Encryption processing method for geographic information data

Abstract

The invention belongs to the technical field of encryption transmission, and particularly relates to an encryption processing method for geographic information data, which comprises the following steps that: encryption keys of different hierarchies are constructed according to role authority, each layer of key comprises a plurality of groups of chaotic mapping parameters, and the next hierarchy comprises all parameters of the previous hierarchy. And encrypting the geographic image by using each group of chaotic mapping parameters, and forming a ciphertext of a corresponding hierarchy by using each group of results. The method specifically comprises the following steps: S1, generating a chaotic sequence; s2, selecting pixel points in the image without putting back based on the chaos sequence, performing AMBTC coding on the selected pixel points to obtain a high quantization value, a low quantization value and a binarization mask, and splicing corresponding binary numbers into a coding result; and S3, repeating the step S2 until all the pixels are selected, and summarizing encoding results to form an encryption result under the group of parameters. According to the method, authority management and chaotic characteristics are combined, hierarchical encryption of geographic images is realized, and statistical analysis attacks and brute force attack attacks can be resisted.

Description

Technical Field

[0001] The present invention relates to the field of encryption transmission technology. More specifically, the present invention relates to a method for encrypting and processing 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 in the secure transmission and storage of data.

[0003] In practical applications, encryption algorithms such as AES and DES have certain limitations. Encryption algorithms such as AES and DES mainly focus on the overall confidentiality of data, emphasizing that the original data is completely encrypted and ensuring that it cannot be accessed by unauthorized users. However, such algorithms do not consider the hierarchical access requirements under different user permissions. In the field of geographic information, image data often contains multiple levels of sensitive information, such as terrain features, locations of key facilities, etc., and different levels of detail need to be provided according to the user's permission level. However, traditional AES and DES encryption algorithms cannot directly perform differential processing on the permissions of personnel, and all users obtain the complete original data after decryption, which may expose unnecessary sensitive information.

[0004] To solve this problem, image encryption technology based on chaotic mapping has gradually become a research hotspot. Chaotic mapping uses simple mathematical formulas to generate highly random and unpredictable sequences, which can achieve efficient encryption operations while ensuring security. However, image encryption based on chaotic mapping fails to combine with a permission management mechanism and cannot provide differential decryption results according to the permission levels of different users. This limitation makes it difficult for image encryption based on chaotic mapping to meet the requirements of hierarchical access in the field of geographic information in practical applications. Summary of the Invention

[0005] To solve the above technical problem that the existing encryption algorithms cannot directly perform differential processing on the permissions of personnel and may expose sensitive information in geographic information data, the present invention provides a method for encrypting and processing geographic information data, including: Construct encryption keys at different levels according to the role permissions. The encryption keys at different levels include several groups of chaotic mapping parameters, and the encryption key at the next level includes all groups of chaotic mapping parameters in the encryption key at the previous level. Use each group of chaotic mapping parameters to encrypt the geographical image respectively to obtain the encryption result of the geographical image under each group of chaotic mapping parameters, and form the ciphertext of the corresponding level with the encryption results corresponding to all groups of chaotic mapping parameters included in the encryption keys at different levels. Among them, the encryption process includes: S1: For any group of chaotic mapping parameters, generate a chaotic sequence according to the chaotic mapping parameters; S2: Select several pixel points from the geographical image without replacement according to the chaotic sequence; perform AMBTC encoding on the selected pixel points to obtain a high quantization value, a low quantization value, and a binarization mask; splice the binarization mask, the binary number corresponding to the high quantization value, and the binary number corresponding to the low quantization value together to obtain a coding result; S3: Repeat S2 until all pixels in the geographical image have been selected and stop the iteration, and form the encryption result of the geographical image under the chaotic mapping parameters with all coding results.

[0006] The present invention constructs a hierarchical encryption key by combining role permissions and chaotic mapping parameters, realizing multi-level security protection of geographical images. The encryption keys at different levels contain an increasing number of groups of chaotic mapping parameters, ensuring that high-privilege users can restore more detailed image information, while low-privilege users can only obtain vague general content, effectively meeting the hierarchical access requirements. In the encryption process, pixel points are selected using the randomness and unpredictability of the chaotic sequence, and data is encoded in combination with the AMBTC algorithm, improving the security of the encryption result. Finally, by splicing the binarization mask and the binary numbers corresponding to the quantization values to generate the ciphertext, the anti-attack ability of the encryption result is further enhanced, while retaining the core features of the geographical image, achieving a balance between security and efficiency.

[0007] Preferably, the chaotic mapping parameter is , where represents the bifurcation parameter in the th group of chaotic mapping parameters, represents the initial value parameter in the th group of chaotic mapping parameters, represents the discarded iteration times in the th group of chaotic mapping parameters.

[0008] Preferably, the generating of the chaotic sequence according to the chaotic mapping parameters includes: for the th group of chaotic mapping parameters, according to the bifurcation parameter and the initial value parameter , use the Logistic chaotic mapping algorithm to generate a sequence with a length of , and for the first Some data is discarded, and the remaining data forms the th chaotic sequence, where represents the number of discarded iterations in the th group of chaotic mapping parameters, represents the number of rows of the geographical image, represents the number of columns of the geographical image.

[0009] Preferably, the step of randomly selecting several pixel points from the geographical image according to the chaotic sequence includes: mapping the first element in the chaotic sequence to an integer within the range of [2, , denoted as the target quantity, represented by ; mapping the 2nd to the th elements in the chaotic sequence to integers within the range of [1, , and forming a position sequence with the integers; where is a preset expansion multiple, represents the number of rows of the geographical image, represents the number of columns of the geographical image; and selecting pixel points from the geographical image in sequence according to each element in the position sequence.

[0010] The present invention generates a position sequence through a chaotic sequence and uses it for pixel point selection, which has high randomness and flexibility. First, the first element of the chaotic sequence is mapped to the target quantity, so that the number of pixel points selected each time is not fixed, avoiding the regular loopholes that may be brought by fixed quantity selection. Then, using the position sequence generated by the chaotic sequence, due to the randomness and unpredictability of the chaotic sequence, it is difficult for an attacker to infer the specific pixel point positions or quantities selected, thus significantly improving the anti-attack ability of the encryption algorithm. At the same time, the non-replacement selection method ensures that each pixel point is only selected once, further enhancing the uniformity and reliability of the encryption result.

[0011] Preferably, the step of selecting pixel points from the geographical image in sequence according to each element in the position sequence includes: denoting the th element in the position sequence as , if and , then select the th pixel point from the remaining pixel points in the geographical image; if and and , then select the th pixel point from the remaining pixel points in the geographical image; if and and , then select the last pixel point from the remaining pixel points in the geographical image; if , stop selecting; where % represents the modulo symbol, represents the number of remaining pixel points in the geographical image.

[0012] Preferably, perform AMBTC encoding on the selected pixel points to obtain a high quantization value, a low quantization value, and a binarization mask, including: taking the selected pixel points as the pixel points to be encoded, calculating the average value of the grayscale values of all the pixel points to be encoded, taking the pixel points to be encoded with grayscale values greater than or equal to the average value as high-brightness pixel points, and taking the pixel points to be encoded with grayscale values less than the average value as low-brightness pixel points; when the pixel point to be encoded belongs to the high-brightness pixel points, set the mask to 1, otherwise, set the mask to 0, and form a binarization mask with the masks corresponding to all the pixel points to be encoded; taking the result of rounding up the average value of the grayscale values of all the high-brightness pixel points as the high quantization value; taking the result of rounding up the average value of the grayscale values of all the low-brightness pixel points as the low quantization value.

[0013] The present invention efficiently encodes the selected pixel points through the AMBTC algorithm, reduces the data volume while retaining the main features of the image, not only reduces the data volume for storage and transmission, but also uses the quantization value and the mask to achieve a concise description of the image content. At the same time, the AMBTC algorithm can restore an approximate pixel value distribution according to the mask and the quantization value during the reconstruction process, ensuring that the decryption result is visually consistent with the original image. The present invention combines the advantages of compression and encryption, improves the processing efficiency while ensuring the security of geographical image information.

[0014] Preferably, the method for obtaining the binary number corresponding to the high quantization value is: converting the high quantization value into an octal 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 octal number to obtain the binary number corresponding to the low quantization value.

[0015] Preferably, the method for obtaining the binary number corresponding to the high quantization value is: constructing an encoding table, where the encoding objects in the encoding table are each integer within [0, 255], the codewords of each encoding object are 8-bit binary numbers, and the codewords of each encoding object are all different; taking the codeword of the encoding object equal to the high quantization value in the encoding table 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 codeword of the encoding object equal to the low quantization value in the encoding table as the binary number corresponding to the low quantization value.

[0016] By constructing a coding table, the present invention maps high quantization values and low quantization values to unique 8-bit binary numbers, significantly enhancing the security and complexity of the coding results. 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 arranged arbitrarily, there are theoretically 256! possible combinations, far beyond the exhaustive range of classical or quantum computing capabilities, making it impossible for attackers to restore the coding table through brute-force guessing, thus effectively preventing the reverse analysis of the binary representation of quantization values. At the same time, the 8-bit binary codewords of fixed length ensure the consistency of the data format, avoiding problems such as the loss of leading zeros and facilitating the efficient implementation of subsequent encryption and decryption operations.

[0017] Preferably, the encryption process further includes: in response to obtaining each coding object, removing the first elements from the chaotic sequence to update the chaotic sequence, where represents the target quantity.

[0018] Preferably, it further includes: when personnel with different permissions request to view a geographical image; returning the ciphertext of the corresponding level of the permission personnel to the requesting terminal; the requesting terminal decrypts the encryption results of the geographical image under each group of chaotic mapping parameters in the ciphertext using each group of chaotic mapping parameters at this level to obtain the decryption results of the geographical image under each group of chaotic mapping parameters; taking the average value of the decryption results of the geographical image under all groups of chaotic mapping parameters at this level as the final decryption result at this level.

[0019] According to the permission levels of different personnel, the present invention only returns the ciphertext of the corresponding level, ensuring that low-permission users cannot obtain high-permission information, thereby protecting the security of sensitive data. The requesting terminal gradually decrypts the ciphertext using the chaotic mapping parameters at this level and calculates the average value of the decryption results under each group of parameters as the final output, which not only retains the basic features of the image but also dynamically adjusts the degree of detail restoration according to the permission level. Low-permission users can only view vague general information, while high-permission users can obtain clearer image details, meeting the multi-level access requirements while avoiding the risk of excessive exposure of geographical image information.

[0020] The beneficial effects of the present invention are as follows: 1. The present invention constructs encryption keys at different levels based on role permissions, ensuring that high-permission users can restore more detailed image information, while low-permission users can only obtain vague general content, meeting the multi-level access requirements and effectively protecting sensitive information. At the same time, the incremental key structure design ensures that the next level contains all the parameters of the previous level, simplifies the key management process, and enhances the scalability of the system.

[0021] 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 ability of the encryption result, and providing a high-quality set of random pixels for subsequent coding.

[0022] 3. The present invention uses the AMBTC algorithm to encode the selected pixels, which not only reduces the amount of data stored and transmitted, but also improves the overall encryption strength.

[0023] 4. The present invention returns the ciphertext at the corresponding level according to the permissions of the viewers. Low-permission users can only view vague general information, while high-permission users can obtain clearer detailed content. By gradually decrypting the ciphertext using the chaotic mapping parameters and calculating the mean of each group of decryption results as the final output, both permission control is achieved and the accuracy and consistency of the decryption result are ensured, effectively preventing unauthorized data leakage and providing comprehensive protection for the secure sharing and transmission of geographical images. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flowchart schematically showing a method for encrypting and processing geographical information data in the present invention; Figure 2 is a schematic diagram showing the coding representation; Figure 3 is a schematic diagram showing a geographical image; Figure 4 is a schematic diagram showing the final decryption result of the first level; Figure 5 is a schematic diagram showing the final decryption result of the second level; Figure 6 is a schematic diagram showing the final decryption result of the fifth level; Figure 7 is a schematic diagram showing the final decryption result of the tenth level. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0026] Next, the specific embodiments of the present invention will be described in detail in conjunction with the accompanying drawings.

[0027] An embodiment of the present invention discloses a method for encrypting and processing geographical information data, referring to Figure 1 , including steps S001 to S004: S001. Construct encryption keys of different levels according to the role permissions.

[0028] Specifically, according to the differences in role permissions, divide into several different levels, and record the number of levels as . Number the levels in ascending order of role permissions, where the first level corresponds to the lowest permission, and the th level corresponds to the highest permission.

[0029] Furthermore, set groups of chaotic mapping parameters , where represents the bifurcation parameter in the th group of chaotic mapping parameters, represents the initial value parameter in the th group of chaotic mapping parameters, represents the discarded iteration number in the th group of chaotic mapping parameters, .

[0030] 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], after at least 100 iterations, the chaotic mapping system enters the chaotic state. Therefore, in the present invention, the value range of the bifurcation parameter is (3.57, 4], the value range of the initial value parameter is (0, 1), and the value range of the discarded iteration number is . Among them, the discarded iteration number is used to discard the results of the first iterations when generating the chaotic sequence according to the bifurcation parameter and the initial value parameter , so as to avoid the influence of the non-chaotic results generated when the chaotic mapping system has not fully entered the chaotic state on the final chaotic sequence, and ensure that the generated chaotic sequence is in the chaotic region of the chaotic mapping system, with high randomness and unpredictability.

[0031] Furthermore, allocate different numbers of groups of chaotic mapping parameters to different levels as the encryption keys of different levels. Specifically: For the th level, select groups of chaotic mapping parameters from groups of chaotic mapping parameters as the encryption key of the th level. Among them, when , the selected The chaotic mapping parameter groups are Any of the chaotic mapping parameter groups groups; when , the selected groups of chaotic mapping parameters need to include all the groups of chaotic mapping parameters in the encryption key at the level.

[0032] In other embodiments, the implementer can also set the number of chaotic mapping parameters included in different levels according to the actual implementation situation.

[0033] S002. Obtain the geographical image to be encrypted.

[0034] It should be noted that the present invention performs encryption processing on grayscale images. When the geographical image to be encrypted is a grayscale image, the geographical image is encrypted using step S003. When the geographical 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.

[0035] S003. Encrypt the geographical image using each group of chaotic mapping parameters respectively to obtain ciphertexts at different levels.

[0036] Specifically, encrypt the geographical image using each group of chaotic mapping parameters respectively to obtain the encryption result of the geographical image under each group of chaotic mapping parameters. The encryption results corresponding to all the groups of chaotic mapping parameters included in the encryption keys at different levels form the ciphertext at the corresponding level.

[0037] Specifically, the encryption process includes: 1. For the th group ( ) of chaotic mapping parameters, according to the bifurcation parameter and the initial value parameter , generate a sequence with a length of using the Logistic chaotic mapping algorithm. Discard the first data in the sequence, and the remaining data forms the th chaotic sequence. Among them, represents the discard iteration times in the th group of chaotic mapping parameters, represents the number of rows of the geographical image, represents the number of columns of the geographical image, represents the number of pixel points in the geographical image.

[0038] 2. Denote the first element in the th chaotic sequence as , and use as the target quantity, denoted by , where Denotes the ceiling symbol. It should be noted that the value range of elements in the chaotic sequence is (0, 1), then for the target quantity is an integer within the range of [2, . Among them, is a preset expansion multiple, which is used to limit the maximum number of pixel points selected each time subsequently. In this embodiment, , in other embodiments, the implementer can set the value according to the actual implementation situation.

[0039] Exemplarily, assuming that the th chaotic sequence is {0.21, 0.39, 0.98, 0.62, 0.17, 0.54,...}, for the first element 0.21 in the th chaotic sequence, the target quantity is .

[0040] It should be noted that the chaotic sequence has high randomness and unpredictability. Since the target quantity is generated based on the chaotic sequence, it makes it difficult for attackers to predict the number of pixel points selected each time, improving the security of the subsequent encryption result.

[0041] 3. Obtain the 2nd to the th elements in the th chaotic sequence, multiply these elements by respectively and then take the ceiling to obtain integers within the range of [1, . The integers within the range of [1, form a position sequence. Among them, represents the number of rows of the geographical image, represents the number of columns of the geographical image.

[0042] Exemplarily, assume that the th chaotic sequence is {0.21, 0.39, 0.98, 0.62, 0.17, 0.54,...}, the target data , the size of the geographical image is , . The 2nd to the th elements in the th chaotic sequence are 0.39, 0.98, 0.62 respectively. Among them, 0.39 multiplied by and then taking the ceiling, we get 5; 0.98 multiplied by and then taking the ceiling, we get 12; 0.62 multiplied by Then round up to get 8. The position sequence is {5, 12, 8}.

[0043] It should be noted that the chaotic sequence has high randomness and unpredictability. 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 master the positions of the selected pixel points, further enhancing the security of the subsequent encryption results.

[0044] 4. Select pixel points in the geographical image in a non-replacement manner. The selection process specifically includes: Select pixel points in the geographical image according to each element in the position sequence in turn. For the th element ( ) in the position sequence, denote the th element in the position sequence as . If and , then select the th pixel point among the remaining pixel points in the geographical image; if and and , then select the th pixel point among the remaining pixel points in the geographical image; if and and , then select the last pixel point among the remaining pixel points in the geographical image; if , stop the selection; where % represents the modulo symbol, represents the number of remaining pixel points in the geographical image. Denote the number of selected pixel points as .

[0045] Exemplarily, assume there are remaining pixel points in the geographical image. If the position sequence is {5, 12, 8}, then for the first selection, , so , at this time, directly select the 5th pixel point among the remaining 12 pixel points in the geographical image. After the 5th pixel point is selected, there are 11 pixel points remaining in the geographical image; for the second selection, , , at this time, select the th pixel point among the remaining 11 pixel points in the geographical image. After this pixel point is selected, there are 10 pixel points remaining in the geographical image; for the third selection, , , at this time, select the 8th pixel point among the remaining 10 pixel points in the geographical image.

[0046] Further, the selected pixel points are used as the pixel points to be encoded.

[0047] 5. When holds, the pixel points to be encoded are encoded using the Absolute Moment Block Truncation Coding (AMBTC) algorithm to obtain a high quantization value, a low quantization value, and a binary mask. The high quantization value and the low quantization value are respectively converted into 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, and the obtained binary string is used as an encoding result.

[0048] When holds, the pixel points to be encoded are not encoded. The gray value of the pixel points to be encoded is converted into a binary number, and the binary number corresponding to the gray value of the pixel points to be encoded is used as the encoding result.

[0049] 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, calculate the mean value of the gray values of all pixel points in the sub-block, and regard the pixel points with gray values greater than or equal to the mean value in the sub-block as high-brightness pixel points, and regard the pixel points with gray values less than the mean value in the sub-block as low-brightness pixel points. A binary mask is generated according to the high-brightness pixel points and the low-brightness pixel points to record whether each pixel point in the sub-block belongs to a high-brightness pixel point or a low-brightness pixel point. When the pixel point belongs to a high-brightness pixel point, the corresponding mask is 1, and when the pixel point belongs to a low-brightness pixel point, the corresponding mask is 0. Calculate the average value of the gray values of all high-brightness pixel points in the sub-block, and round up the average value to obtain the high quantization value. Calculate the average value of the gray values of all low-brightness pixel points in the sub-block, and round up the average value to obtain the low quantization value. In the present invention, all the pixel points to be encoded are regarded as the pixel points in a sub-block and encoded using the AMBTC algorithm.

[0050] Exemplarily, when , and the gray values of the pixel points to be encoded are 89, 156, and 99 respectively, the mean value of the gray values of all the pixel points to be encoded is . For the pixel point to be encoded with a gray value of 89, , then this pixel point is a low-brightness pixel point, and its mask value is 0; for the pixel point to be encoded with a gray value of 165, , then this pixel is a high - brightness pixel, and its mask value is 1; for the pixel to be encoded with a gray value of 99, , then this pixel is a low - brightness pixel, and its mask value is 0; then the finally formed binary mask is 010. The average value of the gray values of all high - brightness pixels is 156, and the result of rounding up is 156, so the high quantization value is 156; the average value of the gray values of all low - brightness pixels is , and the result of rounding up is 94, so the low quantization value is 94.

[0051] In the first embodiment, the converting the high quantization value and the low quantization value into binary data respectively includes: Specifically, convert the high quantization value and the low quantization value into 8 - bit numbers respectively.

[0052] It should be noted that since the range of gray values is [0, 255], the range of the high quantization value obtained according to the average value of the gray values of high - brightness pixels is also [0, 255], and the range of the low quantization value obtained according to the average value of the gray values of low - brightness pixels is also [0, 255]. And the decimal numbers in the range of [0, 255] can be represented by 8 - bit binary numbers. Therefore, in this embodiment, the high quantization value and the low quantization value are respectively converted into 8 - bit numbers.

[0053] Exemplarily, 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, splicing 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 together in order, the encoding result 0101001110001011110 is obtained.

[0054] In the second embodiment, the converting the high quantization value and the low quantization value into binary data respectively includes: Construct an encoding table. The encoding objects in the encoding table are each integer within [0, 255]. The codewords of each encoding object are 8 - bit binary numbers, and the codewords of each encoding object are all different. For the high quantization value, use the codeword of the encoding object equal to this high quantization value in the encoding table as the binary number corresponding to this high quantization value. For the low quantization value, use the codeword of the encoding object equal to this low quantization value in the encoding table as the binary number corresponding to this low quantization value.

[0055] Exemplarily, when the high quantization value is 156 and the low quantization value is 94, the corresponding encoding table is as Figure 2When shown as above, 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 00000110 corresponding to the high quantization value, and the binary number 00001001 corresponding to the low quantization value are concatenated in sequence to obtain the encoding result 0100000011000001001.

[0056] It should be noted that the encoding table contains 256 encoding objects, each encoding object corresponding to a unique 8-bit binary number, and there are also 256 possible values for the 8-bit binary number. Since the mapping relationship between the encoding objects and the 8-bit binary numbers can be arranged arbitrarily, there are 256! possible combination methods, and the order of magnitude is about , far exceeding the exhaustive range of any classical or quantum computing capabilities. Attackers cannot restore the encoding table by brute-force guessing, thus enhancing the complexity and security of the encoding result.

[0057] It should be further noted that when , the conversion method used to convert the grayscale value of the pixel point to be encoded into a binary number is the same as the conversion method for the high quantization value and the low quantization value.

[0058] 6. Remove the first elements from the th chaotic sequence from the th chaotic sequence to update the th chaotic sequence.

[0059] 7. Repeat steps 2 to 6 until there are no remaining pixel points in the geographical image and stop the iteration.

[0060] 8. Combine all the obtained encoding results in sequence to form a one-dimensional binary sequence, which is used as the encryption result of the geographical image under the th group of chaotic mapping parameters.

[0061] S004. Decrypt the encryption result.

[0062] When personnel with different permissions request to view the geographical image, the ciphertext of the corresponding level of this permission personnel is returned to the request terminal of this permission personnel.

[0063] The request terminal decrypts the ciphertext of this level using the groups of chaotic mapping parameters of this level to obtain the decryption results of the geographical image under the groups of chaotic mapping parameters. The average value of the decryption results of the geographical image under all groups of chaotic mapping parameters of this level is used as the final decryption result of this level, and the final decryption result of this level is displayed for this permission personnel to view.

[0064] Among them, the decryption process includes: 1. Denote the serial number of the level corresponding to the permission of the person requesting to view the geographical image as , for the th group ( ) of chaotic mapping parameters, according to the bifurcation parameter and the initial value parameter , use the Logistic chaotic mapping algorithm to generate a sequence of length . Discard the first data in the sequence, and the remaining data constitutes the th chaotic sequence. Among them, represents the discarded iteration number in the th group of chaotic mapping parameters, represents the number of rows of the geographical image, represents the number of columns of the geographical image, represents the number of pixel points in the geographical image.

[0065] 2. Denote the first element in the th chaotic sequence as , and use as the target quantity, denoted by , where represents the ceiling symbol. Among them, is a preset expansion multiple.

[0066] 3. Obtain the 2nd to the th elements in the th chaotic sequence, multiply these elements by and then take the ceiling to obtain integers in the range of [1, . The integers in the range of [1, constitute the position sequence. Among them, represents the number of rows of the geographical image, represents the number of columns of the geographical image.

[0067] 4. Select pixel points from the geographical image in a non-replacement manner according to the position sequence. The selection process specifically includes: Select pixel points from the geographical image in sequence according to each element in the position sequence. For the th element ( ) in the position sequence, denote the th element in the position sequence as . If and , then select the pixel; If and and , then select the th pixel from the remaining pixels in the geographical image; If and and , then select the last pixel from the remaining pixels in the geographical image; If , stop selecting; where % represents the modulo operator, represents the number of remaining pixels in the geographical image. Denote the number of selected pixels as .

[0068] Furthermore, take the selected pixels as the pixels to be decoded.

[0069] 5. When responding to , in the order from left to right, read bits from the encryption result of the geographical image under the th group of chaotic mapping parameters. Take these bits as the binarization mask, then continue to read 16 bits. Take the first 8 bits of the read 16 bits as the binary number corresponding to the high quantization value, and take the last 8 bits of the read 16 bits as the binary number corresponding to the low quantization value. Obtain the high quantization value according to the binary number corresponding to the high quantization value, and obtain the low quantization value according to the binary number corresponding to the low quantization value. Decode using the AMBTC algorithm according to the binarization mask, high quantization value, and low quantization value to obtain the decoded gray value of pixels to be decoded. When responding to , in the order from left to right, read bits from the encryption result of the geographical image under the th group of chaotic mapping parameters as the binary number corresponding to the gray value of the pixel to be decoded. Obtain the gray value of the pixel to be decoded according to the binary number corresponding to the gray value of the pixel to be decoded as the decoded gray value of the pixel to be decoded.

[0070] Exemplarily, when the encryption result of the geographical image under the th group of chaotic mapping parameters is 0101001110001011110011100110…, , the binarization 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.

[0071] Exemplarily, when the The encryption result of the geographical image under a set of chaotic mapping parameters is 01001011. When , the binary number corresponding to the gray value of the pixel point to be decoded is 01001011.

[0072] Furthermore, obtaining the high quantization value according to the binary number corresponding to the high quantization value and obtaining the low quantization value according to the binary number corresponding to the low quantization value includes: 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. When , then convert the binary number corresponding to the gray value of the pixel point to be decoded into decimal to obtain the decoded gray value of the pixel point to be decoded.

[0073] 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.

[0074] Exemplarily, when the binary number corresponding to the gray value of the pixel point to be decoded is 01001011, the decoded gray value of the pixel point to be decoded is 75.

[0075] If the second embodiment in step S306 is used to convert the high quantization value and the low quantization value into binary data during encryption, then during decryption, when , use the coding object corresponding to the codeword in the coding table that is the same as the binary number corresponding to the high quantization value as the high quantization value, and use the coding object corresponding to the codeword in the coding table that is the same as the binary number corresponding to the low quantization value as the low quantization value. When , then obtain the coding object corresponding to the codeword in the coding table that is the same as the binary number corresponding to the gray value of the pixel point to be decoded as the decoded gray value of the pixel point to be decoded.

[0076] Exemplarily, when the binary number corresponding to the high quantization value is 10011100, the binary number corresponding to the low quantization value is 01011110, and the coding table is as Figure 2 shown, the high quantization value is 238 and the low quantization value is 170.

[0077] Exemplarily, when the binary number corresponding to the gray value of the pixel point to be decoded is 01001011, and the coding table is as Figure 2 shown, the decoded gray value of the pixel point to be decoded is 193.

[0078] Furthermore, according to the binarization mask, the high quantization value, and the low quantization value, use the AMBTC algorithm for decoding to obtain The decoded grayscale value of a pixel to be decoded, including: 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 the high quantization value, and when the mask value is 0, the decoded grayscale value of the corresponding pixel to be decoded is the low quantization value.

[0079] Exemplarily, 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.

[0080] Exemplarily, 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.

[0081] 6. Remove the first elements from the first chaotic sequence from the nd chaotic sequence to update the nd chaotic sequence.

[0082] When , in the order from left to right, remove the first bit positions from the encryption result of the geographical image under the rd set of chaotic mapping parameters from the encryption result of the geographical image under the th set of chaotic mapping parameters to update the encryption result of the geographical image under the th set of chaotic mapping parameters.

[0083] When , in the order from left to right, remove the first bit positions from the encryption result of the geographical image under the th set of chaotic mapping parameters from the encryption result of the geographical image under the th set of chaotic mapping parameters to update the encryption result of the geographical image under the th set of chaotic mapping parameters.

[0084] 7. Repeat steps S402 to S406 until the encryption result of the geographical image under the th set of chaotic mapping parameters is empty and stop the iteration.

[0085] 8. Use the image formed by the decoded grayscale values corresponding to all the pixels in the geographical image as the decryption result of the geographical image under the th set of chaotic mapping parameters.

[0086] It should be noted that when the permissions of the viewer are relatively low, the number of chaotic mapping parameters included in the level corresponding to their permissions is small, resulting in a corresponding reduction in the number of times the pixel points in the geographical image are decoded. Due to insufficient decoding times, the decoded gray values of the pixel points may be affected by the gray values of other pixel points to be encoded that are encoded together, resulting in deviations in the decoded results of the pixel points, thereby making the decryption result of the geographical image more distorted. At this time, the viewer can only obtain the general information of the geographical image and cannot observe the specific details. On the contrary, when the viewer has higher permissions, the number of chaotic mapping parameters included in the level corresponding to their permissions is larger, enabling more times of decoding of the pixel points in the geographical image, thereby reducing the influence of the gray values of other pixel points to be encoded that are encoded together on the decoded gray values of the pixel points, making the decoded results of the pixel points closer to the original gray values of the pixel points, and further making the decryption result of the geographical image closer to the original geographical image. The details of the geographical image are better restored, and the viewer can view more details of the geographical image.

[0087] Exemplarily, when the geographical image is as Figure 3 shown, and the sets of chaotic mapping parameters are respectively {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 as Figure 2 shown, the final decryption result of the first level is as Figure 4 shown, the final decryption result of the second level is as Figure 5 shown, the final decryption result of the fifth level is as Figure 6 shown, and the final decryption result of the tenth level is as Figure 7 shown. It can be seen from the decryption results that Figure 4 only contains the Figure 3 general information, and the detailed part is lost due to the lower permissions. Figure 5 Compared with Figure 4 it has more detailed information. Figure 6 On the basis of retaining more details, some features of the geographical image are further restored. Compared with Figure 5 it is clearer. Figure 7 further restores Figure 3The detailed information therein shows the overall picture of the geographical image under a higher permission level. Through the above comparison, it can be found that as the permission level increases, the decryption result gradually approaches the original geographical image. The decryption result under a low permission level only shows rough information, while the decryption result under a high permission level can present richer detailed content, thus achieving effective hierarchical protection of sensitive information.

Claims

1. A method for encrypting geographical information data, characterized in that, Including: Construct encryption keys at different levels according to the role permissions. The encryption keys at different levels include several groups of chaotic mapping parameters, and the encryption key at the next level includes all the groups of chaotic mapping parameters in the encryption key at the previous level; Use each group of chaotic mapping parameters to encrypt the geographical image respectively, obtain the encryption results of the geographical image under each group of chaotic mapping parameters, and form the ciphertext of the corresponding level from the encryption results corresponding to all the groups of chaotic mapping parameters included in the encryption keys at different levels; Among them, the encryption process includes: S1: For any group of chaotic mapping parameters, generate a chaotic sequence according to the chaotic mapping parameters; S2: Select several pixel points from the geographical image without replacement according to the chaotic sequence; perform AMBTC encoding on the selected pixel points to obtain a high quantization value, a low quantization value, and a binarization mask; splice the binarization 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; S3: Repeat S2 until all pixels in the geographical image have been selected and stop the iteration, and form the encryption result of the geographical image under the chaotic mapping parameters from all the encoding results.

2. The encryption processing method for geographic information data according to claim 1, wherein The chaotic mapping parameters are , where represents the bifurcation parameter in the th group of chaotic mapping parameters, represents the initial value parameter in the th group of chaotic mapping parameters, represents the discarded iteration number in the th group of chaotic mapping parameters.

3. The encryption processing method for geographic information data according to claim 1, characterized in that, The generating of the chaotic sequence according to the chaotic mapping parameters includes: For the group of chaotic mapping parameters, according to the bifurcation parameter and the initial value parameter , use the Logistic chaotic mapping algorithm to generate a sequence with a length of . Discard the first data in the sequence, and the remaining data form the th chaotic sequence. Among them, represents the discarded iteration times in the th group of chaotic mapping parameters, represents the number of rows of the geographical image, represents the number of columns of the geographical image.

4. A method for encrypting and processing geographical information data according to claim 1, characterized in that, The selecting of several pixel points from the geographical image without replacement according to the chaotic sequence includes: Map the first element in the chaotic sequence to an integer within the range of [2, , denoted as the target quantity, and use to represent it; map the 2nd to the th elements in the chaotic sequence to integers within the range of [1, , and form a position sequence with the integers; where is a preset expansion multiple, represents the number of rows of the geographical image, and represents the number of columns of the geographical image. Select pixel points in the geographical image in sequence according to each element in the position sequence.

5. The encryption processing method for geographic information data according to claim 4, wherein The selecting of pixel points in the geographical image in sequence according to each element in the position sequence includes: Denote the th element in the position sequence as . If and , then select the th pixel point among the remaining pixel points in the geographic image; if and and , then select the th pixel point among the remaining pixel points in the geographic image; if and and , then select the last pixel point among the remaining pixel points in the geographic image; if , stop selection; where % represents the remainder symbol, represents the number of remaining pixel points in the geographic image.

6. The encryption processing method for geographic information data according to claim 1, wherein, The performing of AMBTC encoding on the selected pixel points to obtain a high quantization value, a low quantization value, and a binarization mask includes: Take the selected pixel points as the pixel points to be encoded, calculate the average value of the gray values of all the pixel points to be encoded, take the pixel points to be encoded with gray values greater than or equal to the average value as high-brightness pixel points, and take the pixel points to be encoded with gray values less than the average value as low-brightness pixel points; When the pixel point to be encoded belongs to a high-brightness pixel point, set the mask to 1, otherwise, set the mask to 0, and form the binarization mask from the masks corresponding to all the pixel points to be encoded; take the result of rounding up the average value of the gray values of all the high-brightness pixel points as the high quantization value; take the result of rounding up the average value of the gray values of all the low-brightness pixel points as the low quantization value.

7. A method for encrypting and processing geographical information data according to claim 1, characterized in that, The method for obtaining the binary number corresponding to the high quantization value is: Convert 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: Convert the low quantization value into an 8-bit binary number to obtain the binary number corresponding to the low quantization value.

8. A method for encrypting and processing 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, where the coding objects in the coding table are each integer within [0, 255], the codewords of each coding object are 8-bit binary numbers, and the codewords of each coding object are all different; Take the codeword of the coding object equal to the high quantization value in the coding table as the binary number corresponding to the high quantization value; The method for obtaining the binary number corresponding to the low quantization value is: Take the codeword of the coding object equal to the low quantization value in the coding table as the binary number corresponding to the low quantization value.

9. The encryption processing method for geographical information data according to claim 4, wherein, The encryption process further includes: In response to obtaining each encoded object, the first elements in the chaotic sequence are removed from the chaotic sequence to update the chaotic sequence, where represents the target quantity.

10. A method for encrypting and processing geographical information data according to claim 1, characterized in that, It further includes: When personnel with different permissions request to view a geographical image; Return the ciphertext of the corresponding level of the authorized personnel to the requesting terminal; The requesting terminal decrypts the encryption results of the geographical image under each group of chaotic mapping parameters in the ciphertext using each group of chaotic mapping parameters at this level to obtain the decryption results of the geographical image under each group of chaotic mapping parameters; and takes the average value of the decryption results of the geographical image under all groups of chaotic mapping parameters at this level as the final decryption result at this level.

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