminance pixel points is rounded up to obtain the low quantization value.

[0014] The application encodes the selected pixel points by AMBTC algorithm, reduces the data volume while retaining the main features of the image, not only reduces the data volume of storage and transmission, but also realizes a simple description of the image content by using quantization values and masks. At the same time, the AMBTC algorithm can restore the approximate pixel value distribution according to the mask and the quantization value in the reconstruction process, ensuring that the decryption result is visually consistent with the original image. The application combines the advantages of compression and encryption, ensures the security of geographical image information while improving the processing efficiency.

[0015] Preferably, the method for obtaining the binary number corresponding to the high quantization value is: converting the high quantization value into an 8-bit binary number to obtain the binary number corresponding to the high quantization value;The method for obtaining the binary number corresponding to the low quantization value is: converting the low quantization value into an 8-bit binary number to obtain the binary number corresponding to the low quantization value.

[0016] Preferably, the method for obtaining the binary number corresponding to the high quantization value is: constructing an encoding table, the encoding objects in the encoding table are each integer in [0, 255], the code words of each encoding object are 8-bit binary numbers, and the code words of each encoding object are all different;The code word of the encoding object in the encoding table equal to the high quantization value is taken as the binary number corresponding to the high quantization value;The method for obtaining the binary number corresponding to the low quantization value is: taking the code word of the encoding object in the encoding table equal to the low quantization value as the binary number corresponding to the low quantization value.

[0017] The present invention maps high quantization values ​​and low quantization values ​​to unique 8-bit binary numbers by constructing a coding table, significantly improving the security and complexity of the coding result. A one-to-one correspondence is established between the 256 coding objects in the coding table and the 8-bit binary numbers. Since the mapping relationship can be arbitrarily arranged, there are theoretically 256 possible combinations, far exceeding the exhaustive range of classical or quantum computing capabilities, making it impossible for attackers to restore the coding table by brute force guessing, thereby effectively preventing reverse analysis of the binary representation of the quantization value. At the same time, the fixed-length 8-bit binary codeword ensures the consistency of the data format, avoids problems such as leading zero loss, and is convenient for the efficient implementation of subsequent encryption and decryption operations.

[0018] Preferably, the encryption process further comprises: in response to each obtained coded object, Elements are removed from the chaotic sequence to update the chaotic sequence, where Indicates the number of targets.

[0019] Preferably, it also includes: when personnel with different permissions request to view geographic images; returning the ciphertext of the level corresponding to the authorized personnel to the requesting terminal; the requesting terminal uses each group of chaotic mapping parameters of the level to decrypt the encryption results of the geographic images under each group of chaotic mapping parameters in the ciphertext, and obtains the decryption results of the geographic images under each group of chaotic mapping parameters; and taking the average of the decryption results of the geographic images under all groups of chaotic mapping parameters of the level as the final decryption result of the level.

[0020] The present invention only returns ciphertext at the corresponding level based on the permission level of different personnel, ensuring that low-privilege users cannot obtain high-privilege information, thereby protecting the security of sensitive data. The requesting terminal uses the chaotic mapping parameters of the level to gradually decrypt the ciphertext, and calculates the mean of the decryption results under each set of parameters as the final output. This not only retains the basic characteristics of the image, but also dynamically adjusts the degree of detail restoration according to the permission level. Low-privilege users can only view vague general information, while high-privilege users can obtain clearer image details. While meeting multi-level access requirements, it avoids the risk of excessive exposure of geographic image information.

[0021] The beneficial effects of the present invention are:

[0022] This invention constructs different levels of encryption keys based on role permissions, ensuring that high-privilege users can restore more detailed image information, while low-privilege users can only obtain vague approximate content. This meets multi-level access requirements and effectively protects sensitive information. Furthermore, the incremental key structure design ensures that the next level contains all parameters of the previous level, simplifying the key management process and enhancing the scalability of the system.

[0023] 2. The present invention uses a chaotic sequence to generate a position sequence for pixel selection, ensuring the randomness and uniformity of the pixel selection process, enhancing the anti-attack capability of the encryption result, and providing a high-quality random pixel point set for subsequent encoding.

[0024] 3. The present invention uses the AMBTC algorithm to encode the selected pixel points, which not only reduces the amount of data stored and transmitted, but also improves the overall encryption strength.

[0025] 4. This invention returns ciphertext at the corresponding level based on the viewing user's permissions. Low-privilege users can only view vague general information, while high-privilege users can obtain clearer details. By gradually decrypting the ciphertext using chaotic mapping parameters and calculating the mean of each group of decryption results as the final output, this method not only achieves permission control but also ensures the accuracy and consistency of the decryption results, effectively preventing unauthorized data leakage and providing comprehensive protection for the secure sharing and transmission of geographic images. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flow chart schematically illustrating a method for encrypting geographic information data in the present invention;

[0027] Figure 2 It is a schematic diagram showing the coding intention;

[0028] Figure 3 is a schematic diagram schematically showing a geographical image;

[0029] Figure 4 is a schematic diagram schematically showing the final decryption result of the first level;

[0030] Figure 5 is a schematic diagram schematically showing the final decryption result of the second level;

[0031] Figure 6 is a schematic diagram schematically showing the final decryption result of the fifth level;

[0032] Figure 7 FIG. 1 is a schematic diagram schematically showing the final decryption result of the 10th level. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the scope of protection of the present invention.

[0034] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0035] The embodiment of the present invention discloses a method for encrypting geographic information data. Figure 1 , including steps S001 to S004:

[0036] S001. Build encryption keys at different levels based on role permissions.

[0037] Specifically, according to the difference in role permissions, several different levels are divided, and the number of levels is recorded as The levels are numbered in ascending order of role permissions, with the first level corresponding to the lowest permissions, the The level corresponds to the highest authority.

[0038] Furthermore, setting Group chaos map parameters ,in Indicates the The bifurcation parameter in the group chaos map parameter, Indicates the The initial value parameter in the group chaos map parameter, Indicates the The number of dropout iterations in the group chaos map parameters, .

[0039] It should be noted that the chaotic mapping algorithm used in the present invention is the Logistic chaotic mapping. In the Logistic chaotic mapping algorithm, the value range of the initial value parameter is (0, 1). When the bifurcation parameter is in the range of (3.57, 4], the chaotic mapping system enters a chaotic state after at least 100 iterations. Therefore, the bifurcation parameter in the present invention is The value range is (3.57,4], the initial value parameter The value range is (0,1), and the number of iterations is discarded The value range is . Among them, the number of discarded iterations Used to follow the fork parameters And the initial value parameters When generating a chaotic sequence, The results of the first iteration are discarded to avoid the influence of non-chaotic results generated by the chaotic mapping system before it completely enters the chaotic state on the final chaotic sequence, ensuring that the generated chaotic sequence is in the chaotic region of the chaotic mapping system and has a high degree of randomness and unpredictability.

[0040] Furthermore, different numbers of groups of chaotic mapping parameters are allocated to different levels as encryption keys for different levels, specifically:

[0041] For the level, in Group Chaos Map Parameters Selection The chaotic map parameters are used as the first The encryption key of the level, where When the selected The group chaotic map parameters are Any of the group chaos map parameters group; when , selected The group chaos map parameters need to include the All group chaotic map parameters in the hierarchy's encryption key.

[0042] In other embodiments, implementers may also set the number of chaotic mapping parameters included in different levels according to actual implementation conditions.

[0043] S002. Obtain the geographic image to be encrypted.

[0044] It should be noted that the present invention performs encryption processing on grayscale images. When the geographic image to be encrypted is a grayscale image, step S003 is used to encrypt the geographic image. When the geographic image to be encrypted is an RGB image, each channel of the RGB image is regarded as a separate grayscale image and encrypted using step S003.

[0045] S003. Use each set of chaotic mapping parameters to encrypt the geographic image respectively to obtain ciphertexts at different levels.

[0046] Specifically, each set of chaotic mapping parameters is used to encrypt the geographic image respectively to obtain the encryption result of the geographic image under each set of chaotic mapping parameters, and the encryption results corresponding to all sets of chaotic mapping parameters contained in the encryption keys of different levels constitute the ciphertext of the corresponding level.

[0047] Specifically, the encryption process includes:

[0048] 1. For the Group( ) Chaotic mapping parameters, according to the bifurcation parameters And the initial value parameters , using the Logistic Chaotic Mapping algorithm to generate a length of sequence, the first The data are discarded and the remaining data constitute the chaotic sequences, where Indicates the The number of dropout iterations in the group chaos map parameters, Indicates the number of rows of geographic imagery, represents the number of columns of geographic images, Indicates the number of pixels in a geographic image.

[0049] 2. The first element in a chaotic sequence is denoted as ,Will As the target quantity, use Indicates that It should be noted that the value range of the elements in the chaotic sequence is (0,1), so for the target number is [2, ] is an integer in the range of . is a preset expansion multiple, which is used to limit the maximum number of pixels selected each time. In this embodiment, In other embodiments, the implementer can set The value of .

[0050] For example, assuming When the chaotic sequence is {0.21, 0.39, 0.98, 0.62, 0.17, 0.54, ...}, The first element of the chaotic sequence is 0.21, so the target number for .

[0051] It should be noted that chaotic sequences are highly random and unpredictable. It is generated based on a chaotic sequence, making it difficult for attackers to predict the number of pixels selected each time, thereby improving the security of subsequent encryption results.

[0052] 3. Get the The 2nd to 3rd chaotic sequences elements, multiply these elements by Then round up to get [1, ] range, the [1, ] constitutes a position sequence. Indicates the number of rows of geographic imagery, Represents the number of columns of the geographic image.

[0053] For example, assuming The chaotic sequence is {0.21, 0.39, 0.98, 0.62, 0.17, 0.54, ...}, and the target data , the geographic image size is 、 . No. The 2nd to 3rd chaotic sequences The elements are 0.39, 0.98, and 0.62 respectively. Among them, 0.39 multiplied by Then round up to 5; 0.98 multiplied by Then round up to 12; 0.62 multiplied by Then round up to 8. The position sequence is {5, 12, 8}.

[0054] It should be noted that chaotic sequences are highly random and unpredictable. Since the position sequence is generated based on the chaotic sequence, it is difficult for attackers to infer or predict the specific position sequence generated each time. Since the selection of subsequent pixel points depends on the position sequence, it is difficult for attackers to grasp the position of the selected pixel points, further improving the security of subsequent encryption results.

[0055] 4. Select without replacement in geographic images based on position sequence The selection process includes:

[0056] Select pixel points in the geographic image according to each element in the position sequence. Elements ( ), the first Elements are recorded as ,like and , then select the first pixel from the remaining pixels in the geographic image pixels; if and and , then select the first pixel from the remaining pixels in the geographic image pixels; if and and , then select the last pixel point from the remaining pixels in the geographic image; if , stop selecting; where % represents the remainder symbol, Indicates the number of remaining pixels in the geographic image. The number of selected pixels is recorded as .

[0057] For example, assuming that the remaining If the position sequence is {5,12,8}, then when the first selection is made, ,therefore , at this time, the 5th pixel point of the remaining 12 pixels in the geographic image is directly selected. After the 5th pixel point is selected, there are 11 pixels remaining in the geographic image; when selecting for the second time, , , then select the remaining 11 pixels in the geographic image Pixels, after the pixel is selected, there are 10 pixels left in the geographic image; when the third pixel is selected, , , at this time, the 8th pixel point among the remaining 10 pixels in the geographic image is selected.

[0058] Furthermore, the selected pixels as the pixels to be encoded.

[0059] 5. When When, right The pixels to be encoded are encoded using the Absolute Moment Block Truncation Coding (AMBTC) algorithm, resulting in a high quantization value, a low quantization value, and a binary mask. The high and low quantization values ​​are converted to binary numbers, and the binary mask, the binary number corresponding to the high quantization value, and the binary number corresponding to the low quantization value are concatenated in sequence to form the resulting binary string as the encoding result.

[0060] when The grayscale value of the pixel to be encoded is converted into a binary number, and the binary number corresponding to the grayscale value of the pixel to be encoded is used as the encoding result.

[0061] It should be noted that the AMBTC algorithm is an image compression algorithm based on block truncation coding (BTC). The core idea of ​​the AMBTC algorithm is to divide the image into small sub-blocks and calculate the mean grayscale value of all pixels in the sub-block. Pixels with grayscale values ​​greater than or equal to the mean are considered high-brightness pixels, while pixels with grayscale values ​​less than the mean are considered low-brightness pixels. A binary mask is generated based on the high-brightness and low-brightness pixels to record whether each pixel in the sub-block is a high-brightness pixel or a low-brightness pixel. When a pixel is a high-brightness pixel, the corresponding mask is 1, and when it is a low-brightness pixel, the corresponding mask is 0. The average grayscale value of all high-brightness pixels in the sub-block is calculated and rounded up. The result is used as the high quantization value. The average grayscale value of all low-brightness pixels in the sub-block is calculated and rounded up. The result is used as the low quantization value. The present invention regards all pixels to be encoded as pixels in a sub-block and uses the AMBTC algorithm to encode them.

[0062] For example, when , the average value of the gray scale values of all the to-be-encoded pixel points is For the to-be-encoded pixel point with the gray scale value of 89, it is a low-brightness pixel point, and the mask value thereof is 0; for the to-be-encoded pixel point with the gray scale value of 165, it is a high-brightness pixel point, and the mask value thereof is 1; for the to-be-encoded pixel point with the gray scale value of 99, it is a low-brightness pixel point, and the mask value thereof is 0; and the finally formed binary mask is 010. The average value of the gray scale values of all the high-brightness pixel points is 156, and the result of rounding up is 156, so the high quantization value is 156; the average value of the gray scale values of all the low-brightness pixel points is , and the result of rounding up is 94, so the low quantization value is 94.

[0063] In the first embodiment, the converting the high quantization value and the low quantization value into binary data respectively comprises:

[0064] Specifically, the high quantization value and the low quantization value are respectively converted into 8-bit binary numbers.

[0065] It should be noted that, since the range of the gray scale value is [0, 255], the range of the high quantization value obtained according to the average value of the gray scale values of the high-brightness pixel points is also [0, 255], and the range of the low quantization value obtained according to the average value of the gray scale values of the low-brightness pixel points is also [0, 255], and the decimal numbers in the range of [0, 255] can be represented by 8-bit binary, so the high quantization value and the low quantization value are respectively converted into 8-bit binary numbers in this embodiment.

[0066] For example, when the high quantization value is 156 and the low quantization value is 94, the corresponding 8-bit binary numbers are 10011100 and 01011110 respectively. If the binary mask is 010, the binary mask 010, the binary number 10011100 corresponding to the high quantization value, and the binary number 01011110 corresponding to the low quantization value are spliced together in order to obtain the encoding result 0101001110001011110.

[0067] In the second embodiment, the converting the high quantization value and the low quantization value into binary data respectively comprises:

[0068] Construct a coding table in which the coding objects in the coding table are each integer in the range [0, 255], the codewords for each coding object are 8-bit binary numbers, and the codewords for each coding object are different. For a high quantization value, the codeword of the coding object in the coding table that is equal to the high quantization value is used as the binary number corresponding to the high quantization value. For a low quantization value, the codeword of the coding object in the coding table that is equal to the low quantization value is used as the binary number corresponding to the low quantization value.

[0069] For example, when the high quantization value is 156 and the low quantization value is 94, the corresponding encoding table is as follows: Figure 2 As shown, the binary number corresponding to the high quantization value of 156 is 00000110, and the binary number corresponding to the low quantization value of 94 is 00001001. If the binarization mask is 010, the binarization mask 010, the binary number corresponding to the high quantization value 00000110, and the binary number corresponding to the low quantization value 00001001 are concatenated in order to obtain the encoded result 0100000011000001001.

[0070] It should be noted that the encoding table contains 256 encoding objects, each encoding object corresponds to a unique 8-bit binary number, and the 8-bit binary number also has 256 possible values. Since the mapping relationship between the encoding objects and the 8-bit binary numbers can be arranged arbitrarily, there are 256 possible combinations, which is about the order of magnitude of , far beyond the exhaustive scope of any classical or quantum computing capabilities. Attackers cannot restore the coding table through brute force guessing, thereby improving the complexity and security of the coding results.

[0071] It should be further explained that when When the grayscale value of the pixel to be encoded is converted into a binary number, the conversion method used is the same as the conversion method of the high quantization value and the low quantization value.

[0072] 6. The first chaotic sequence Elements from the Remove the chaotic sequence to achieve the An update of a chaotic sequence.

[0073] 7. Repeat steps 2 to 6 until there are no remaining pixels in the geographic image.

[0074] 8. All the encoding results are sequentially formed into a one-dimensional binary sequence as the first Encryption results of geographic images under group chaos mapping parameters.

[0075] S004. Decrypt the encryption result.

[0076] When a person with different permissions requests to view the geographic image, the ciphertext of the level corresponding to the permission person is returned to the request terminal of the permission person.

[0077] The request terminal decrypts the ciphertext of the level using each set of chaotic mapping parameters of the level to obtain the decryption results of the geographic image under each set of chaotic mapping parameters. The mean of the decryption results of the geographic image under all sets of chaotic mapping parameters of the level is taken as the final decryption result of the level, and the final decryption result of the level is displayed to the permission person for viewing.

[0078] The decryption process includes:

[0079] 1. The sequence number of the level corresponding to the permission of the person requesting to view the geographic image is recorded as For the first set of chaotic mapping parameters , according to the bifurcation parameter and the initial value parameter , a sequence of length is generated using the Logistic chaotic mapping algorithm, the first data in the sequence is discarded, and the remaining data constitutes the first chaotic sequence, where represents the number of discarded iterations in the first set of chaotic mapping parameters, represents the number of rows of the geographic image, represents the number of columns of the geographic image, represents the number of pixel points in the geographic image.

[0080] 2. The first element in the first chaotic sequence is recorded as , and is taken as the target number, using , where represents the ceiling symbol. Wherein is a preset expansion multiple.

[0081] 3. The second to elements in the first chaotic sequence are obtained, multiplied by and then rounded up to obtain integers in the range of [1, ], and the integers in the range of [1, ] constitute a position sequence. Wherein represents the number of rows of the geographic image, represents the number of columns of the geographic image.

[0082] 4. Select without replacement in geographic images based on position sequence The selection process includes:

[0083] Select pixel points in the geographic image according to each element in the position sequence. Elements ( ), the first Elements are recorded as ,like and , then select the first pixel from the remaining pixels in the geographic image pixels; if and and , then select the first pixel from the remaining pixels in the geographic image pixels; if and and , then select the last pixel point from the remaining pixels in the geographic image; if , stop selecting; where % represents the remainder symbol, Indicates the number of remaining pixels in the geographic image. The number of selected pixels is recorded as .

[0084] Furthermore, the selected pixels as pixels to be decoded.

[0085] 5. Response When the number is 1, the number is 1. Read the encrypted result of geographic image under the set chaotic mapping parameters bits, this The first 8 bits are used as the binary mask, and then the 16 bits are read. The first 8 bits of the 16 bits are used as the binary number corresponding to the high quantization value, and the last 8 bits of the 16 bits are used as the binary number corresponding to the low quantization value. The high quantization value is obtained according to the binary number corresponding to the high quantization value, and the low quantization value is obtained according to the binary number corresponding to the low quantization value. According to the binary mask, the high quantization value and the low quantization value, the AMBTC algorithm is used for decoding to obtain The decoded grayscale value of the pixel to be decoded. When the number is 1, the number is 1. Read the encrypted result of geographic image under the set chaotic mapping parameters bits as the binary number corresponding to the grayscale value of the pixel to be decoded, and the grayscale value of the pixel to be decoded is obtained according to the binary number corresponding to the grayscale value of the pixel to be decoded, as the decoded grayscale value of the pixel to be decoded.

[0086] For example, when The encryption result of the geographic image under the group chaotic mapping parameters is 0101001110001011110011100110…, When , the binary mask is 010, the binary number corresponding to the high quantization value is 10011100, and the binary number corresponding to the low quantization value is 01011110.

[0087] For example, when The encryption result of the geographic image under the group chaotic mapping parameters is 01001011. When , the binary number corresponding to the grayscale value of the pixel to be decoded is 01001011.

[0088] Furthermore, the step of obtaining a high quantization value according to a binary number corresponding to the high quantization value and obtaining a low quantization value according to a binary number corresponding to the low quantization value includes:

[0089] If the first embodiment in step S305 is used to convert the high quantization value and the low quantization value into binary data during encryption, then during decryption, when , convert the binary number corresponding to the high quantization value into decimal to obtain the high quantization value, and convert the binary number corresponding to the low quantization value into decimal to obtain the low quantization value. , then convert the binary number corresponding to the grayscale value of the pixel to be decoded into decimal to obtain the decoded grayscale value of the pixel to be decoded.

[0090] Exemplarily, when the binary number corresponding to the high quantization value is 10011100 and the binary number corresponding to the low quantization value is 01011110, the high quantization value is 156 and the low quantization value is 94.

[0091] Exemplarily, when the binary number corresponding to the grayscale value of the pixel to be decoded is 01001011, the decoded grayscale value of the pixel to be decoded is 75.

[0092] If the second embodiment in step S306 is used to convert the high quantization value and the low quantization value into binary data respectively during encryption, then during decryption, when , the coding object corresponding to the codeword with the same binary number as the high quantization value in the coding table is used as the high quantization value, and the coding object corresponding to the codeword with the same binary number as the low quantization value in the coding table is used as the low quantization value. , then obtain the coding object corresponding to the codeword with the same binary number corresponding to the grayscale value of the pixel to be decoded in the coding table as the decoded grayscale value of the pixel to be decoded.

[0093] For example, when the binary number corresponding to the high quantization value is 10011100 and the binary number corresponding to the low quantization value is 01011110, the coding table is as follows: Figure 2 As shown, the high quantization value is 238 and the low quantization value is 170.

[0094] For example, when the binary number corresponding to the grayscale value of the pixel to be decoded is 01001011, the encoding table is as follows: Figure 2 As shown, the decoded grayscale value of the pixel to be decoded is 193.

[0095] Furthermore, according to the binary mask, high quantization value and low quantization value, the AMBTC algorithm is used for decoding to obtain The decoded grayscale value of the pixel to be decoded includes:

[0096] Each mask value in the binary mask corresponds to a pixel to be decoded. When the mask value is 1, the decoded grayscale value of the corresponding pixel to be decoded is a high quantization value. When the mask value is 0, the decoded grayscale value of the corresponding pixel to be decoded is a low quantization value.

[0097] For example, when the binary mask is 010, the high quantization value is 156, and the low quantization value is 94, The decoded grayscale values ​​of the pixels to be decoded are 94, 94, and 156 respectively.

[0098] For example, when the binary mask is 11011, the high quantization value is 238, and the low quantization value is 170, The decoded grayscale values ​​of the pixels to be decoded are 238, 238, 170, 238, and 238 respectively.

[0099] 6. The first chaotic sequence Elements from the Remove the chaotic sequence to achieve the An update of a chaotic sequence.

[0100] when , from left to right, The encryption results of geographic images under the group chaotic mapping parameters are as follows: bits from the The encryption results of geographic images under the set of chaotic mapping parameters are eliminated to achieve the first Update of encryption results of geographic images under group chaotic mapping parameters.

[0101] when , from left to right, The encryption results of geographic images under the group chaotic mapping parameters are as follows: bits from the The encryption results of geographic images under the set of chaotic mapping parameters are eliminated to achieve the first Update of encryption results of geographic images under group chaotic mapping parameters.

[0102] 7. Repeat steps S402 to S406 until the The iteration stops when the encryption result of the geographic image under the group chaos mapping parameters is empty.

[0103] 8. The image composed of the decoded gray values ​​corresponding to all pixels in the geographic image is used as the first Decryption results of geographic images under group chaotic mapping parameters.

[0104] It should be noted that when the viewer's authority is low, the level corresponding to their authority contains fewer chaotic mapping parameters, resulting in a corresponding decrease in the number of times pixels in the geographic image are decoded. Due to insufficient decoding times, the decoded grayscale value of a pixel may be affected by the grayscale values ​​of other pixels to be encoded, resulting in deviations in the pixel's decoding result, further distorting the decrypted result of the geographic image. In this case, the viewer can only obtain general information about the geographic image, but cannot observe specific details. Conversely, when the viewer's authority is high, the level corresponding to their authority contains more chaotic mapping parameters, resulting in more pixels in the geographic image being decoded. This reduces the influence of the grayscale values ​​of other pixels to be encoded on the pixel's decoded grayscale value, making the pixel's decoding result closer to the pixel's original grayscale value. Consequently, the decrypted geographic image is closer to the original geographic image, better restoring the details of the geographic image, and allowing the viewer to view more details of the geographic image.

[0105] For example, when a geographic image such as Figure 3 As shown in the figure, the parameters of each group of chaotic mapping are {3.9, 0.112, 100}, {3.776, 0.028, 200}, {3.7, 0.321, 150}, {3.88, 0.423, 300}, {3.879, 0.567, 250}, {3.969, 0.609, 350}, {3.6932, 0.78, 400}, {3.811, 0.812, 450}, {3.841, 0.912, 500}, {3.912, 0.951, 550}, and the coding table is shown in the figure. Figure 2 When shown, the final decryption result of the first level is as follows Figure 4 As shown, the final decryption result of the second level is as follows Figure 5As shown, the final decryption result of the 5th level is as follows Figure 6 As shown, the final decryption result of the 10th level is as follows Figure 7 As shown. From the decryption results, we can see that Figure 4 Contains only Figure 3 The general information, the details are lost due to lower permissions, Figure 5 Compared to Figure 4 More details, Figure 6 On the basis of retaining more details, some features of geographic images are further restored. Figure 5 More clarity, Figure 7 It further restored Figure 3 The detailed information in the image shows the full picture of the geographic image under higher permissions. Through the above comparison, we can find that as the permission level increases, the decryption result gradually approaches the original geographic image. The decryption result under low permissions only shows rough information, while the decryption result under high permissions can show richer details, thus achieving effective hierarchical protection of sensitive information.

Claims

1. A method for encrypting geographic information data, characterized in that: include: Constructing different levels of encryption keys according to role permissions, wherein the encryption keys of the different levels include several groups of chaotic mapping parameters, and the encryption keys of the next level include all the groups of chaotic mapping parameters in the encryption keys of the previous level; Each set of chaotic mapping parameters is used to encrypt the geographic image respectively, and the encryption result of the geographic image under each set of chaotic mapping parameters is obtained. The encryption results corresponding to all sets of chaotic mapping parameters contained in the encryption keys of different levels constitute the ciphertext of the corresponding level. The encryption process includes: S1: For any set of chaotic mapping parameters, a chaotic sequence is generated according to the chaotic mapping parameters; S2: Select a number of pixels in the geographic image without replacement based on the chaotic sequence, including: The first element in the chaotic sequence is recorded as ,Will As the target quantity, use Indicates that Indicates the rounding symbol. It is a preset expansion multiple, which is used to limit the maximum number of pixels selected each time, the target number is [2, ] an integer in the range; The 2nd to 3rd in the chaotic sequence The elements are mapped to [1, ] within the range integers, the integers constitute a position sequence; among them, Indicates the number of rows of geographic imagery, The number of columns representing the geographic image; Select pixels in the geographic image according to each element in the position sequence, including: The first Elements are recorded as ,like and , then select the first pixel from the remaining pixels in the geographic image pixels; if and and , then select the first pixel from the remaining pixels in the geographic image pixels; if and and , then select the last pixel point from the remaining pixels in the geographic image; if , stop selecting; where % represents the remainder symbol, Indicates the number of remaining pixels in the geographic image; Performing AMBTC encoding on the selected pixel points to obtain a high quantization value, a low quantization value, and a binary mask; splicing the binary mask, the binary number corresponding to the high quantization value, and the binary number corresponding to the low quantization value together to obtain an encoding result; a method for obtaining the binary number corresponding to the high quantization value is: converting the high quantization value into an 8-bit number to obtain the binary number corresponding to the high quantization value; a method for obtaining the binary number corresponding to the low quantization value is: converting the low quantization value into an 8-bit number to obtain the binary number corresponding to the low quantization value; S3: Repeat S2 until all pixels in the geographic image have been selected and then stop the iteration, and all the encoding results constitute the encryption result of the geographic image under the chaotic mapping parameters.

2. The encryption processing method for geographic information data according to claim 1, characterized in that: The chaotic mapping parameters are ,in Indicates the The bifurcation parameter in the group chaos map parameter, Indicates the Initial value parameters in the group chaos map parameters, Indicates the Number of dropout iterations in the group chaos map parameters.

3. The encryption processing method for geographic information data according to claim 1, characterized in that: Generating a chaotic sequence according to chaotic mapping parameters includes: For the Group chaos mapping parameters, according to the bifurcation parameters And the initial value parameters , using the Logistic Chaotic Mapping algorithm to generate a length of sequence, the first The data are discarded and the remaining data constitute the chaotic sequences, where Indicates the The number of dropout iterations in the group chaos map parameters, Indicates the number of rows of geographic imagery, Represents the number of columns of the geographic image.

4. The encryption processing method for geographic information data according to claim 1, characterized in that: Perform AMBTC encoding on the selected pixel points to obtain high quantization value, low quantization value and binary mask, including: The selected pixels are used as the pixels to be encoded, and the mean of the grayscale values ​​of all the pixels to be encoded is calculated. The pixels to be encoded with grayscale values ​​greater than or equal to the mean are regarded as high-brightness pixels, and the pixels to be encoded with grayscale values ​​less than the mean are regarded as low-brightness pixels. When the pixel to be encoded is a high-brightness pixel, the mask is set to 1, otherwise, the mask is set to 0, and the masks corresponding to all the pixels to be encoded form a binary mask; the average value of the grayscale values ​​of all high-brightness pixels is rounded up as the high quantization value; the average value of the grayscale values ​​of all low-brightness pixels is rounded up as the low quantization value.

5. The encryption processing method for geographic information data according to claim 1, characterized in that: The method for obtaining the binary number corresponding to the high quantization value is: Construct a coding table, wherein the coding object in the coding table is each integer in the range [0, 255], the codeword of each coding object is an 8-bit binary number, and the codeword of each coding object is different; The codeword of the coding object equal to the high quantization value in the coding table is used as the binary number corresponding to the high quantization value; The method for obtaining the binary number corresponding to the low quantization value is: The codeword of the coding object that is equal to the low quantization value in the coding table is used as the binary number corresponding to the low quantization value.

6. The encryption processing method for geographic information data according to claim 1, characterized in that: The encryption process also includes: In response to each coded object, the first Elements are removed from the chaotic sequence to update the chaotic sequence, where Indicates the number of targets.

7. The encryption processing method for geographic information data according to claim 1, characterized in that: Also includes: When personnel with different clearances request to view geographic imagery; Return the ciphertext of the level corresponding to the authorized person to the requesting terminal; The requesting terminal uses each set of chaotic mapping parameters of this level to decrypt the encryption results of the geographic image under each set of chaotic mapping parameters in the ciphertext, and obtains the decryption results of the geographic image under each set of chaotic mapping parameters; the average of the decryption results of the geographic image under all sets of chaotic mapping parameters of this level is used as the final decryption result of this level.

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