Member archive encryption management method

Abstract

The invention provides a member archive encryption management method, which comprises the following steps of: S11, performing encryption judgment on a received member archive, and if the encryption state is unencrypted, executing a next step on the member archive; s12, generating an encryption key for a member file needing to be encrypted through a chaos sequence; s13, performing pixel point conversion on the text data to obtain a text image; s14, performing encryption processing on the image data and the text image through a chaotic encryption algorithm to obtain a final encrypted image, and storing the final encrypted image to a corresponding file in a protection system; and S15, receiving a query request sent by the member equipment, judging whether the member identity information is consistent with preset registration information, and if so, restoring the encrypted member file. According to the invention, after the member archive is encrypted based on the chaos encryption algorithm, the text data and the image data in the member archive are encrypted, so that the security and the integrity of the encrypted member archive and the data in the archive are ensured.

Description

Technical Field

[0001] The present invention relates to the field of information security technology, and in particular to a member file encryption management method. Background Art

[0002] With the development of information technology, the rapid development of member file digitization has been promoted. The digitization of member files can reduce the physical space occupied by member file storage, and at the same time, it can facilitate users to quickly locate and find stored member files. Compared with traditional paper member files, it has more excellent effects, and it is precisely because of this that it can be quickly popularized. However, at the same time as electronicization, it also increases the possibility of member file leakage, which increases security issues. Therefore, the safe storage of electronic member files is an important means to protect the security of member file content. Sensitive information contained in member files, such as identity information, transaction records, etc., once leaked, may bring serious consequences to individuals and enterprises. Therefore, the use of encryption technology to protect member files has become an important means to ensure information security.

[0003] In order to improve the efficiency of encryption, the existing technology uses different encryption algorithms to encrypt text and images respectively. The heterogeneity of encrypted data increases the complexity of key management, that is, different data types (such as text and images) require different encryption algorithms, resulting in an increase in the types and number of keys, making the key generation, storage, distribution, update and destruction processes more complicated and cumbersome. Therefore, the heterogeneity of encrypted data not only increases the technical complexity of key management, but also slows down the encryption and decryption process, affecting the efficiency of encryption. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a member file encryption management method, which converts text data into text images for encryption to reduce encryption transmission time and improve the security of member files.

[0005] To achieve the above-mentioned purpose, the present invention provides a member file encryption management method, the method comprising:

[0006] S11, performing encryption judgment on the received member file, if the encryption status is unencrypted, executing the next step for it, the member file includes text data and image data;

[0007] S12, generating an encryption key for the member files that need to be encrypted through a chaotic sequence;

[0008] S13, converting the text data into a text image through pixel conversion;

[0009] S14, encrypting the image data and the text image by using a chaotic encryption algorithm to obtain a final encrypted image, and storing the final encrypted image in a corresponding file in the protection system;

[0010] S15. Receive a query request sent by a member device, wherein the query request includes member identity information and electronic certificate information, determine whether the member identity information is consistent with the preset registration information, and if consistent, restore the encrypted member file according to the electronic certificate information and provide it to the member for viewing.

[0011] Furthermore, in step S11, the received member profile is encrypted and judged, specifically including:

[0012] S21, determining whether the received member file has been stored in the protection system;

[0013] S22, if yes, continue to determine whether the member profile needs to be updated, if yes, search for the original profile of the member profile that needs to be updated, update and encrypt it, and then retransmit it to the protection system;

[0014] S23. If not, the member file is directly encrypted and transmitted to the protection system.

[0015] Furthermore, in step S12, an encryption key is generated for the member file to be encrypted through a chaotic sequence, specifically including:

[0016] S31. Encrypt the member files and couple them with the spatiotemporal evolution to generate the key combination x n (i), the calculation formula is as follows:

[0017]

[0018] Among them, i is the encrypted discrete parameter, ε is the coupling coefficient, n is the spatial discrete value, and x n-1 (i is the element before the current encrypted element, x n+1 (i) is the next element after the current encrypted element;

[0019] S32, binarize the key combination to obtain the encrypted chaotic sequence f′ of the member file ( i ) , the calculation formula is as follows:

[0020]

[0021] Among them, k i is the chaotic encryption floating point parameter, N is a floating point number;

[0022] S33, separating the original encrypted orbit, which is the periodic orbit of the encrypted chaotic sequence, and obtaining the encryption key C(R), which is calculated as follows:

[0023]

[0024] Among them, H is the chaos coefficient, R is the periodic orbit encryption radius, x i is the chaos vector, x j is the chaotic space weight.

[0025] Furthermore, in step S13, the text data is converted into a text image by pixel conversion, which specifically includes:

[0026] S41, encoding each character in the text data to obtain a character code for each character;

[0027] S42, converting each character code into a channel value of an image channel to obtain a character pixel point corresponding to each character;

[0028] S43, performing pixel point replacement processing on a bearing image used to bear the text data using character pixels corresponding to each character to obtain a text image.

[0029] Furthermore, in step S14, the image data and the text image are encrypted by a chaotic encryption algorithm to obtain a final encrypted image, which specifically includes:

[0030] S51, performing scrambling processing on the image data and the text image to obtain a scrambled image;

[0031] S52, performing a chaotic encryption process on the scrambled image to obtain a first encrypted image;

[0032] S53, performing wavelet decomposition on the first encrypted image to extract image data and texture areas in the text image;

[0033] S54, placing the first encrypted image into the texture area by introducing a scale factor to obtain a final encrypted image.

[0034] Furthermore, in step S51, the image data and the text image are scrambled, specifically including:

[0035] S61, converting the image data and the text image into a binary function S on a plane area, the calculation formula is as follows:

[0036] S=h(x,y),(x,y)∈I

[0037] Wherein, h(x,y) is the function of transforming image data and text image, (x,y) is the pixel point on the plane area, and I is the target area;

[0038] S62. Expand and permute the binary function S. The calculation formula is as follows:

[0039]

[0040] Wherein, (x′, y′) is the pixel information after substitution, m and n are the pixel coordinate points in two-dimensional coordinates, and mod1 is the modulo 1 operation, which is used to determine the range of the coordinate points;

[0041] S63, converting the binary function S into a two-dimensional discrete point matrix, and performing expansion and permutation processing on the two-dimensional discrete point matrix. The calculation formula is as follows:

[0042]

[0043] in, is the image information after permutation, xy is the position of each pixel on the two-dimensional plane, n is the state before permutation, n+1 is the state after permutation, N is the matrix order, is the grayscale information of the original image, mod2 is the modulo 2 operation, which is used to replace the grayscale information of the original image, (x, y) E The input is the original image.

[0044] Furthermore, in step S52, the scrambled image is subjected to chaotic encryption processing, which specifically includes:

[0045] S71. Set the initial value c(r) of the chaotic map, which is expressed as follows:

[0046] c (r) =sgn(d (r) ),r=0,1,…,M-1

[0047] Among them, sgn(d (r) ) is the sign function, d (r) is the sequence of chaotic mapping, r is the index of chaotic sequence, and M is a constant;

[0048] S72, straighten the scrambled image to be encrypted by using the set initial value to obtain a vector Z, which is expressed as follows:

[0049]

[0050] S73, select the initial value and length sequence, obtain the chaotic sequence through chaotic mapping, and sort the chaotic sequence to obtain the vector U, which is calculated as follows:

[0051] U=c (r) ·L(x)×R

[0052] Among them, L(x) is the length sequence, R is a random vector;

[0053] S74. Arrange the row and column relationship of the original binary image by using the vector R and the vector Z to obtain a first encrypted image P(x, y). The calculation expression is as follows:

[0054] P(x,y)=R·Z.

[0055] Further, in step S53, the first encrypted image is subjected to wavelet decomposition to extract image data and texture areas in the text image, specifically including:

[0056] S81, using wavelet transform to divide the first encrypted image into four sub-bands, and respectively obtaining horizontal, vertical, low-frequency and 45-degree direction components;

[0057] S82, performing expansion processing on the low-frequency sub-band to obtain four sub-bands on the low-frequency component;

[0058] S83, statistically analyzing the energy distribution and numbers of each sub-band in steps S81 and S82, and extracting the texture area in the image data and text image.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] The present invention provides a member file encryption management method, which first generates an encryption key for the member file through a chaotic sequence, converts the text data in the encrypted member file into a text image, and then encrypts the converted text image and the image data in the file through a chaotic encryption algorithm, and the encrypted member file is stored in a protection system. When members and staff need to access the file, they need to verify their identity information and electronic credentials before they can view the member file in the protection system, otherwise the access fails or only the encrypted content can be accessed. While protecting the member file, the present invention also protects the privacy information in the member file, so that even if unauthorized personnel obtain the member file, they cannot understand its content. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0062] Figure 1 The present invention provides a flowchart of a member file encryption management method. DETAILED DESCRIPTION

[0063] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0064] Reference Figure 1 This embodiment provides a member file encryption management method, the method comprising:

[0065] S11. Perform encryption judgment on the received member file. If the encryption status is unencrypted, execute the next step. The member file includes text data and image data. The member file contains sensitive personal information, such as contact information, transaction records, personal photos, etc. Encryption can prevent unauthorized access or leakage of this information during storage or transmission.

[0066] In step S11, the received member profile is encrypted and judged, which specifically includes:

[0067] S21. Determine whether the received member file has been stored in the protection system.

[0068] S22. If yes, continue to determine whether the member file needs to be updated. If yes, search for the original file of the member file that needs to be updated, update and encrypt it, and then retransmit it to the protection system.

[0069] S23. If not, the member file is directly encrypted and transmitted to the protection system.

[0070] In this embodiment, when entering member information, it is necessary to determine whether the same member information exists in the protection system. If so, the system will issue a reminder message, and the person entering the information can choose to update the existing member profile, or generate a new member profile. The update process and the newly generated member profile must be encrypted before being stored in the protection system. If not, the system will directly execute the encryption step and transmit the encrypted member profile to the protection system.

[0071] S12. Generate encryption keys for member files that need to be encrypted through chaotic sequences. Chaos is a deterministic random process that occurs in nonlinear dynamic systems. This process is neither periodic nor convergent, and is extremely sensitive to initial values. The chaotic sequence is one of the products of this phenomenon. Based on the characteristics of the chaotic phenomenon, the chaotic sequence has the following characteristics: a slight change in the initial conditions can lead to different results in a large range, which greatly enhances the confidentiality of information. Based on this characteristic, a chaotic signal can be used to generate a frequency hopping sequence to achieve the purpose of anti-interference and confidential communication. The chaotic sequence is a non-periodic sequence that is highly sensitive to initial conditions and satisfies the uniform distribution relationship for automatic encryption of member file privacy information. Therefore, the chaotic key for encrypting file privacy information is obtained based on the chaotic sequence.

[0072] In step S12, an encryption key is generated for the member file to be encrypted through a chaotic sequence, which specifically includes:

[0073] S31. Encrypt the member files and couple them with the spatiotemporal evolution to generate the key combination x n( i ) , the calculation formula is as follows:

[0074]

[0075] Among them, i is the encrypted discrete parameter, ε is the coupling coefficient, n is the spatial discrete value, and x n-1( i ) is the element before the current encrypted element, x n+1 (i) is the element following the current encrypted element.

[0076] S32, binarize the key combination to obtain the encrypted chaotic sequence f′ of the member file ( i ) , the calculation formula is as follows:

[0077]

[0078] Among them, k i is the chaotic encryption floating point parameter, and N is a floating point number.

[0079] S33, separating the original encrypted orbit, which is the periodic orbit of the encrypted chaotic sequence, and obtaining the encryption key C(R), which is calculated as follows:

[0080]

[0081] Among them, H is the chaos coefficient, R is the periodic orbit encryption radius, x i is the chaos vector, x j is the chaotic space weight.

[0082] As a preferred embodiment, the chaotic encryption algorithm can quickly generate keys and is suitable for the real-time encryption requirements of large amounts of data. Encryption-coupled spatiotemporal evolution is a method for data encryption using a spatiotemporal chaotic system in chaos theory, which generates encryption keys through a system that exhibits chaotic behavior in both time and space. Generating key combinations through encryption-coupled spatiotemporal evolution can provide strong data protection to prevent unauthorized access and data leakage. The dynamic behavior of the chaotic system and its sensitivity to initial conditions make the generated key sequence have good randomness and unpredictability, thereby providing higher security. Binarization converts the key combination into binary form to simplify the encryption process, making the computer system more efficient in the encryption process, while also increasing the security of encryption. At the same time, the encrypted chaotic sequence after binarization has higher randomness and unpredictability, which is safer for enterprises that need to process a large number of member files. By separating the encryption track, a chaotic key with high randomness and unpredictability can be generated, thereby enhancing the security of encryption.

[0083] S13, converting the text data into a text image through pixel points. After the text data is converted into a text image and then encrypted, the image encryption algorithm can adapt to different data types and encryption requirements. The image encryption calculation complexity is low, which is suitable for the rapid encryption requirements of large amounts of data.

[0084] In step S13, the text data is converted into a text image by pixel conversion, which specifically includes:

[0085] S41, encoding each character in the text data to obtain a character code for each character.

[0086] As a preferred embodiment, the embodiment of the present application does not limit the type of text data. The text data includes at least one character. A character is a unit of glyph, a glyph-like unit or basic information of a symbol. For example, a character can be a Chinese character, an English letter, an Arabic numeral, a punctuation mark, a graphic symbol or a control symbol. Each character in the text data is encoded to map each character to data in digital form, i.e., character encoding. The embodiment of the present application does not limit the encoding standard used for the encoding process. A suitable encoding standard can be selected according to the actual application scenario so that the encoding range of the encoding standard can cover all characters that may appear in the text data to avoid encoding failure.

[0087] S42, converting each character code into a channel value of an image channel to obtain a character pixel point corresponding to each character.

[0088] Among them, the conversion may include base conversion, that is, converting the base of the character code of each character into the same base as that used by the image channel. If the base of the character code of the character is the same as that used by the image channel, the character code can be directly determined as the channel value. On the basis of base conversion, a specific operation can also be performed on the result obtained by base conversion to obtain the channel value. It is worth noting that the value range of the channel value of the image channel should be greater than or equal to the encoding range of the character code, so as to ensure that the character code of each character has a unique corresponding channel value.

[0089] When the number of image channels is multiple, the character code of each character is split according to the number of image channels to obtain multiple sub-character codes of each character; wherein each sub-character code corresponds to an image channel; the multiple sub-character codes of each character are respectively converted into channel values ​​of the corresponding image channels to obtain character pixels corresponding to each character. In the case where the number of image channels (i.e., the first image channel, and the same applies below) used to store the channel values ​​obtained by converting the character code is multiple, the character code of each character is split according to the number of image channels to obtain multiple sub-character codes of each character, i.e., the number of sub-character codes of each character is equal to the number of image channels, wherein the splitting process can be average splitting or non-average splitting, and the splitting rules can be set according to the actual application scenario. Each split sub-character code corresponds to an image channel, therefore, the multiple sub-character codes of each character are respectively converted into channel values ​​of the corresponding image channels to obtain character pixels corresponding to each character. In the above manner, when the number of image channels is multiple, each image channel can be converted separately to improve the orderliness and accuracy of the conversion process.

[0090] S43, performing pixel point replacement processing on a bearing image used to bear the text data using character pixels corresponding to each character to obtain a text image.

[0091] On the basis of obtaining the character pixel points described by the converted channel value, the pixel point replacement processing is performed on the bearing image used to bear the text data according to the character pixel points to obtain the text image, wherein the pixel point replacement processing refers to replacing an original pixel point in the bearing image according to each character pixel point, and different character pixels correspond to different pixel point positions respectively, so as to ensure that all character pixels are included in the text image. The text image is mixed with character pixels and original pixels in the bearing image. Only by combining the text image and the bearing image can the text decryption be realized. Even if the hijacker hijacks the key image, since there is no bearing image, it is impossible to determine which are the character pixels in the key image, that is, the text data cannot be restored from the key image. In this way, the storage and transmission of text data can be replaced by the storage and transmission of the key image, thereby improving the security and confidentiality of the text data. It is worth noting that the embodiment of the present application does not limit the type of the bearing image, for example, it can be specified by the user (for example, the initial image uploaded by the user is used as the bearing image), it can be randomly selected from multiple images, or it can be obtained after a special processing (such as noise processing) of a certain image.

[0092] S14, encrypting the image data and the text image by using a chaotic encryption algorithm to obtain a final encrypted image, and storing the final encrypted image in a corresponding file in the protection system.

[0093] In step S14, the image data and the text image are encrypted by a chaotic encryption algorithm to obtain a final encrypted image, which specifically includes:

[0094] S51, performing scrambling processing on the image data and the text image to obtain a scrambled image.

[0095] S52: Perform chaotic encryption processing on the scrambled image to obtain a first encrypted image.

[0096] S53: Perform wavelet decomposition on the first encrypted image to extract image data and texture areas in the text image.

[0097] S54, by introducing the scale factor, the first encrypted image is placed in the texture area to obtain the final encrypted image. For the scale factor algorithm, if the embedded scale factor value is too large, it will have a relatively large impact on the initial coefficient adjustment, resulting in unsatisfactory quality of the image after embedding. In order to select a suitable scale factor, it is necessary to appropriately enlarge and reduce the scale factor range, and select the embedding scale factor that best suits the image size according to the image adaptively. After obtaining the scale factor suitable for the original image, the first encrypted image is placed in the texture area determined in step S53 through the scale factor, and finally the secure encryption of the member file is achieved.

[0098] In step S51, the image data and the text image are scrambled. The scrambling process can scramble the original meaningful or sequential data to achieve the purpose of encryption, which specifically includes:

[0099] S61, converting the image data and the text image into a binary function S on a plane area, the calculation formula is as follows:

[0100] S=h(x,y),(x,y)∈I

[0101] Among them, h(x,y) is the function of transforming image data and text image, (x,y) is the pixel point on the plane area, and I is the target area.

[0102] Scrambling transformation regards image data and text images as binary functions on a plane area, and then expands and permutes them by converting them into binary functions on a plane area. In general, the target area I is a rectangle. For a random point in I, the corresponding function value (x, y) represents the information of the original image. The permutation of image data and text images is to permute the pixel information of point (x, y) to the pixel information of point (x′, y′).

[0103] S62. Expand and permute the binary function S. The calculation formula is as follows:

[0104]

[0105] Wherein, (x′, y′) is the pixel information after substitution, m and n are the pixel coordinate points in two-dimensional coordinates, and mod1 is the modulo 1 operation, which is used to determine the range of the coordinate points;

[0106] S63, converting the binary function S into a two-dimensional discrete point matrix, and performing expansion and permutation processing on the two-dimensional discrete point matrix. The calculation formula is as follows:

[0107]

[0108] in, is the image information after permutation, xy is the position of each pixel on the two-dimensional plane, n is the state before permutation, n+1 is the state after permutation, N is the matrix order, is the grayscale information of the original image, mod2 is the modulo 2 operation, which is used to replace the grayscale information of the original image, (x, y) E The input is the original image.

[0109] With the digitization of the image, the binary function S can be set as a two-dimensional discrete point matrix to obtain the independent variable values ​​of each group in the corresponding rows and columns, where the elements are the original image information. After the discretization process, it can be seen that there is a close relationship between the digital image and each element, and the correlation matrix is ​​obtained. The matrix is ​​expanded and permuted to obtain a new matrix, and the two-dimensional discrete point matrix is ​​expanded and permuted.

[0110] In step S52, the scrambled image is subjected to an unfolding chaotic encryption process, which specifically includes:

[0111] S71. Set the initial value c(r) of the chaotic map, which is expressed as follows:

[0112] c (r) =sgn(d (r) ),r=0,1,…,M-1

[0113] Among them, sgn(d (r) ) is the sign function, d (r) is the sequence of chaotic mapping, r is the index of chaotic sequence, and M is a constant;

[0114] S72, straighten the scrambled image to be encrypted by using the set initial value to obtain a vector Z, which is expressed as follows:

[0115]

[0116] S73, select the initial value and length sequence, obtain the chaotic sequence through chaotic mapping, and sort the chaotic sequence to obtain the vector U, which is calculated as follows:

[0117] U=c (r) ·L(x)×R

[0118] Among them, L(x) is the length sequence, R is a random vector;

[0119] S74. Arrange the row and column relationship of the original binary image by using the vector R and the vector Z to obtain a first encrypted image P(x, y). The calculation expression is as follows:

[0120] P(x,y)=R·Z.

[0121] In step S53, the first encrypted image is subjected to wavelet decomposition to extract image data and texture areas in the text image, which specifically includes:

[0122] S81, using wavelet transform to divide the first encrypted image into four sub-bands, and respectively obtaining horizontal, vertical, low-frequency and 45-degree direction components;

[0123] S82, performing expansion processing on the low-frequency sub-band to obtain four sub-bands on the low-frequency component;

[0124] S83, statistically analyzing the energy distribution and numbers of each sub-band in steps S81 and S82, and extracting the texture area in the image data and text image.

[0125] As a preferred embodiment, the image data and the text image are subjected to scrambling transformation operations and chaotic encryption processing to obtain a first encrypted image P(x, y). According to the characteristics of HSV, it is necessary to select a suitable texture area, and select the embedding area of ​​the original image through wavelet decomposition. In the process of selecting high and low frequency sub-bands, since the coefficient of the low frequency part is significantly higher than the coefficients of the other two sub-bands, the low frequency area of ​​the original image is selected as the embedding area, that is, the texture area finally determined.

[0126] S15. Receive a query request sent by a member device, wherein the query request includes member identity information and electronic certificate information, determine whether the member identity information is consistent with the preset registration information, and if consistent, restore the encrypted member file according to the electronic certificate information and provide it to the member for viewing.

[0127] As a preferred embodiment, by verifying member identity information and electronic credential information, it is ensured that only authorized members can access their encrypted files. During the chaotic encryption and credential-based decryption process, the system will verify the visitor's electronic credential information to ensure that only legitimate members can access their files, preventing members' file information from being leaked to non-members.

[0128] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A member file encryption management method, characterized in that: The method comprises: S11, performing encryption judgment on the received member file, if the encryption status is unencrypted, executing the next step for it, the member file includes text data and image data; S12, generating an encryption key for the member files that need to be encrypted through a chaotic sequence; S13, converting the text data into a text image through pixel conversion; S14, encrypting the image data and the text image by using a chaotic encryption algorithm to obtain a final encrypted image, and storing the final encrypted image in a corresponding file in the protection system; S15. Receive a query request sent by a member device, wherein the query request includes member identity information and electronic certificate information, determine whether the member identity information is consistent with the preset registration information, and if consistent, restore the encrypted member file according to the electronic certificate information and provide it to the member for viewing.

2. The member file encryption management method according to claim 1, characterized in that: In step S11, the received member profile is encrypted and judged, which specifically includes: S21, determining whether the received member file has been stored in the protection system; S22, if yes, continue to determine whether the member profile needs to be updated, if yes, search for the original profile of the member profile that needs to be updated, update and encrypt it, and then retransmit it to the protection system; S23. If not, the member file is directly encrypted and transmitted to the protection system.

3. The member file encryption management method according to claim 1, characterized in that: In step S12, an encryption key is generated for the member file to be encrypted through a chaotic sequence, which specifically includes: S31. Encrypt the member files and couple them with time and space evolution to generate the key combination x n (i), the calculation formula is as follows: Among them, i is the encrypted discrete parameter, ε is the coupling coefficient, n is the spatial discrete value, X n-1 (i) is the previous element of the current encrypted element, X n+1 (i) is the next element after the current encrypted element; S32, binarize the key combination to obtain the encrypted chaotic sequence f′(i) of the member file, which is calculated as follows: Among them, k i is the chaotic encryption floating point parameter, N is a floating point number; S33, separating the original encrypted orbit, which is the periodic orbit of the encrypted chaotic sequence, and obtaining the encryption key C(R), which is calculated as follows: Among them, H is the chaos coefficient, R is the periodic orbit encryption radius, x i is the chaos vector, x j is the chaotic space weight.

4. The member file encryption management method according to claim 3 is characterized in that: In step S13, the text data is converted into a text image by pixel conversion, which specifically includes: S41, encoding each character in the text data to obtain a character code for each character; S42, converting each character code into a channel value of an image channel to obtain a character pixel point corresponding to each character; S43, performing pixel point replacement processing on a bearing image used to bear the text data using character pixels corresponding to each character to obtain a text image.

5. The member file encryption management method according to claim 4 is characterized in that: In step S14, the image data and the text image are encrypted by a chaotic encryption algorithm to obtain a final encrypted image, which specifically includes: S51, performing scrambling processing on the image data and the text image to obtain a scrambled image; S52, performing a chaotic encryption process on the scrambled image to obtain a first encrypted image; S53, performing wavelet decomposition on the first encrypted image to extract image data and texture areas in the text image; S54, placing the first encrypted image into the texture area by introducing a scale factor to obtain a final encrypted image.

6. The member file encryption management method according to claim 5, characterized in that: In step S51, the image data and the text image are scrambled, specifically including: S61, converting the image data and the text image into a binary function S on a plane area, the calculation formula is as follows: S = h(x, y), (x, y)∈I Wherein, h(x, y) is the function of transforming image data and text image, (x, y) is the pixel point on the plane area, and I is the target area; S62. Expand and permute the binary function S. The calculation formula is as follows: Wherein, (x′, y′) is the pixel information after substitution, m and n are the pixel coordinate points in two-dimensional coordinates, and mod1 is a modulo 1 operation, which is used to determine the range of the coordinate points; S63, converting the binary function S into a two-dimensional discrete point matrix, and performing expansion and permutation processing on the two-dimensional discrete point matrix. The calculation formula is as follows: in, is the image information after permutation, xy is the position of each pixel on the two-dimensional plane, n is the state before permutation, n+1 is the state after permutation, N is the matrix order, is the grayscale information of the original image, mod2 is the modulo 2 operation, which is used to replace the grayscale information of the original image, (x, y) E The input is the original image.

7. The member file encryption management method according to claim 5, characterized in that: In step S52, the scrambled image is subjected to an unfolding chaotic encryption process, which specifically includes: S71, set the initial value c of the chaotic map (r) , the expression is as follows: c (r) =sgn(d (r) ),r=0,1,…,M-1 Among them, sgn(d (r) ) is the sign function, d (r) is the sequence of chaotic mapping, r is the index of chaotic sequence, and M is a constant; S72, straighten the scrambled image to be encrypted by using the set initial value to obtain a vector Z, which is expressed as follows: S73, select the initial value and length sequence, obtain the chaotic sequence through chaotic mapping, and sort the chaotic sequence to obtain the vector U, which is calculated as follows: U=c (r) ·L(x)×R Among them, L(x) is the length sequence, R is a random vector; S74. Arrange the row and column relationship of the original binary image by using the vector R and the vector Z to obtain a first encrypted image P (x, y). The calculation expression is as follows: P(x, y) = R·Z.

8. The member file encryption management method according to claim 5, characterized in that: In step S53, the first encrypted image is subjected to wavelet decomposition to extract image data and texture areas in the text image, which specifically includes: S81, using wavelet transform to divide the first encrypted image into four sub-bands, and respectively obtaining horizontal, vertical, low-frequency and 45-degree direction components; S82, performing expansion processing on the low-frequency sub-band to obtain four sub-bands on the low-frequency component; S83, statistically analyzing the energy distribution and numbers of each sub-band in steps S81 and S82, and extracting the texture area in the image data and text image.

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