Image encryption method based on internal and external channel replacement and Fibonacci variable matrix

Abstract

The invention discloses an image encryption method based on internal and external channel replacement and a Fibonacci variable matrix, two-dimensional cosine polynomial hyperchaotic mapping with a wider chaotic parameter range and higher randomness is adopted, compared with an existing two-dimensional chaotic system, the Lyapunov index is remarkably improved, and the problems that the chaotic performance is limited and the randomness is insufficient can be effectively solved. Through the combination of three-channel grouping and internal and external scrambling algorithms, the correlation between pixels is effectively destroyed, and the statistical analysis resistance of the image is significantly improved. Meanwhile, based on a chaos variable matrix of a Fibonacci sequence and a pseudo-random translation vector design, the diffusion process shows a strong avalanche effect, so that the image shows stronger resistance to differential attacks and selected plaintext attacks. And by adopting a low-complexity internal and external channel replacement algorithm and a two-dimensional matrix diffusion method, the calculation overhead can be reduced, and the execution efficiency is remarkably improved compared with the traditional algorithm.

Description

Technical Field

[0001] The present invention relates to the technical field of image encryption, and in particular to an image encryption method based on internal and external channel permutation and Fibonacci variable matrix. Background Art

[0002] With the rapid development of medical cloud services and remote consultation technology, unauthorized access to patient information poses a serious threat to information security. In medical scenarios, preventing the leakage or tampering of patient personal information has become an important issue that needs to be solved urgently. In addition, in order to meet the low latency requirements of information transmission, it is also necessary to develop fast encryption algorithms. As the most direct and secure method to protect image information, image encryption has gradually attracted widespread attention because it can effectively resist information leakage. However, due to the large amount of data and high correlation between pixels, traditional encryption methods (such as DES and AES) face huge challenges in image encryption. Chaotic image encryption system has become a more suitable solution for image encryption needs due to its high sensitivity to initial conditions, long periodicity and unpredictable iterative trajectory.

[0003] Existing chaotic systems are mainly divided into one-dimensional and high-dimensional systems. The one-dimensional chaotic system has a simple structure, but its chaotic trajectory is vulnerable to attack and has low security. In contrast, the high-dimensional chaotic system has a more complex structure and stronger chaotic performance, and is a hot research direction. However, increasing the dimension of the chaotic system will significantly increase the computational complexity, so the two-dimensional chaotic system is widely adopted as a trade-off solution. The two-dimensional chaotic system has both computational efficiency and chaotic performance to a certain extent, and is an important direction for image encryption research.

[0004] In addition, the permutation-diffusion image encryption method based on two-dimensional chaotic mapping proposed by Fridrich is regarded as a typical structure and is widely used in image encryption. In recent years, chaos-based image encryption methods have further integrated technologies such as DNA coding, neural networks, and group permutation. Among them, the group permutation scheme is particularly suitable for fast encryption scenarios because it can quickly complete scrambling and effectively destroy the correlation between pixels.

[0005] However, the above-mentioned prior art all has the following disadvantages:

[0006] 1. The existing two-dimensional chaotic systems (such as 2D-SPHM, 2D-SSCDB and Cross-2DHM) have a narrow range of chaotic parameters and insufficient randomness, making it difficult to effectively destroy the correlation between pixels. Especially in high-security and high-efficiency application scenarios, these systems are difficult to meet the requirements.

[0007] 2. In terms of channel group scrambling, the security of existing methods (such as the three-channel scrambling method based on Arnold mapping) is affected by the periodicity limitation of chaotic attractors. In addition, although the Fisher-Yates scrambling algorithm can achieve effective block-in-block scrambling, its high time complexity makes it unsuitable for fast encryption applications.

[0008] 3. Although existing diffusion algorithms based on linear matrix transformation (such as Hill cipher) are widely used due to their simplicity, speed and effectiveness, their original and improved key matrices must be reversible in ring Z / 256Z, otherwise decryption will fail, increasing the complexity and risk of the application.

[0009] 4. As most images transmitted on the network are color images, encryption of the RGB three channels has become a research focus. However, existing methods are difficult to balance efficiency and security in terms of three-channel grouping and scrambling.

[0010] 5. Many existing algorithms fail to reach the ideal level in terms of execution time. For example, some encryption schemes based on DNA coding or complex chaotic systems have great deficiencies in image processing speed and are difficult to meet the needs of real-time encryption. Summary of the invention

[0011] The purpose of the present invention is to overcome the deficiencies of the prior art and provide an image encryption method based on inner and outer channel permutation and Fibonacci variable matrix.

[0012] To achieve the above purpose, the technical solution provided by the present invention is:

[0013] An image encryption method based on internal and external channel permutation and Fibonacci variable matrix, comprising:

[0014] Input a plaintext image P, and perform scrambling processing on the plaintext image P based on a two-dimensional cosine polynomial hyperchaotic mapping system and an internal and external channel replacement algorithm to obtain a scrambled image P′;

[0015] The model of the two-dimensional cosine polynomial hyperchaotic mapping system is as follows:

[0016]

[0017] y v+1 = b·cos(ay v -bx v +x v )

[0018] Among them, x v and vis the input variable of the chaotic mapping; v is the number of iterations of the two-dimensional chaotic system; a and b are the control parameters of the mapping, which are used to adjust the chaotic behavior of the system;

[0019] The scrambled image P′ is diffused by the modulo-π Fibonacci matrix diffusion algorithm, and finally the encrypted image is obtained.

[0020] Furthermore, the plaintext image P is scrambled based on the internal and external channel replacement algorithm, including:

[0021] A1. Use a two-dimensional cosine polynomial hyperchaotic mapping system to generate three chaotic matrices C, Q and S. These chaotic matrices are adjusted to the same size as the input plaintext image P. The element value range of the chaotic matrix C is [1,6], and the element value range of the chaotic matrix Q is [1,M]; M is the length of the plaintext image P.

[0022] A2. For each pixel position R(i,j)G(i,j)B(i,j), use the value of the chaotic matrix C(i,j) as an index and select the corresponding three-channel arrangement order from the preset channel sequence list selectedlist;

[0023] Selected_Channels(i,j)=selected_list[C(i,j)]

[0024] A3. Combine Selected_Channels(i,j) and the chaotic matrix Q to obtain the channel image grouping matrix G;

[0025] A4, grouping the image grouping matrix G by row, and in combination with the chaotic matrix S, scrambling each group by the internal and external channel scrambling algorithm to achieve element scrambling exchange;

[0026] A5. Repeat step A4 until all elements of each group are repositioned, and finally obtain the scrambled image P′.

[0027] Furthermore, the image grouping matrix G of the channel is obtained by combining Selected_Channels(i,j), including:

[0028] The value of each pixel in the image grouping matrix G is determined by a triplet, in which:

[0029] The first component represents the row index of the retrieved value from the original image, which is equal to the value of the chaotic matrix Q at the pixel position R(i,j)G(i,j)B(i,j);

[0030] The second component represents the column index, which is equal to the column index of the element position R(i,j)G(i,j)B(i,j);

[0031] The third component represents the channel index, which is equal to the sequence value of the current channel Selected_Channels(i,j);

[0032] Based on the triplet, the value of the corresponding position is extracted from the plaintext image P and filled into the corresponding position of the image grouping matrix G, thereby obtaining the image grouping matrix G of the channel.

[0033] Further, step A4 includes:

[0034] The image grouping matrix G is grouped by rows, and each group is scrambled by the internal and external channel scrambling algorithm:

[0035] One row is a group, and the kth row is grouped into G k , whose size is 1×N, where N is the width of the plaintext image P, namely:

[0036] G k = {g k0 , g k1 , ..., g kN-1}.

[0037] Among them, g kN-1 Indicates group G k The kN-1th element in ;

[0038] The chaotic matrix S is grouped by rows, and the corresponding chaotic sequence is:

[0039] S k ={s k0 ,s k1 , ..., s kN-1}

[0040] Among them, s kN-1 represents the kN-1th element in the kth row of the chaotic matrix S;

[0041] The traversal pointer starts from the starting position of the subgroup and moves in order after each replacement iteration; the chaotic sequence value of the current round and the position of the traversal pointer determine the replacement pointer index value, starting from the position of the traversal pointer and continuing to the position pointed to by the chaotic sequence value;

[0042] Scramble index S shuffle (n) is defined as:

[0043]

[0044] Among them, n is the position of the current traversal pointer, s kn is the chaotic sequence S k The corresponding element in; the formula determines the new index position of the permutation pointer according to the chaotic sequence;

[0045] The scrambling process is as follows:

[0046]

[0047] in, Indicates element exchange, when the traversal pointer traverses the group G k After all elements of , the scrambling of the group is completed.

[0048] Furthermore, the scrambled image P′ is diffused by using the modulo-π Fibonacci matrix diffusion algorithm, including:

[0049] Using the two-dimensional cosine polynomial hyperchaotic mapping system to perform M×N iterations, M is the length of the plaintext image P, N is the width of the plaintext image P, and three chaotic sequences K1, K2 and K3 are generated;

[0050] Generate a Fibonacci sequence and apply the modulo π operation to obtain a Fibonacci sequence variant with chaotic effect, which is used to generate the key matrix parameter f 11 ,f 12 ,f 21 ,f 22 , and the key matrix parameter f 11 Reversible in Ring Z or 256Z;

[0051] Read the scrambled image P′ and obtain its size M×N;

[0052] Convert the scrambled image P′ into a vector form;

[0053] The first pixel P′(1) is encrypted and its neighboring pixels P′(2) are scrambled as follows:

[0054]

[0055] B(2)=(Z(1)+P′(2))mod256

[0056] Where A(1) is the first encrypted pixel, P′(1) is the first pixel value of the scrambled image, B(2) is the second scrambled pixel, and Z(1) is the temporary value used to randomize adjacent pixels;

[0057] The remaining pixels are encrypted as follows:

[0058]

[0059] B(m)=(Z(m-1)+P′m))mod256

[0060] Where m represents the index of the current pixel;

[0061] Extend the encryption to the last pixel, thus completing the encryption process of the entire image;

[0062] Finally, the vector A is converted back into a two-dimensional matrix form to obtain the encrypted image.

[0063] Compared with the prior art, the principles and advantages of this technical solution are as follows:

[0064] 1. The two-dimensional cosine polynomial hyperchaotic mapping (2D-CPHM) with a wider chaotic parameter range and higher randomness is adopted. Compared with the existing two-dimensional chaotic systems (such as 2D-SPHM, 2D-SSCDB, Cross-2DHM), its Lyapunov index (LE1=222.1670, LE2=256.6653) is significantly improved, which can effectively solve the problems of limited chaotic performance and insufficient randomness.

[0065] 2. Through the combination of three-channel grouping and internal and external scrambling algorithms, the correlation between pixels is effectively destroyed, significantly improving the image's ability to resist statistical analysis. At the same time, based on the chaotic variable matrix and pseudo-random translation vector design of the Fibonacci sequence, the diffusion process shows a strong avalanche effect, making the image more resistant to differential attacks and chosen plaintext attacks.

[0066] 3. The low-complexity inner and outer channel permutation algorithm and two-dimensional matrix diffusion method can reduce computational overhead and significantly improve execution efficiency compared to traditional algorithms. For example, in a 512×512 image test, the algorithm encryption time is only 0.32 seconds, which is significantly better than existing algorithms and meets the needs of low-latency applications.

[0067] 4. It supports multi-channel encryption of color images and is suitable for image data of any shape and size. It has good versatility and adaptability, and is particularly suitable for scenarios such as medical cloud services and remote consultations that have high requirements for information security and encryption speed.

[0068] 5. Multiple chaotic initial parameters and Fibonacci sequence initial values ​​are used to form the key, and the key space reaches 2^520, which is more resistant to brute force cracking than existing algorithms. At the same time, the system's high sensitivity to the key ensures that even a slight change in the key will result in incorrect decryption, further enhancing security. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the services required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0070] Figure 1 This is a principle flow chart of an image encryption method based on internal and external channel permutation and Fibonacci variable matrix of the present invention;

[0071] Figure 2 Bifurcation diagrams of the two-dimensional cosine polynomial hyperchaotic mapping (2D-CPHM) adopted in the present invention under different parameters ((a1) and (b1) are two-dimensional diagrams (b=25); (d1) and (e1) are two-dimensional diagrams (a=25); (c1) and (f1) are three-dimensional diagrams);

[0072] Figure 3 The two-dimensional and three-dimensional phase space trajectory diagrams of the two-dimensional cosine polynomial hyperchaotic mapping (2D-CPHM) ((a2) two-dimensional phase space trajectory with a=25, b=25; (b2) three-dimensional phase space trajectory with a=25; (c2) three-dimensional phase space trajectory with b=25);

[0073] Figure 4 Schematic diagram of three-dimensional Lyapunov exponents of different two-dimensional chaotic maps;

[0074] Figure 5 Schematic diagram of two-dimensional Lyapunov exponents of different two-dimensional chaotic maps;

[0075] Figure 6 It is the original image (plaintext image) used in the encrypted image test;

[0076] Figure 7 This is the encrypted image in the encrypted image test;

[0077] Figure 8 A schematic diagram that illustrates the sensitivity of the key. DETAILED DESCRIPTION

[0078] The present invention will be further described below in conjunction with specific embodiments:

[0079] like Figure 1 As shown, the image encryption method based on inner and outer channel permutation and Fibonacci transformation matrix described in this embodiment includes the following steps:

[0080] S1, input a plaintext image P, and perform scrambling processing on the plaintext image P based on a two-dimensional cosine polynomial hyperchaotic mapping system and an internal and external channel replacement algorithm to obtain a scrambled image P';

[0081] The model of the two-dimensional cosine polynomial hyperchaotic mapping system is as follows:

[0082]

[0083] y v+1 = b·cos(ayv -bx v +x v )

[0084] Among them, x v and v is the input variable of the chaotic mapping; v is the number of iterations of the two-dimensional chaotic system; a and b are the control parameters of the mapping, which are used to adjust the chaotic behavior of the system;

[0085] In this step, the plaintext image P is scrambled based on the internal and external channel replacement algorithm, including:

[0086] A1. Use a two-dimensional cosine polynomial hyperchaotic mapping system to generate three chaotic matrices C, Q and S. These chaotic matrices are adjusted to the same size as the input plaintext image P. The element value range of the chaotic matrix C is [1,6], and the element value range of the chaotic matrix Q is [1,M]; M is the length of the plaintext image P.

[0087] A2. For each pixel position R(i,j)G(i,j)B(i,j), use the value of the chaotic matrix C(i,j) as an index and select the corresponding three-channel arrangement order from the preset channel sequence list selectedlist;

[0088] Selected_Channels(i,j)=selected_list[C(i,j)]

[0089] Specifically, selectedlist is a preset channel sequence list generated by listing 6 permutations and combinations of RGB channels, which is used for the chaotic matrix C index;

[0090] A3. Combine Selected_Channels(i,j) and the chaotic matrix Q to obtain the channel image grouping matrix G;

[0091] This sub-step specifically includes:

[0092] The value of each pixel in the image grouping matrix G is determined by a triplet, in which:

[0093] The first component represents the row index of the retrieved value from the original image, which is equal to the value of the chaotic matrix Q at the pixel position R(i,j)G(i,j)B(i,j);

[0094] The second component represents the column index, which is equal to the column index of the element position R(i,j)G(i,j)B(i,j);

[0095] The third component represents the channel index, which is equal to the sequence value of the current channel Selected_Channels(i,j);

[0096] Based on the triplet, the value of the corresponding position is extracted from the plaintext image P and filled into the corresponding position of the image grouping matrix G, thereby obtaining the image grouping matrix G of the channel.

[0097] A4, grouping the image grouping matrix G by row, and in combination with the chaotic matrix S, scrambling each group by the internal and external channel scrambling algorithm to achieve element scrambling exchange;

[0098] This sub-step specifically includes:

[0099] The image grouping matrix G is grouped by rows, and each group is scrambled by the internal and external channel scrambling algorithm:

[0100] One row is a group, and the kth row is grouped into G k , whose size is 1×N, where N is the width of the plaintext image P, namely:

[0101] G k = {g k0 , g k1 , ..., g kN-1}

[0102] Among them, g kN-1 Indicates group G k The kN-1th element in ;

[0103] The chaotic matrix S is grouped by rows, and the corresponding chaotic sequence is:

[0104] S k ={s k0 ,s k1 , ..., s kN-1}

[0105] Among them, s kN-1 represents the kN-1th element in the kth row of the chaotic matrix S;

[0106] The traversal pointer starts from the starting position of the subgroup and moves in order after each replacement iteration; the chaotic sequence value of the current round and the position of the traversal pointer determine the replacement pointer index value, starting from the position of the traversal pointer and continuing to the position pointed to by the chaotic sequence value;

[0107] Scramble index S shuffle (n) is defined as:

[0108]

[0109] Among them, n is the position of the current traversal pointer, s kn is the chaotic sequence S k The corresponding element in; the formula determines the new index position of the permutation pointer according to the chaotic sequence;

[0110] The scrambling process is as follows:

[0111]

[0112] in, Indicates element exchange, when the traversal pointer traverses the group G k After all elements of , the scrambling of the group is completed.

[0113] A5. Repeat step A4 until all elements of each group are repositioned, and finally obtain the scrambled image P'.

[0114] S2. The scrambled image P′ is diffused by using the modulo-π Fibonacci matrix diffusion algorithm to obtain an encrypted image.

[0115] This step specifically includes:

[0116] Using the two-dimensional cosine polynomial hyperchaotic mapping system to perform M×N iterations, M is the length of the plaintext image P, N is the width of the plaintext image P, and three chaotic sequences K1, K2 and K3 are generated;

[0117] Generate a Fibonacci sequence and apply the modulo π operation to obtain a Fibonacci sequence variant with chaotic effect, which is used to generate the key matrix parameter f 11 ,f 12 ,f 21 ,f 22 , and the key matrix parameter f 11 Reversible in Ring Z or 256Z;

[0118] Read the scrambled image P′ and obtain its size M×N;

[0119] Convert the scrambled image P′ into a vector form;

[0120] The first pixel P'(1) is encrypted and its adjacent pixels P'(2) are scrambled as follows:

[0121]

[0122] B(2)=(Z(1)+P′(2))mod256

[0123] Where A(1) is the first encrypted pixel, P′(1) is the first pixel value of the scrambled image, B(2) is the second scrambled pixel, and Z(1) is the temporary value used to randomize adjacent pixels;

[0124] The remaining pixels are encrypted as follows:

[0125]

[0126] B(m)=(Z(m-1)+P′m))mod256

[0127] Where m represents the index of the current pixel;

[0128] Extend the encryption to the last pixel, thus completing the encryption process of the entire image;

[0129] Finally, the vector A is converted back into a two-dimensional matrix form to obtain the encrypted image.

[0130] In order to prove the superiority of the method of the present invention, the following analytical experiments were performed:

[0131] 1. Analyze the two-dimensional cosine polynomial hyperchaotic mapping (2D-CPHM) used. Figure 2 The bifurcation diagrams of 2D-CPHM under different parameters are shown, and the trajectories are evenly distributed and have no periodic behavior, indicating good ergodicity. Figure 3 The two-dimensional and three-dimensional phase space trajectories show that the trajectory distribution of 2D-CPHM is complex and uniform, further supporting its applicability as a chaotic encryption core.

[0132] 2. Perform Lyapunov index test:

[0133] Table 1 shows that the two Lyapunov exponents (LE1 and LE2) of the 2D-CPHM system are both positive, 222.1670 and 256.6653 respectively, indicating that the system has significant hyperchaotic characteristics.

[0134]

[0135] Table 1

[0136] Figure 4 The three-dimensional Lyapunov exponent distribution of the 2D-CPHM is demonstrated, showing that it maintains a high level of chaotic properties over a wide range of parameters. Figure 5 It is further shown that the two-dimensional distribution of the Lyapunov exponents as a function of the control parameters proves that the chaos intensity and range of 2D-CPHM are superior to those of traditional chaotic systems.

[0137] 3. Encrypted image test

[0138] like Figure 6 and Figure 7 As shown, a3, b3, and c3 are all original images (plaintext images), and d3, e3, and f3 are encrypted images. It can be seen that the method of the present invention has a good image encryption effect.

[0139] 4. Encryption time analysis

[0140]

[0141]

[0142] Table 2 Execution time analysis of different images

[0143] Table 2 shows the superiority of the image encryption algorithm of the present invention in encryption time, proving its high encryption efficiency.

[0144] 5. Key space analysis

[0145] For an image of size 512, assuming the calculation accuracy is 10^16, the key space is: 512×(10^16×10^16×10^16)^2≈2^520. Compared with the existing algorithms, the present invention is more resistant to brute force cracking.

[0146] 6. Key sensitivity analysis

[0147]

[0148] Among them, SNR is signal-to-noise ratio, MSE is mean square error, PSNR is peak signal-to-noise ratio, and SSIM is structural similarity;

[0149] project <![CDATA[x1]]> <![CDATA[y1]]> a b <![CDATA[N0]]> Change value <![CDATA[10 -15 ]]> <![CDATA[10 -15 ]]> 1 2 1

[0150] Table 3

[0151]

[0152]

[0153] Table 4 Evaluation of encrypted image differences due to encryption key changes

[0154] Evaluation metrics such as SNR, MSE, PSNR, and SSIM are used to evaluate the difference between encrypted or decrypted images. The more significant the difference between the two images, the higher the MSE and the lower the SNR, PSNR, and SSIM. If the encryption scheme is insensitive to key changes, a small modification of the key will not change the structural difference between the two encrypted images. Figure 8 In the experiment, a4 is the original image, b4, c4, d4, e4 are the images decrypted with slightly changed keys, and f4 is the image decrypted with the correct key. This experiment shows that the encryption scheme of the present invention embodies key sensitivity, indicating that even a single bit change in the key effectively prevents any retrieval of meaningful information.

[0155] The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, all changes made according to the shape and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An image encryption method based on internal and external channel permutation and Fibonacci matrix transformation, characterized in that: include: Input a plaintext image P, and perform scrambling processing on the plaintext image P based on a two-dimensional cosine polynomial hyperchaotic mapping system and an internal and external channel replacement algorithm to obtain a scrambled image P′; The model of the two-dimensional cosine polynomial hyperchaotic mapping system is as follows: y v+1 =b·cos(a v -bx v +x v ) Among them, x v and v is the input variable of the chaotic mapping; v is the number of iterations of the two-dimensional chaotic system; a and b are the control parameters of the mapping, which are used to adjust the chaotic behavior of the system; The scrambled image P′ is diffused by the modulo-π Fibonacci matrix diffusion algorithm, and finally the encrypted image is obtained.

2. According to claim 1, the image encryption method based on internal and external channel permutation and Fibonacci matrix transformation is characterized in that: The plaintext image P is scrambled based on the internal and external channel replacement algorithm, including: A1. Use a two-dimensional cosine polynomial hyperchaotic mapping system to generate three chaotic matrices C, Q and S. These chaotic matrices are adjusted to the same size as the input plaintext image P. The element value range of the chaotic matrix C is [1,6], and the element value range of the chaotic matrix Q is [1,M]; M is the length of the plaintext image P. A2. For each pixel position R(i,j)G(i,j)B(i,j), use the value of the chaotic matrix C(i,j) as an index and select the corresponding three-channel arrangement order from the preset channel sequence list selected list; Selected_Channels(i,j)=selected_list[C(i,j)] A3. Combine Selected_Channels(i,j) and the chaotic matrix Q to obtain the channel image grouping matrix G; A4, grouping the image grouping matrix G by row, and in combination with the chaotic matrix S, scrambling each group by the internal and external channel scrambling algorithm to achieve element scrambling exchange; A5. Repeat step A4 until all elements of each group are repositioned, and finally obtain the scrambled image P′.

3. The image encryption method based on internal and external channel permutation and Fibonacci matrix transformation according to claim 2 is characterized in that: Combined with Selected_Channels(i,j), we can get the channel image grouping matrix G, including: The value of each pixel in the image grouping matrix G is determined by a triplet, in which: The first component represents the row index of the retrieved value from the original image, which is equal to the value of the chaotic matrix Q at the pixel position R(i,j)G(i,j)B(i,j); The second component represents the column index, which is equal to the column index of the element position R(i,j)G(i,j)B(i,j); The third component represents the channel index, which is equal to the sequence value of the current channel Selected_Channels(i,j); Based on the triplet, the value of the corresponding position is extracted from the plaintext image P and filled into the corresponding position of the image grouping matrix G, thereby obtaining the image grouping matrix G of the channel.

4. The image encryption method based on internal and external channel permutation and Fibonacci matrix transformation according to claim 2 is characterized in that: Step A4 includes: The image grouping matrix G is grouped by rows, and each group is scrambled by the internal and external channel scrambling algorithm: One row is a group, and the kth row is grouped into G k , whose size is 1×N, where N is the width of the plaintext image P, namely: G k ={q k0 ,q k1 ,...,q kN-1 } Among them, g kN-1 Indicates group G k The kN-1th element in ; The chaotic matrix S is grouped by rows, and the corresponding chaotic sequence is: S k ={s k0 ,s k1 ,...,s kN-1 } Among them, s kN-1 represents the kN-1th element in the kth row of the chaotic matrix S; The traversal pointer starts from the starting position of the subgroup and moves in order after each replacement iteration; the chaotic sequence value of the current round and the position of the traversal pointer determine the replacement pointer index value, starting from the position of the traversal pointer and continuing to the position pointed to by the chaotic sequence value; Scramble index S shuffle (n) is defined as: Among them, n is the position of the current traversal pointer, s kn is the chaotic sequence S k The corresponding element in; the formula determines the new index position of the permutation pointer according to the chaotic sequence; The scrambling process is as follows: in, Indicates element exchange, when the traversal pointer traverses the group G k After all elements of , the scrambling of the group is completed.

5. The image encryption method based on internal and external channel permutation and Fibonacci matrix transformation according to claim 1 is characterized in that: The scrambled image P′ is diffused by the modulo-π Fibonacci matrix diffusion algorithm, including: Using the two-dimensional cosine polynomial hyperchaotic mapping system to perform M×N iterations, M is the length of the plaintext image P, N is the width of the plaintext image P, and three chaotic sequences K1, K2 and K3 are generated; Generate a Fibonacci sequence and apply the modulo π operation to obtain a Fibonacci sequence variant with chaotic effect, which is used to generate the key matrix parameter f 11 ,f 12 ,f 21 ,f 22 , and the key matrix parameter f 11 Reversible in Ring Z or 256Z; Read the scrambled image P′ and obtain its size M×N; Convert the scrambled image P′ into a vector form; The first pixel P′(1) is encrypted and its neighboring pixels P′(2) are scrambled as follows: B(2)=(Z(1)+P′(2))mod256 Where A(1) is the first encrypted pixel, P′(1) is the first pixel value of the scrambled image, B(2) is the second scrambled pixel, and Z(1) is the temporary value used to randomize adjacent pixels; The remaining pixels are encrypted as follows: B(m)=(Z(m-1)+P′m))mod256, where m represents the index of the current pixel; Extend the encryption to the last pixel, thus completing the encryption process of the entire image; Finally, the vector A is converted back into a two-dimensional matrix form to obtain the encrypted image.

Images