3D model encryption method based on coordinate regularization

Abstract

The invention discloses a 3D model encryption method based on coordinate regularization, and relates to the technical field of 3D model encryption. The method comprises the following steps: acquiring vertex coordinate data of a 3D model, and constructing a vertex coordinate matrix; the vertex coordinate data are converted into integers in the range of 0-255 through a regularization method, and a two-dimensional numerical matrix is constructed; encrypting the two-dimensional numerical matrix by using a permutation-diffusion model and an encryption method in the variant of the permutation-diffusion model; and converting the encrypted two-dimensional numerical matrix into vertex coordinate data conforming to a 3D model format to form a format-compatible encrypted 3D model. According to the 3D model encryption method, data structure simplification is achieved through coordinate regularization, multiple encryption prototypes (such as row and column replacement, XOR diffusion, modular addition diffusion and AES encryption) are designed to enhance safety, a more generalized encryption method is achieved, and the 3D model encryption method is suitable for 3D data privacy protection in the multimedia fields of industrial manufacturing, medical treatment, 3D modeling and the like.

Description

Technical Field

[0001] The present invention belongs to the technical field of 3D model encryption, and in particular relates to a 3D model encryption method based on coordinate regularization. Background Art

[0002] With the development of 3D scanning technology and computer vision, 3D models have been widely used in many fields, such as industrial design, medical treatment, education and entertainment. 3D modeling and 3D printing technologies are also increasingly used in life. These technologies can create lifelike objects in real life, and also greatly promote the development of virtual reality. Compared with 2D images, 3D models contain richer and more detailed object information; 3D information is more comprehensive, and the projection between views is more accurate; objects can be observed from all angles; they are highly interactive and have richer user experience. However, 3D models contain data used to describe their geometric shape, texture and other properties. In the military, finance, cultural relics protection and highly confidential industries, these data have high commercial value, and the leakage of 3D models may cause immeasurable losses. Therefore, the protection of 3D files is essential to prevent illegal copying, tampering or unauthorized access.

[0003] Traditional 3D model encryption uses algorithmic three-dimensional coordinates, mesh surfaces, textures and other features to encrypt, so that the encrypted model only retains spatial and dimensional characteristics, and its encrypted visual features cannot be identified. Specifically, a cascaded chaotic system is constructed to encrypt 3D models. An optional encryption method can be used. Some researchers use coordinate regularization to convert coordinates into binary bytes, and use a sliding window to encrypt the optional tail of the binary bytes to achieve format-compatible encryption of 3D models. However, in the above encryption process, the discrete value data of vertex coordinates is mainly encrypted. Compared with integer encryption, a more generalized encryption method cannot be achieved.

[0004] To overcome the above shortcomings, the present invention designs a more generalized encryption method, which converts the coordinates into 0-255 integers through coordinate regularization, constructs a two-dimensional coordinate matrix, designs 6 encryption protocols, and encrypts the two-dimensional coordinate matrix, thereby realizing 3D model encryption. Summary of the invention

[0005] The purpose of the present invention is to provide a 3D model encryption method based on coordinate regularization to solve the problems that the existing technology proposed in the above background technology mainly encrypts the discrete value data of vertex coordinates during the encryption process and cannot realize a more generalized encryption method.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] The present invention proposes a 3D model encryption method based on coordinate regularization, comprising the following steps:

[0008] S1. Obtain vertex coordinate data of the 3D model and construct a vertex coordinate matrix;

[0009] S2, converting the vertex coordinate data into integers in the range of 0-255 by a regularization method, and constructing a two-dimensional numerical matrix;

[0010] S3, encrypting a two-dimensional numerical matrix using a permutation-diffusion model and an encryption method in its variants;

[0011] S4. Convert the encrypted two-dimensional numerical matrix into vertex coordinate data that conforms to the 3D model format to form an encrypted 3D model that is compatible with the format.

[0012] Preferably, the S1 is as follows:

[0013] Extract the vertex coordinates of the 3D model from the storage data of various formats of the 3D model. The vertex format is:

[0014] P = {p1, p2, ... p |P|}

[0015] p i =(x i ,y i , z i ), i = {1, ..., |P|}′

[0016] Construct the vertex coordinate matrix, expressed as:

[0017]

[0018] Where P represents the vertices of the 3D model, |·| represents the number of elements in the dataset, and p i Contains three elements, namely the Cartesian coordinates of each vertex (x i ,y i , z i ).

[0019] Preferably, S2 specifically includes the following steps:

[0020] S201, converting the vertex coordinate floating point number into a 32-bit binary number according to the IEEE754 standard;

[0021] S202, the coordinate data (x i ,y i , z i ) is converted to 32-bit binary form, each vertex gets a 96-bit bit stream;

[0022] S203, for each vertex coordinate bit stream, convert each 8 binary bits into decimal to form an integer of 0 to 255, and form 12 integers through conversion;

[0023] S204, forming a final two-dimensional matrix Q with the converted vertex coordinates as columns and the number of vertices as rows;

[0024] The two-dimensional matrix Q is expressed as:

[0025]

[0026] Among them, δ i，j is the jth integer of the ith vertex.

[0027] Preferably, S3 specifically includes the following steps:

[0028] S301, designing a secret key generation method to generate a random sequence;

[0029] S302, the encryption method in the substitution-diffusion model and its variants uses a random sequence to encrypt a two-dimensional numerical matrix.

[0030] Further, the S301 is specifically as follows:

[0031] Generate the secret key K through the SHA-256 function and divide the secret key K into 5 parts:

[0032] K = (k1, k2, k3, k4, k5)

[0033] Among them, k i (1≤i≤4) is a 32-bit binary number, k5 is 128 bits, and the first 4 bits are converted into 4 values ​​as the 4 parameters (a, b, x0, y0) of the next pseudo-random function. k5 controls the number of iterations of the pseudo-random function.

[0034] The pseudo-random function is as follows:

[0035] x i+1 =cos(4·a·x i ·(1-x i )+b·sin(π·y i )+1)

[0036] y i+1 =cos(4·a·y i ·(1-x i )+b·sin(π·x i )+1)

[0037] The iteration of the pseudo-random function ends and two random sequences are generated.

[0038] Furthermore, the substitution-diffusion model in S302 and its variants include 6 encryption methods, which are row-column substitution encryption, block substitution encryption, XOR diffusion encryption, modular diffusion encryption, XOR and row-column substitution encryption, and AES encryption. Any one of the 6 encryption methods is used to encrypt the two-dimensional numerical matrix.

[0039] Specifically, there are 6 encryption methods, as follows:

[0040] S3021, row-column permutation encryption: for two random sequences, sort the random sequences by numerical value, obtain the sorted serial numbers as row indexes and column indexes; re-sort the sequences according to the row and column indexes, and the re-sorted two-dimensional matrix is ​​the encrypted two-dimensional matrix;

[0041] S3022, block permutation encryption: for two random sequences, select one of the sequences, remap the subscripts of the random sequence to form a regularized vector, and organize the vector into a matrix T in a row-first manner;

[0042] The matrix T is:

[0043]

[0044] Set the block size to α and divide the two-dimensional matrix Q into blocks according to α rows. The matrix T is also divided into the same blocks By The numerical values ​​in are sorted by size. according to chaos The data in is obtained to obtain the encrypted two-dimensional matrix;

[0045] S3023, XOR diffusion encryption: Through the matrix T constructed in S3022, T' is obtained by removing the identifier, T' is multiplied by Ω, and the result is obtained by rounding down Its formula is expressed as:

[0046]

[0047] Where, Ω is an integer in the range of o≤Ω≤2000;

[0048] right Modulo 256 to get an integer in the range 0-255 Its formula is expressed as:

[0049]

[0050] Similarly, Converted into 8-bit binary bytes; finally, the two-dimensional matrix Q and Perform bitwise XOR operation to obtain the encrypted two-dimensional matrix;

[0051] S3024, Modular Diffusion Encryption: Multiply the matrix T constructed in S3022 by Ω and round down to get Its formula is expressed as:

[0052]

[0053] The two-dimensional matrix Q and Perform a sum operation and then perform a modular operation with 256 to obtain the encrypted two-dimensional matrix; the modular addition operation formula is:

[0054]

[0055] S3025, XOR and row-column permutation encryption: first, perform XOR diffusion encryption on the two-dimensional matrix according to S3023, and then perform row-column permutation encryption according to S3021 to obtain an encrypted two-dimensional matrix;

[0056] S3026, AES encryption: Use CFB mode; input the 128-bit initialization vector and the 256-bit key into the AES function to generate a 128-bit output; every 16 8-byte integers are divided into a block AES encrypted output and data blocks Perform an XOR operation to obtain the encrypted result C; use C as the new initialization vector to continue encrypting the next data block, and repeat in sequence until all blocks are encrypted to obtain the encrypted two-dimensional matrix;

[0057] in The block method is shown in the following formula:

[0058]

[0059] Each block has 16 integers, or 128 bytes.

[0060] Preferably, the S4 specifically includes the following steps:

[0061] S401, converting each value of the encrypted two-dimensional matrix into an 8-bit binary number, and then combining them into a matrix in a 96-bit binary form;

[0062] S402. According to the IEEE 754 standard, each 32 bits are converted into a real number N. The conversion formula is as follows:

[0063] N=(-1) s ×m×2 e-127

[0064] Among them, m is the binary mantissa part, e is the binary exponent part, and s is the binary identifier, usually 0 or 1;

[0065] S403: Forming an encrypted vertex coordinate matrix P e , whose format is:

[0066]

[0067] S404: Obtain an encrypted 3D model by aggregating the encrypted points and surfaces.

[0068] Compared with the prior art, the present invention has the following beneficial effects:

[0069] (1) The present invention proposes a coordinate regularized 3D model encryption method, which solves the challenges brought by the complex data structure of 3D objects to encryption. The present invention uses coordinate regularization to simplify the data structure. By converting the data structure of the three-dimensional model into a two-dimensional numerical matrix, the complexity of the traditional three-dimensional object encryption method is simplified, so that the existing two-dimensional image encryption technology can be directly applied to three-dimensional objects, realizing a more generalized encryption method, and significantly reducing the difficulty of designing and implementing the encryption algorithm.

[0070] (2) The 3D model encryption method of the present invention designs multiple encryption prototypes (such as row and column permutation, XOR diffusion, modular diffusion and AES encryption) to enhance security, and the encrypted three-dimensional object has good anti-statistical properties, such as high randomness and strong uniformity, which makes it difficult to infer the characteristics of the original object through statistical analysis.

[0071] (3) The encryption mechanism proposed in the 3D model encryption method of the present invention can maintain the format compatibility of the three-dimensional model without changing the format of the original data, so that the encrypted three-dimensional model can be seamlessly adapted to the existing three-dimensional model processing system and application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 It is a flow chart of the 3D model encryption method based on coordinate regularization in the present invention;

[0073] Figure 2 A flowchart for generating a random sequence in the present invention;

[0074] Figure 3 It is a schematic diagram of the change of the two-dimensional numerical matrix in the present invention. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0076] Embodiment 1:

[0077] like Figure 1 As shown, the 3D model encryption method based on coordinate regularization includes the following steps:

[0078] The first step is to obtain the vertex coordinate data of the 3D model and construct a coordinate matrix.

[0079] The vertex coordinate data of the 3D model is obtained. The 3D model stores relevant information about the 3D model in a format that can be understood by a computer, including but not limited to obj, stl, stp and max. The 3D file format can store four key features: the geometry of the model, the surface texture of the model, the scene details and any animation of the model.

[0080] In this embodiment, the geometric shape of the 3D model is mainly used to obtain the vertex coordinate data of the 3D model, where the vertex format is:

[0081] P = {p1, p2, ... p |P|}

[0082] p i =(x i ,y i , z i ), i = {1, ..., |P|}′

[0083] Where P is the vertex of the 3D model, |·| represents the number of elements in the data set, and p i Contains three elements, namely the Cartesian coordinates of each vertex (x i ,y i , z i ).

[0084] Construct a vertex coordinate matrix in the following format:

[0085]

[0086] The second step is to normalize the vertex coordinate data into integers in the range of 0-255 and construct a two-dimensional numerical matrix.

[0087] According to the IEEE754 standard, convert the vertex coordinate floating point number to a 32-bit binary number.

[0088] The coordinate data of each vertex (x i ,y i , z i ) are converted to 32-bit binary form, that is, each vertex can be represented as a 96-bit bit stream. For each vertex coordinate bit stream, every 8 binary bits are converted to decimal to form an integer from 0 to 255. Through the conversion, 12 integers are formed, with the converted vertex coordinates as columns and the number of vertices as rows, forming the final two-dimensional matrix Q.

[0089] The two-dimensional matrix Q is:

[0090]

[0091] Among them, δ i，j is the jth integer of the ith vertex.

[0092] In the third step, the two-dimensional numerical matrix is ​​encrypted using the permutation-diffusion model and its variants.

[0093] First, a random sequence is generated; Figure 2 The random sequence generation process is described, and further details are given as follows:

[0094] Generate the secret key K through the SHA-256 function, and further divide the secret key K into 5 parts:

[0095] K = (k1, k2, k3, k4, k5)

[0096] Among them, k i (1≤i≤4) is a 32-bit binary number, and k5 is 128 bits. Convert the first 4 bits into 4 values, which are used as the 4 parameters (a, b, x0, y0) of the next pseudo-random function. k5 controls the number of iterations of the pseudo-random function.

[0097] The further pseudo-random function is as follows:

[0098] x i+1 =cos(4·a·x i ·(1-x i )+b·sin(π·y i )+1)

[0099] y i+1 =cos(4·a·y i ·(1-x i )+b·sin(π·x i )+1)

[0100] Generate two random number sequences using the above method.

[0101] Secondly, six encryption methods are designed using permutation, diffusion model and their variants; Figure 3 The generation process of encrypted two-dimensional numerical matrix is ​​described, and the encryption protocol is as follows:

[0102] 1) Row-column permutation protocol: sort the two random sequences generated above by numerical value, obtain the sorted serial numbers as row indexes and column indexes; re-sort according to the row and column indexes, and the re-sorted two-dimensional matrix is ​​the encrypted two-dimensional matrix.

[0103] 2) Block permutation protocol: select one of the two random sequences generated above, remap the subscripts of the random sequence to form a regularized vector, and organize the vector into a matrix T in a row-first manner;

[0104] The matrix T is:

[0105]

[0106] Set the block size to α and divide the two-dimensional matrix Q into blocks according to α rows. The matrix T is also divided into the same blocks By The numerical values ​​in are sorted by size. according to chaos The data in is used to obtain the encrypted two-dimensional matrix.

[0107] 3) XOR encryption protocol: Construct the matrix T through 2), get T′ by removing the identifier, multiply T′ by a large number Ω in the range of 0≤Ω≤2000, and get

[0108] Its formula is expressed as:

[0109]

[0110] Then Modulo 256 to get an integer in the range 0-255

[0111] Its formula is expressed as:

[0112]

[0113] Same can be converted into 8-bit binary bytes; finally, the two-dimensional matrix Q and Perform bitwise XOR operation to obtain the encrypted two-dimensional matrix.

[0114] 4) Modular encryption protocol: Through the matrix T constructed in 2), multiply T by a sufficient number Ω and round down to get Its formula is expressed as:

[0115]

[0116] The two-dimensional matrix Q and Perform a sum operation and then perform a modulo operation with 256 to obtain an encrypted two-dimensional matrix;

[0117] The modular addition operation formula is:

[0118]

[0119] 5) XOR and row-column permutation encryption: First, perform XOR encryption on the two-dimensional matrix according to 3), and then perform row-column permutation according to 1) to obtain the encrypted two-dimensional matrix.

[0120] 6) AES encryption protocol: using CFB (Cipher Feedback) mode. Input the 128-bit initialization vector and the 256-bit key into the AES function to generate a 128-bit output. Every 16 8-byte integers can be divided into a block AES encrypted output and data blocks Perform an XOR operation to obtain the encrypted result C. Use C as the new initialization vector to continue encrypting the next data block, and cycle in sequence until all blocks are encrypted to obtain the encrypted two-dimensional matrix.

[0121] in The block method is shown in the following formula:

[0122]

[0123]

[0124] Each block has 16 integers, or 128 bytes.

[0125] In the fourth step, the encrypted two-dimensional matrix values ​​are converted into an encrypted 3D model with a compatible format.

[0126] Each value of the encrypted two-dimensional matrix is ​​converted into an 8-bit binary number, and then combined into a 96-bit binary matrix. Then, according to the IEEE 754 standard, each 32 bits is converted into a real number N. The conversion formula is as follows:

[0127] N=(-1) s ×m×2 e-127

[0128] Among them, m is the binary mantissa part, e is the binary exponent part, and s is the binary identifier, usually 0 or 1.

[0129] Finally, the encrypted vertex coordinate matrix P is formed e , whose format is:

[0130]

[0131] By aggregating the encrypted points and surfaces, an encrypted 3D model is obtained.

[0132] In summary, the present invention proposes a 3D model encryption method based on coordinate regularization, firstly obtaining the vertex coordinate data of the 3D model and constructing a coordinate matrix; converting the vertex coordinate data into integers in the range of 0-255 through coordinate regularization to construct a two-dimensional numerical matrix; encrypting the two-dimensional numerical matrix using the permutation-diffusion model and its variants; converting the encrypted matrix two-dimensional numerical data into vertex data that conforms to the 3D model format to form a format-compatible encrypted 3D model. This method is suitable for 3D data privacy protection in multimedia fields such as industrial manufacturing, medical treatment, and 3D modeling.

[0133] The above description is only used to help understand the method of the present invention and its core essence, but the protection scope of the present invention is not limited thereto. For those skilled in the art in the art, equivalent replacement or change according to the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A 3D model encryption method based on coordinate regularization, characterized in that: The following steps are involved: S1. Obtain vertex coordinate data of the 3D model and construct a vertex coordinate matrix; S2, converting the vertex coordinate data into integers in the range of 0-255 by a regularization method, and constructing a two-dimensional numerical matrix; S3, encrypting a two-dimensional numerical matrix using a permutation-diffusion model and an encryption method in its variants; S4. Convert the encrypted two-dimensional numerical matrix into vertex coordinate data that conforms to the 3D model format to form an encrypted 3D model that is compatible with the format.

2. The 3D model encryption method based on coordinate regularization according to claim 1, characterized in that: The S1 is specifically as follows: Extract the vertex coordinates of the 3D model from the storage data of various formats of the 3D model. The vertex format is: P={p1,p2,…p |P| } p i =(x i ,y i ,z i ),i={1,…,|P|}′ Construct the vertex coordinate matrix, expressed as: Where P represents the vertices of the 3D model, |·| represents the number of elements in the dataset, and p i Contains three elements, namely the Cartesian coordinates of each vertex (x i ,y i , z i ).

3. The 3D model encryption method based on coordinate regularization according to claim 2, characterized in that: The S2 specifically includes the following steps: S201, converting the vertex coordinate floating point number into a 32-bit binary number according to the IEEE754 standard; S202, the coordinate data (x i ,y i , z i ) is converted to 32-bit binary form, each vertex gets a 96-bit bit stream; S203, for each vertex coordinate bit stream, convert each 8 binary bits into decimal to form an integer of 0 to 255, and form 12 integers through conversion; S204, forming a final two-dimensional matrix Q with the converted vertex coordinates as columns and the number of vertices as rows; The two-dimensional matrix Q is expressed as: Among them, δ i，j is the jth integer of the ith vertex.

4. The 3D model encryption method based on coordinate regularization according to claim 3, characterized in that: The S3 specifically includes the following steps: S301, designing a secret key generation method to generate a random sequence; S302, the encryption method in the substitution-diffusion model and its variants uses a random sequence to encrypt a two-dimensional numerical matrix.

5. The 3D model encryption method based on coordinate regularization according to claim 4, characterized in that: The S301 is specifically as follows: Generate the secret key K through the SHA-256 function and divide the secret key K into 5 parts: K = (k1, k2, k3, k4, k5) Among them, k i (1≤i≤4) is a 32-bit binary number, k5 is 128 bits, and the first 4 bits are converted into 4 values ​​as the 4 parameters (a, b, x0, y0) of the next pseudo-random function. k5 controls the number of iterations of the pseudo-random function. The pseudo-random function is as follows: x i+1 =cos(4·a·x i ·(1-x i )+b·sin(π·y i )+1) and i+1 =coS(4 a y i ·(1-x i )+b·sin(π·x i )+1) The iteration of the pseudo-random function ends and two random sequences are generated.

6. The 3D model encryption method based on coordinate regularization according to claim 5, characterized in that: The permutation-diffusion model in S302 and its variants include 6 encryption methods, which are row-column permutation encryption, block permutation encryption, XOR diffusion encryption, modular diffusion encryption, XOR and row-column permutation encryption, and AES encryption. Any one of the 6 encryption methods is used to encrypt a two-dimensional numerical matrix.

7. The 3D model encryption method based on coordinate regularization according to claim 6, characterized in that: The encryption method in S302 is as follows: S3021, row-column permutation encryption: for two random sequences, sort the random sequences by numerical value, obtain the sorted serial numbers as row indexes and column indexes; re-sort the sequences according to the row and column indexes, and the re-sorted two-dimensional matrix is ​​the encrypted two-dimensional matrix; S3022, block permutation encryption: for two random sequences, select one of the sequences, remap the subscripts of the random sequence to form a regularized vector, and organize the vector into a matrix T in a row-first manner; The matrix T is: Set the block size to α and divide the two-dimensional matrix Q into blocks according to α rows. The matrix T is also divided into the same blocks By The numerical values ​​in are sorted by size. according to chaos The data in is obtained to obtain the encrypted two-dimensional matrix; S3023, XOR diffusion encryption: Through the matrix T constructed in S3022, T' is obtained by removing the identifier, and f' is multiplied by Ω, and the result is obtained by rounding down Its formula is expressed as: Where, Ω is an integer in the range of o≤Ω≤2000; right Modulo 256 to get an integer in the range 0-255 Its formula is expressed as: Similarly, Converted into 8-bit binary bytes; finally, the two-dimensional matrix Q and Perform bitwise XOR operation to obtain the encrypted two-dimensional matrix; S3024, Modular Diffusion Encryption: Multiply the matrix T constructed in S3022 by Ω and round down to get Its formula is expressed as: The two-dimensional matrix Q and Perform a sum operation and then perform a modular operation with 256 to obtain the encrypted two-dimensional matrix; the modular addition operation formula is: S3025, XOR and row-column permutation encryption: first, perform XOR diffusion encryption on the two-dimensional matrix according to S3023, and then perform row-column permutation encryption according to S3021 to obtain an encrypted two-dimensional matrix; S3026, AES encryption: Use CFB mode; input the 128-bit initialization vector and the 256-bit key into the AES function to generate a 128-bit output; every 16 8-byte integers are divided into a block AES encrypted output and data blocks Perform an XOR operation to obtain the encrypted result C; use C as the new initialization vector to continue encrypting the next data block, and repeat in sequence until all blocks are encrypted to obtain the encrypted two-dimensional matrix; in The block method is shown in the following formula: Each block has 16 integers, or 128 bytes.

8. A 3D model encryption method based on coordinate regularization according to any one of claims 4 to 7, characterized in that: The S4 specifically includes the following steps: S401, converting each value of the encrypted two-dimensional matrix into an 8-bit binary number, and then combining them into a matrix in a 96-bit binary form; S402. According to the IEEE 754 standard, each 32 bits are converted into a real number N. The conversion formula is as follows: N=(-1) s ×m×2 e-127 Among them, m is the binary mantissa part, e is the binary exponent part, and s is the binary identifier; S403: Forming an encrypted vertex coordinate matrix P e , whose format is: S404: Obtain an encrypted 3D model by aggregating the encrypted points and surfaces.

Images