CN113077374A - Color image encryption method based on new 4-dimensional hyperchaos and DNA random coding calculation - Google Patents

Color image encryption method based on new 4-dimensional hyperchaos and DNA random coding calculation Download PDF

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CN113077374A
CN113077374A CN202110306095.XA CN202110306095A CN113077374A CN 113077374 A CN113077374 A CN 113077374A CN 202110306095 A CN202110306095 A CN 202110306095A CN 113077374 A CN113077374 A CN 113077374A
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佟晓筠
刘西林
张淼
王翥
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Harbin Institute of Technology Weihai
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Abstract

The invention provides a color image encryption method based on new 4-dimensional hyperchaos and DNA random coding calculation, aiming at the problems that static DNA coding and calculation rules are single, the encryption process is separated from a plaintext and is easy to be attacked by the plaintext. The method comprises the steps of firstly designing a new 4-dimensional hyper-chaotic system, generating a plurality of pseudo-random sequences by an iterative system, calculating and correcting the pseudo-random sequences to generate new pseudo-random sequences and matrixes, decomposing a color image into R, G and B channel components, then fusing the color image into one matrix, then carrying out DNA random coding on the image and the pseudo-random matrix according to the newly generated pseudo-random sequences, carrying out DNA random calculation, carrying out DNA level plaintext related scrambling and DNA random decoding, decomposing the matrix into channel components, and fusing to generate a final ciphertext image, wherein an initial value of the chaotic system is obtained by calculating a plaintext by an SHA-512 algorithm. The encryption method provided by the invention not only has large key space and strong sensitivity to plaintext, but also can effectively resist attacks such as statistics, violence, difference and the like.

Description

Color image encryption method based on new 4-dimensional hyperchaos and DNA random coding calculation
Technical Field
The invention belongs to the technical field of digital image encryption, and particularly relates to a color image encryption method based on new 4-dimensional hyperchaos and DNA random coding calculation.
Background
With the rapid development of electronic communication technology, images are one of the most important communication ways for people to use as the main carrier of information. In real life, a large amount of private image information is transmitted through the internet, military secret-related images and private or commercial images are often leaked and tampered, and how to safely transmit the image information becomes a problem to be solved urgently.
Because the image has the characteristics of high redundancy, large data capacity, strong correlation among pixels and the like, the traditional encryption method such as DES, AES and the like can not meet the requirements of image encryption. The chaotic system has pseudo-randomness, non-periodicity and the like, and can generate unpredictable pseudo-random sequences in a short time, so the chaotic system has natural advantages when being applied to the field of image encryption. At present, the chaotic encryption technology is widely applied to the field of image encryption[1-5]。
Because DNA molecules have the characteristics of super-large-scale storage and lower energy consumption, the DNA molecules have unique advantages when being applied to the field of image encryption, and in recent years, the image encryption method based on the DNA technology is widely applied[6-8]。
Disclosure of Invention
Aiming at the problems that the encryption of each channel component is independent, the calculation rule of DNA codes is single and the encryption process is separated from the plaintext in the existing partial color image encryption method, so that the encryption method is easy to attack and break through by the plaintext, a new 4-dimensional hyper-chaos is designed in the method, and the pseudo-randomness of a system generation sequence is ensured; r, G and B channel components of the color image are encrypted in a cascade mode in the encryption process, so that all the channel components of the image are closely related; the DNA random coding and the DNA random calculation operation are used, so that the problem of single DNA coding and calculation rule is avoided; the scrambling related to the DNA level plaintext is added in the encryption process, and the initial value of the chaotic system is generated by computing the plaintext through SHA-512, so that the sensitivity of the encryption method to the plaintext and the secret key is enhanced.
The invention relates to a color image encryption method based on new 4-dimensional hyperchaos and DNA random coding calculation, which comprises the following steps:
firstly, decomposing a color image P with the size of M × N × 3 into 3R channel components, G channel components, and B channel components with the size of M × N, then expanding the 3 channel components into one-dimensional vectors R1, G1, and B1 by columns, and then expanding the three vectors into binary vectors R2, G2, and B2 with the rows of M × N and the columns of 8, respectively, to further generate a fusion matrix Q ═ R2G 2B 2;
second, a SHA-512 is used to compute a 512bit hash of the color plaintext image, which is converted to 128bit decimal K ═ K1,k2,…,k128The method comprises the steps of (1) carrying out grouping calculation on the original values y1, y2, y3 and y4 of a new 4-dimensional hyper-chaotic system and parameters R1 and R2 for controlling the times of an iterative system, giving the parameter values and the original values of the chaotic system, iterating the chaotic system R1+ R2+100 times, skipping the transition state of the chaotic system, continuously iterating the chaotic system M multiplied by N times, generating four pseudo-random sequences, calculating the sum of the pixels of the first quarter of an R channel component matrix to be Sp1, calculating the sum of the pixels of the last quarter of the R channel component matrix to be Sp2 and the sum of all the pixels of the R channel component matrix to be Sup, participating in calculation and correction of a pseudo-random sequence X of a selected DNA random coding rule, and calculation and correction of a pseudo-random sequence U and a pseudo-random matrix W of the selected DNA random calculation;
the equation of the new 4-dimensional hyper-chaotic system is designed and used as follows:
Figure BDA0002987781550000021
where y1, y2, y3 and y4 are state variables of the system, a11, a12, a13, a14, a21, a22, a23, a24, a31, a32, a33, a34, a41, a42, a43, a44, and β and γ are control parameters of the system, and when a11 ═ 0.5, a12 ═ 4.6, a13 ═ 5.1, a14 ═ 1, a21 ═ 4.8, a22 ═ 3.5, a23 ═ 0.5, a24 ═ 1, a24 ═ 5.1, a24 ═ 0.1, a24 ═ 3, a24 ═ 1, a24 ═ 2, a ═ 24 ═ 3, a ═ 24 ═ 3, a ═ 24 ═ 364, a ═ 3616, γ ═ 3616, and γ are chaotic states.
Thirdly, converting the pseudo-random matrix W into a binary generation matrix W1, selecting a DNA coding rule for each row of the image information matrix Q according to the value of the row corresponding to the sequence X, thereby performing DNA random coding to generate a matrix Q1, and similarly, selecting a DNA coding rule for each row of the matrix W1 according to the value of the row corresponding to the sequence X, thereby performing DNA random coding to generate a matrix W2, and selecting a DNA random calculation mode for the row values of the matrices Q1 and W2 according to the row value of the sequence U, thereby performing DNA random calculation to generate a matrix Q2;
fourthly, calculating the total number of 'A', the total number of 'C', the total number of 'G' and the total number of 'T' in a matrix Q2, calculating and correcting pseudorandom sequences V and T which participate in DNA-level plaintext correlation scrambling, calculating and correcting a pseudorandom sequence L which participates in selection of a DNA random decoding rule, and then performing plaintext correlation scrambling on rows, columns and rows of a matrix Q2 according to the pseudorandom sequences V and T to generate a matrix Q4;
and fifthly, selecting a DNA decoding rule according to row values corresponding to the sequence L for the row values of the matrix Q4, carrying out DNA random decoding to generate a matrix Q5, converting Q5 into decimal, decomposing to generate M × N one-dimensional vectors R3, G3 and B3, reshaping the M × N matrixes for 3 vectors respectively, and fusing to obtain a final ciphertext image of M × N × 3.
Drawings
FIG. 1 is a flow chart of a color image encryption method based on new 4-dimensional hyper-chaos and DNA random coding calculation according to the present invention;
FIG. 2 is a diagram of Lyapunov exponent of the new 4-dimensional hyper-chaos used in the present invention;
FIG. 3 is a diagram showing the process of random encoding of color image DNA in the present invention;
FIG. 4 shows the experimental results of 256 × 256Lena color images in the present invention;
FIG. 5 is a histogram of the plaintext and ciphertext of each channel component of the Lena color image in the present invention;
FIG. 6 is a graph showing the correlation between adjacent pixels in plaintext and ciphertext for each channel component of a Lena color image according to the present invention;
Detailed Description
In order to further understand the technical solution of the present invention, the following further describes the embodiments of the present invention with reference to the accompanying drawings.
The invention relates to a color image encryption method based on new 4-dimensional hyper-chaos and DNA random coding calculation, the flow is shown in figure 1, the invention relates to four main modules, the first module is the generation of a fusion matrix, a pseudo-random sequence and a pseudo-random matrix; the second module is DNA random coding, DNA random calculation and DNA level plaintext related scrambling operation; the third module is DNA random decoding and ciphertext image generation.
1. Fusion matrix, pseudo-random sequence and generation of pseudo-random matrix
1.1 Generation of fusion matrices
A color image P of size M × N × 3 is decomposed into 3R, G, and B channel components of size M × N, then the 3 channel components are expanded into one-dimensional vectors R1, G1, and B1 by columns, and the three vectors are expanded into binary vectors R2, G2, and B2 of size M × N and column 8, respectively, and a fusion matrix Q is further generated [ R2G 2B 2 ].
1.2 Generation of pseudo-random sequences and pseudo-random matrices
The invention designs a new 4-dimensional hyper-chaotic system, and the equation is as follows:
Figure BDA0002987781550000031
where y1, y2, y3 and y4 are state variables of the system, a11, a12, a13, a14, a21, a22, a23, a24, a31, a32, a33, a34, a41, a42, a43, a44, and β and γ are control parameters of the system, and a11 ═ 0.5, a12 ═ 4.6, a13 ═ 5.1, a14 ═ 1, a21 ═ 4.8, a22 ═ 3.5, a23 ═ 0.5, a24 ═ 1, a24 ═ 5.1, a24 ═ 0.1, a24 ═ 3, a24 ═ 1, a24 ═ 2, a ═ 5.1, a24 ═ 3, a ═ 24 ═ 3, a ═ 368, a ═ 364 ═ 3, a ═ 3 ═ 16, a ═ 16, β ═ 16, γ, and γ are chaotic states, and γ are shown in.
The SHA-512 is used to calculate the plain text image of the color image to generate 512bit hash value as the initial key of the invention, which is converted into 128bit decimal systemK represents, wherein K ═ K1,k2,…,k128Obtaining an initial value of the new 4-dimensional hyper-chaotic system and a parameter for controlling the number of times of the iterative system according to the following formula:
Figure BDA0002987781550000041
Figure BDA0002987781550000042
sup is the sum of the pixel values of the R channel component matrix of the color plaintext image, and the calculation formula is as follows:
Figure BDA0002987781550000043
sp1 is the sum of the values of the first quarter pixels of the R-channel component matrix of the color plaintext image, and the calculation formula is as follows:
Figure BDA0002987781550000044
sp2 is the sum of the last quarter pixel values of the R-channel component matrix of the color plaintext image, and the calculation formula is as follows:
Figure BDA0002987781550000045
where floor (t) returns the largest integer less than or equal to the number t.
Giving initial values and parameter values of a system, wherein beta is 10, gamma is 8, iterating the chaotic system r1+ r2+100 times, skipping a transition state, continuing iterating the chaotic system M times N times, and generating 4 pseudo-random sequences y1(a1,a2,…,aM×N)，y2(b1,b2,…,bM×N)，y3(c1,c2,…,cM×N) And y4(d1,d2,…,dM×N) Generating pseudo-random sequences X, Y and a pseudo-random matrix W by computing corrections to the 4 pseudo-random sequences:
Figure BDA0002987781550000046
Y(i)＝mod(floor((y2(i)+y4(i))×1014×Sp2),3)+1 (8)
Figure BDA0002987781550000047
then the pseudo-random matrix is W ═ W1 W2 W3]；
Where i ═ 1,2, …, M × N, floor (t) denotes the largest integer returned which is less than or equal to t, mod (N, t) denotes the number N times t.
Random encoding of DNA, random calculation of DNA and scrambling operations associated with plaintext at DNA level
2.1 random coding of DNA
DNA is a high molecular compound with a double-chain structure, and has three components, namely deoxyribose, phosphoric acid and nitrogenous base. Among them, nitrogenous bases are of four types: A. c, G, T, wherein A is complementary to T, G is complementary to C. Each pixel of the grayscale image may be represented by an 8-bit binary number, with 0 and 1 being complementary in the binary number, so 00 and 11, 01 and 10 are also complementary. Therefore, if 4 nitrogenous bases A, C, G, T represent binary numbers 00, 10, 01, and 11, respectively, each pixel value can be represented by a DNA sequence of length 4, and eight coding rules satisfying the complementary relationship between DNA bases are shown in Table 1.
TABLE 1 eight DNA coding rules
Figure BDA0002987781550000051
The specific formula for random coding of DNA is as follows:
Q1＝DNA_Random_Engcoding(Q(i,j),X(i)) (10)
indicates that the fusion matrix Q (i, j) is randomly coded for each row according to the value of the pseudo-random sequence X (i), i.e. one of the DNA coding rules in Table 1, for example, X (i) has the value of 1, and the ith row of Q (i, j) selects rule 1 for DNA coding; for example, x (i) has a value of 2, the i-th row of Q (i, j) selects rule 2 for DNA encoding … …, for example, x (i) has a value of 8, the i-th row of Q (i, j) selects rule 8 for DNA encoding, and DNA is randomly encoded to generate a DNA matrix Q1, where i is 1,2, …, M × N, j is 1,2, …,24, and the DNA random encoding process is shown in fig. 3.
2.2 random calculation of DNA sequences
The DNA addition and subtraction method is similar to the conventional algebraic calculation, the rule of DNA addition is shown in Table 2, the rule of DNA subtraction is shown in Table 3, and the rule of DNA XOR is shown in Table 4.
TABLE 2DNA addition rules
Figure BDA0002987781550000052
TABLE 3DNA subtraction rules
Figure BDA0002987781550000061
TABLE 4 DNA XOR rule
Figure BDA0002987781550000062
The pseudo-random matrix W is converted into binary W1 and then DNA random encoding is performed according to the following formula:
W2＝DNA_Random_Encoding(W1(i,j),X(i)) (11)
similarly, each row of the pseudorandom matrix W1(i, j) is randomly encoded according to the value of the pseudorandom sequence x (i), to generate a DNA matrix W2, where i is 1,2, …, M × N, j is 1,2, …, 24.
The random calculation formula of the DNA sequence is as follows:
Q2＝DNA_Random_Operation(Q1(i,j),W2(i,j),Y(i)) (12)
according to the value of pseudo-random y (i), the DNA matrix Q1(i, j) and the pseudo-random DNA matrix W2(i, j) are randomly calculated to generate a matrix Q2, that is, any rule of DNA addition, DNA subtraction and DNA exclusive or is selected for each row to calculate, if the value of y (i) is 1, the DNA addition is performed on the i-th row of the matrices Q1 and W2, if the value of y (i) is 2, the DNA subtraction is performed on the i-th row of the matrices Q1 and W2, and if the value of y (i) is 3, the DNA exclusive or is performed on the i-th row of the matrices Q1 and W2, wherein i is 1,2, …, M × N, j is 1,2, …, 12.
2.3 DNA-level plaintext related scrambling
The number of ` A ` in the calculation matrix Q2 was tR1, the number of ` C ` in the matrix Q2 was tR2, the number of ` G ` in the matrix Q2 was tR3, and the number of ` T ` in the matrix Q2 was tR 4.
Pseudo-random sequences V and T for scrambling and sequence L for DNA random decoding were generated from the values of tR1, tR2, tR3 and tR4 by the following equations:
Figure BDA0002987781550000063
Figure BDA0002987781550000064
Figure BDA0002987781550000071
the DNA-level plaintext associated scrambling of matrix Q2 includes the following two processes:
scrambling at column level: q3(: j) ═ circshift (Q2(: j), v (j),1), representing a cyclic shift of each column of the image information matrix Q2(: j) by v (j) units, where j ═ 1,2, …, 12;
scrambling at row level: q4 (i): circshift (Q3 (i): t (i),2) denotes cyclically shifting each row of the image information matrix Q3 (i): by t (i) units, where i ═ 1,2, …, mxn.
DNA random decoding and ciphertext image generation
The rule for decoding DNA is the inverse of the coding rule of table 1, and the DNA random decoding formula is as follows:
Q5＝DNA_Random_Decoding(Q4(i,j),L(i)) (16)
the expression "DNA decoding" is performed on each row of the image DNA matrix Q4(i, j) by the value of the pseudo random sequence l (i) to generate a binary matrix Q5, where i is 1,2, …, M × N, j is 1,2, …, 12.
The final ciphertext image of M × N × 3 is generated by performing matrix decomposition on Q5 according to R3 ═ Q5(1: M × N,1:8), G3 ═ Q5(1: M × N,9:16), B3 ═ Q5(1: M × N,17:24), then converting R3, G3, and B3 into decimal R4, G4, and B4, and then reshaping the R4, G4, and B4 into an M × N matrix through fusion.
The decryption process of the image is the reverse process of the encryption, and is not described in detail herein.
To verify the effectiveness of the present invention, the following simulation experiment further explains that the present invention is tested with Window 10(intel (r) core (tm) i5-4590,3.30GHZ, RAM 4.00GB) and Matlab 2017a as platforms, and the security analysis is performed on the encryption method of the present invention. Fig. 4 is an experimental result of a Lena color image of 256 × 256, where (a) in fig. 4 is a plaintext image of the Lena color image, (b) in fig. 4 is a ciphertext image of the Lena color image, and (c) in fig. 4 is a Lena decrypted image; fig. 5 is histograms of respective channel components of the Lena color image plaintext and ciphertext, and (a), (c), (e) in fig. 5 are histograms of R, G, B channel components of the Lena color image plaintext, respectively, (b), (d), and (f) are histograms of R, G, B channel components of the Lena color image ciphertext, respectively; FIG. 6 is a graph showing correlation distribution among adjacent pixels in the respective channel components of plaintext and ciphertext of a Lena color image, (a), (B), and (c) in FIG. 6 are graphs showing correlation distribution among adjacent pixels in the horizontal, vertical, and diagonal directions of the clear text R channel component of a Lena color image, (d), (e), and (f) in FIG. 6 are graphs showing correlation distribution among adjacent pixels in the horizontal, vertical, and diagonal directions of the R channel component of a Lena color image ciphertext, and (G), (h), (i) in FIG. 6 are graphs showing correlation distribution among adjacent pixels in the horizontal, vertical, and diagonal directions of the clear text G channel component of a Lena color image, (j), (k), (l) in FIG. 6 are graphs showing correlation distribution among adjacent pixels in the horizontal, vertical, and diagonal directions of the G channel component of a Lena color image, and (m), (n), (o) in FIG. 6 are graphs showing correlation distribution among adjacent pixels in the horizontal, vertical, diagonal directions of the B channel component of a, The correlation distribution maps between the adjacent pixels in the vertical and diagonal directions are (p), (q), and (r) in fig. 6, which are the correlation distribution maps between the adjacent pixels in the horizontal, vertical, and diagonal directions of the component of the Lena color image ciphertext B channel.
It can be seen from fig. 4 that the ciphertext image after using the encryption method is similar to noise, and any information about the plaintext image cannot be obtained from the ciphertext image, and the decrypted image is the same as the plaintext image, so that the purpose of encrypting and decrypting the image is achieved.
1. Key space analysis
The security of the encryption method has a great relationship with the key space, and generally, the larger the key space is, the stronger the ability of the encryption method to resist brute force attack is. The key of the encryption method of the invention comprises 512bit key generated by SHA-512 computing plaintext, and Sup, Sp1, Sp2, tR1, tR2, tR3 and tR4 values related to plaintext in the encryption process, so that the key is more than 10200Therefore, the encryption method has larger key space and can effectively resist violent attack.
2. Histogram analysis
The histogram represents the distribution frequency of image pixels and describes the statistical correlation of the image, and generally, the more uniform the histogram of the image pixel gray scale is, the more effectively the histogram can resist the attack of statistical analysis[9]. The gray level histograms of the plaintext and ciphertext channel components of the Lena color image are shown in fig. 5, and the uniform distribution of the pixel values of the encrypted image channel components can be found from the histogram, which shows that the image encryption method has good capability of resisting statistical analysis, and an attacker cannot analyze the gray level distribution of the original image from the ciphertext image.
3. Pixel correlation analysis
The strong correlation exists between adjacent pixels of the plaintext image, partial plaintext information exists in the correlation, the information is easily utilized by lawless persons, and in order to resist statistical analysis, the correlation between the pixels must be reduced. The pixel correlation calculation formula is as follows:
Figure BDA0002987781550000081
where N is the logarithm of arbitrarily chosen neighboring pixels whose gray scale value is (u)i,vi) I 1,2, …, N, vector u { u ═ uiV ═ v }, vector v ═ vi}。
2000 pairs of adjacent pixel points are randomly selected from each channel component of the color Lena plaintext and ciphertext images respectively, and correlation coefficients of the horizontal direction, the vertical direction and the diagonal direction are calculated, and the result is shown in table 5. The correlation diagram of the adjacent pixels of the plaintext and ciphertext images of each channel component in the horizontal direction, the vertical direction and the diagonal direction is shown in fig. 6, and it can be seen from table 5 and fig. 6 that the correlation coefficient between the adjacent pixels of the plaintext image is close to 1, and the correlation coefficient between the adjacent pixels of the ciphertext image is basically 0, which shows that the method breaks the correlation between the adjacent pixels, and lawless persons cannot effectively attack the adjacent pixels through statistical analysis.
TABLE 5 neighbor correlation comparison
Figure BDA0002987781550000091
4. Information entropy analysis
The information entropy reflects the uncertainty of the image, generally, the encryption effect of the algorithm is better, the information entropy of the image is closer to 8, and the information quantity and the randomness of the image are larger[9]. The calculation formula of the information entropy is as follows:
Figure BDA0002987781550000092
where L is the grey level of the image and p (i) represents the probability of the grey value i occurring.
TABLE 6 information entropy values
Figure BDA0002987781550000093
The result of the information entropy value is shown in table 6, and it can be seen from table 6 that the information entropy value of each channel component of the ciphertext image is very close to the theoretical value 8, which indicates that the information leakage possibility of the ciphertext is very low, and further proves that the method of the present invention can effectively resist the statistical analysis attack.
5. Clear text sensitivity analysis
The plaintext sensitivity analysis aims to analyze the difference condition of two ciphertext images obtained by encrypting the images by using the same key when the plaintext slightly changes, if the two ciphertext images have obvious difference, the encryption method has strong sensitivity to the plaintext, and if the difference is smaller, the plaintext sensitivity is called to be poor, and the plaintext sensitivity can be measured by a pixel change rate (NPCR) and a normalized average change rate (UACI), and the calculation formula is as follows:
Figure BDA0002987781550000094
where M, N represent the number of rows and columns of the image, respectively, c1(i, j) represents the pixel value at position (i, j) of the original ciphertext image, c2(i, j) represents the pixel value of the ciphertext image at position (i, j) after being slightly changed. If c is1(i,j)＝c2(i, j), D (i, j) is 0, otherwise D (i, j) is 1.
In order to verify the sensitivity of the encryption method to the plaintext, the pixel value of a certain position in the color Lena image is changed by 1, the Lena color image is encrypted by using the same key to obtain a ciphertext image, the two ciphertext images are decomposed to obtain ciphertext images of each channel component, the difference between the ciphertext images of each channel component and the original channel component is measured by using the values of NPCR and UACI, and the result is shown in Table 3.
Table 7 shows the values of the ciphertext images NPCR and UACI of the channel components before and after the text change
Figure BDA0002987781550000101
The results in table 7 show that the NPCR and UACI values calculated by the present invention are very close to their theoretical values, which indicates that the ciphertext image has a great change after a small change in the plaintext, and further indicates that the encryption method of the present invention has a strong sensitivity to the plaintext and can resist differential attack.
The invention combines the new 4-dimensional hyper-chaotic system and the DNA random coding and computing technology to encrypt the color image, thereby realizing the purpose of encrypting the image. In the encryption process, each channel component of the color image is closely related, the information of the plaintext image participates in the calculation and correction of the pseudorandom sequence, the scrambling operation related to the plaintext is carried out at the DNA level, the initial value of the chaotic system is generated by calculating the plaintext by SHA-512, on one hand, the key space of the encryption method is expanded, and on the other hand, the sensitivity of the encryption method to the plaintext and the key is enhanced.
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Claims (1)

1. A color image encryption method based on new 4-dimensional hyperchaos and DNA random coding calculation is characterized by comprising the following steps:
firstly, decomposing a color image P with the size of M × N × 3 into 3R channel components, G channel components, and B channel components with the size of M × N, then expanding the 3 channel components into one-dimensional vectors R1, G1, and B1 by columns, and then expanding the three vectors into binary vectors R2, G2, and B2 with the rows of M × N and the columns of 8, respectively, to further generate a fusion matrix Q ═ R2G 2B 2;
second, a SHA-512 is used to compute a 512bit hash of the color plaintext image, which is converted to 128bit decimal K ═ K1,k2,…,k128And then, grouping and calculating the three components to generate initial values y1, y2, y3 and y4 of a new 4-dimensional hyper-chaotic system and parameters R1 and R2 for controlling the times of an iterative system, giving parameter values and initial values of the chaotic system, iterating the chaotic system R1+ R2+100 times, skipping a transition state of the chaotic system, continuously iterating the chaotic system M multiplied by N times to generate four pseudorandom sequences, calculating the sum of the first quarter of pixels of an R channel component matrix to be Sp1, calculating the sum of the last quarter of pixels of the R channel component matrix to be Sp2 and the sum of all pixels of the R channel component matrix to be Sup, participating in calculation and correction of a pseudorandom sequence X for selecting a DNA random coding rule, and selecting a pseudorandom sequence U and a pseudorandom matrix for a DNA random calculation modeCalculating and correcting W;
the equation of the new 4-dimensional hyper-chaotic system is designed and used as follows:
Figure FDA0002987781540000011
wherein, y1, y2, y3 and y4 are state variables of the system, a11, a12, a13, a14, a21, a22, a23, a24, a31, a32, a33, a34, a41, a42, a43, a44, and β and γ are control parameters of the system, and a11 ═ 0.5, a12 ═ 4.6, a13 ═ 5.1, a14 ═ 1, a21 ═ 4.8, a22 ═ 3.5, a23 ═ 0.5, a24 ═ 1, a24 ═ 5.1, a24 ═ 0.1, a24 ═ 3, a24 ═ 1, a24 ═ 2, a ═ 24 ═ 3, a ═ 24 ═ 364, a ═ 24 ═ 364, a ═ 3616, γ, and γ are chaotic states [ 3618 ] of the chaotic state;
thirdly, converting the pseudo-random matrix W into a binary generation matrix W1, selecting a DNA coding rule for each row of the image fusion matrix Q according to the value of the row corresponding to the sequence X, thereby performing DNA random coding to generate a matrix Q1, and similarly, selecting a DNA coding rule for each row of the matrix W1 according to the value of the row corresponding to the sequence X, thereby performing DNA random coding to generate a matrix W2, and selecting a DNA random calculation mode for the row values of the matrices Q1 and W2 according to the row value of the sequence U, thereby performing DNA random calculation to generate a matrix Q2;
fourthly, calculating the total number of 'A', the total number of 'C', the total number of 'G' and the total number of 'T' in the matrix Q2, calculating and correcting the pseudorandom sequences V and T which participate in the DNA-level plaintext correlation scrambling, calculating and correcting the pseudorandom sequence L which participates in the selection of the DNA random decoding rule, and then performing plaintext correlation scrambling on rows and columns of the matrix Q2 according to the pseudorandom sequences V and T to generate a matrix Q4;
and fifthly, selecting a DNA decoding rule according to row values corresponding to the sequence L for the row values of the matrix Q4, carrying out DNA random decoding to generate a matrix Q5, converting Q5 into decimal, decomposing to generate M × N one-dimensional vectors R3, G3 and B3, reshaping the M × N matrixes for 3 vectors respectively, and fusing to obtain a final ciphertext image of M × N × 3.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116455546A (en) * 2022-12-09 2023-07-18 兰州交通大学 Vector map DNA dynamic coding encryption method considering global element

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116455546A (en) * 2022-12-09 2023-07-18 兰州交通大学 Vector map DNA dynamic coding encryption method considering global element
CN116455546B (en) * 2022-12-09 2023-10-10 兰州交通大学 Vector map DNA dynamic coding encryption method considering global element

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