Video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping

Abstract

The present invention relates to the field of video encryption technology, and in particular to a video encryption method based on a fractional-order memristive chaotic map with controllable multi-stable states, and a video encryption device using the video encryption method. The present invention constructs a fractional-order memristive chaotic map with controllable homogeneous multi-stable states, and uses the continuous and stable enhanced chaotic sequence generated by the map to encrypt video data. Different encryption steps in the present invention use different enhanced chaotic sequences, thereby generating higher security. The present invention can effectively resist noise attacks, and has good robustness against data loss during the transmission of encrypted video data. The present invention has high sensitivity to keys, a large key space, and good practical application prospects.

Description

Technical Field

[0001] The present invention relates to the technical field of video encryption, and in particular to a video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping, and a video encryption device using the video encryption method. Background Art

[0002] Video data is an important carrier of information. However, unencrypted video data is vulnerable to attacks. The limitations of traditional encryption algorithms such as AES (Advanced Encryption Standard), DES (Data Encryption Standard) and IDEA (International Data Encryption Algorithm) are obvious due to their complex and time-consuming processing. Based on some favorable properties, such as inherent high randomness and initial value sensitivity, chaotic signals are suitable for video encryption. In the past few decades, many works on chaos-based video encryption have been reported. However, existing chaos-based video encryption algorithms have disadvantages such as poor security, small key space and poor robustness against attacks. The encrypted video data is vulnerable to attacks during the transmission process.

[0003] The inventor discovered memristor and multistability in the process of solving the above problems.

[0004] Among them, the memristor is the fourth basic circuit element predicted by Shaotang Cai in 1971. Due to its unique nonlinear and memory characteristics, it is widely used in nonlinear circuits, neural networks, and information security. Cai defined the local active memristor in 2014, which is described as a memristor with negative differential resistance or conductance at certain voltage or current values. Since it can produce more complex dynamic behaviors than passive memristors, it has broader application prospects. And the local active discrete memristor is easier to implement in digital circuits. Due to the discrete memory effect, fractional-order difference equations are closer to reality than integer-order difference equations, so objects can be more accurately described by fractional-order differences. Grunwald Letnikov, Riemann Liouville, and Caputo are three common definitions of fractional-order differences, among which the definition of Caputo fractional-order differences is widely used because of its clearer physical meaning and easy implementation in engineering.

[0005] Multistability is described as a dynamical behavior in which a system can generate coexisting attractors with different positions or topological structures from different initial values. In particular, if a system can generate coexisting attractors with the same topological structure at different positions, the system has homogeneous multistability. Coexisting attractors with homogeneous multistability can provide persistent and stable enhanced chaotic sequences, whose oscillation amplitude can be flexibly and losslessly switched by controlling the initial value, which brings great convenience to many chaos-based engineering applications. It is meaningful to control multistability so that the chaotic system can operate in a desired state. Existing works mainly focus on the study of initial bias behavior with an uncontrollable number of coexisting attractors, while there are few reports on controllable multistability. Summary of the invention

[0006] Based on this, it is necessary to provide a video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping to address the problems of poor security, small key space and poor robustness against attacks in existing chaos-based video encryption algorithms. A fractional-order memristor chaotic mapping based on controllable multi-stable is first proposed, and the controllable enhanced chaotic sequence generated is used for video encryption.

[0007] The present invention is implemented by the following technical solutions:

[0008] In a first aspect, the present invention discloses a video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping, which is used to process original video into encrypted video.

[0009] The video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping includes:

[0010] Construct fractional-order memristor chaotic mapping and generate continuous and stable enhanced chaotic sequences;

[0011] Extract and store all frame images P of the original video j , j = 1, 2, 3, ...;

[0012] The extracted frame image P j Decomposed into a pixel matrix P of three channels: R, G, and B jR , P jG , P jB ;

[0013] P jR , P jG , P jB Perform chaos encryption;

[0014] H R , H G , H B Reshape into the encrypted frame image P' j ;

[0015] All encrypted frame images P' j Reconstructed as encrypted video.

[0016] Among them, the method of performing chaotic encryption includes:

[0017] Step 401, using the first part of the enhanced chaotic sequence to jR , P jG , P jB Perform scrambling operation to obtain the scrambled matrix V R 、V G 、V B ;

[0018] Step 402, using the second part of the enhanced chaotic sequence to R 、V G 、V B Perform shift diffusion to obtain the shift diffused pixel matrix V' R 、V' G 、V' B ;

[0019] Step 403, using the third part of the enhanced chaotic sequence to V' R 、V' G 、V' B Perform XOR diffusion to obtain the pixel matrix H after XOR diffusion R , H G , H B .

[0020] Implementation of a video encryption method based on controllable multi-stable fractional-order memristive chaotic mapping is a method or process according to an embodiment of the present disclosure.

[0021] In a second aspect, the present invention discloses a video encryption device, which uses the video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping as disclosed in the first aspect.

[0022] The video encryption device comprises a chaotic sequence generation module, a video processing module, an image decomposition module, a chaotic encryption module, a matrix reshaping module and a video reconstruction module.

[0023] The chaotic sequence generation module is used to construct fractional-order memristor chaotic mapping and generate a continuous and stable enhanced chaotic sequence. The video processing module is used to extract and store all frame images P of the original video. j , j = 1, 2, 3, ... The image decomposition module is used to extract the frame image P j Decomposed into a pixel matrix P of three channels: R, G, and B jR , P jG , P jB The chaos encryption module is used to jR, P jG , P jB Perform chaotic encryption to obtain H R , H G , H B The matrix reshaping module is used to transform H R , H G , H B Reshape into the encrypted frame image P' j The video reconstruction module is used to convert all encrypted frame images P' j Reconstructed as encrypted video.

[0024] The implementation of the video encryption device is based on the method or process of the embodiment of the present disclosure.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] 1. The present invention constructs a fractional-order memristive chaotic mapping with controllable homogeneous multistable states, and uses the continuous and stable enhanced chaotic sequence generated by the mapping to encrypt video data; different encryption steps in the present invention use different enhanced chaotic sequences, thereby generating higher security.

[0027] 2. The present invention can effectively resist noise attacks and has good robustness against data loss during the transmission of encrypted video data; the present invention has high sensitivity to keys, a large key space, and good practical application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a brief flow chart of a video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping in Embodiment 1 of the present invention;

[0029] Figure 2 This is a flow chart of a video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping in Example 1 of the present invention.

[0030] Figure 3 1 is the tight hysteresis loop of the locally active discrete memristor at different frequencies in Example 1 of the present invention.

[0031] Figure 4 1 is a POP curve of the locally active discrete memristor in Example 1 of the present invention.

[0032] Figure 5 This is the DC-VI curve of the locally active discrete memristor in Example 1 of the present invention.

[0033] Figure 6 This is a fixed point distribution diagram of the fractional-order memristor chaotic mapping under different memristor parameters in Example 1 of the present invention.

[0034] Figure 7 This is a structural diagram of the fractional-order memristor chaotic mapping constructed in Example 1 of the present invention.

[0035] Figure 8 for Figure 7 Correspondence between the number of fixed points and the number of attractors of the fractional-order memristive chaotic map in when I=1,b=0.46.

[0036] Fig. 9 for Figure 7 Bifurcation diagram and corresponding phase diagram of the fractional-order memristive chaotic map in when the initial value z(0) changes continuously.

[0037] Fig.10 for Figure 2 Flowchart of the shift-diffusion method.

[0038] Fig.11 The diagram is an effect diagram of the original test video, encrypted video and decrypted video applied to the video encryption method in Example 2 of the present invention.

[0039] Fig.12 for Fig.11 The original histogram and encrypted histogram of the R, G, and B channels of the 91st frame of the test video.

[0040] Fig.13 for Fig.11 The correlation of the R channel in the 91st frame of the test video in the horizontal, vertical and diagonal directions.

[0041] Fig.14 for Fig.11 Decrypted frames of the 91st frame of the test video at three salt and pepper noise intensities of 0.05, 0.1, and 0.15.

[0042] Fig.15 for Fig.11 The encrypted and decrypted frames of the 91st frame of the test video at three data loss rates of 8.35%, 17.19% and 29.12%. DETAILED DESCRIPTION

[0043] 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.

[0044] It should be noted that when a component is referred to as being "mounted on" another component, it may be directly on the other component or there may be a central component. When a component is considered to be "set on" another component, it may be directly set on the other component or there may be a central component at the same time. When a component is considered to be "fixed to" another component, it may be directly fixed on the other component or there may be a central component at the same time.

[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "or / and" used herein includes any and all combinations of one or more of the related listed items.

[0046] Example 1

[0047] Please see Figure 1 , Figure 1 This is a brief flow chart of the video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping in Example 1 of the present invention.

[0048] like Figure 1 , the video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping includes:

[0049] Construct fractional-order memristor chaotic mapping and generate continuous and stable enhanced chaotic sequences. Extract and store all frame images P of the original video j , j = 1, 2, 3, .... The extracted frame image P j Decomposed into a pixel matrix P of three channels: R, G, and B jR , P jG , P jB . jR , P jG , P jB Perform chaotic encryption. R , H G , H B Reshape into the encrypted frame image P' j . All encrypted frame images P' j Reconstructed as encrypted video.

[0050] See also Figure 2 , wherein the chaotic encryption method includes scrambling operation, shift diffusion, and XOR diffusion.

[0051] As the basis of the video encryption method, this embodiment 1 is to construct a fractional-order memristor chaotic mapping based on controllable multi-stability.

[0052] The method for constructing a fractional-order memristor chaotic map includes: constructing a local active discrete memristor with multiple nonlinear functions, and introducing it into the fractional-order chaotic map to generate a fractional-order memristor chaotic map.

[0053] Among them, we first need to construct a local active discrete memristor with multi-segment nonlinear functions, and realize controllable multistability by controlling the number of fixed points.

[0054] The mathematical equation for this memristor is:

[0055]

[0056] Among them, u(z(n)) is a multi-segment nonlinear function inside the memristor:

[0057]

[0058] c, d, and I are the internal parameters of the memristor, f and γ are the internal constants of the memristor, and i(n), v(n), and z(n) are the current, voltage, and internal state variables of the memristor.

[0059] Assuming I = 0, q = 0.95, γ = 0.46, f = 2000, c = 1e-4, d = 1e-7, and taking the sinusoidal voltage source v(n) = Hsin(ωn) as the driving signal, simulation processing is performed to obtain the tight hysteresis loop of the fractional-order local active discrete memristor at different frequencies, as shown in Figure 3 As shown. Figure 3 It can be seen that the volt-ampere relationship of the memristor presents an "8" curve, and as the frequency increases, the area of ​​the hysteresis loop gradually decreases. When the excitation frequency approaches infinity, the tight hysteresis loop shrinks to a single-valued function passing through the origin. These numerical results show that the proposed mathematical equation meets the definition of a generalized memristor.

[0060] On the one hand, non-volatility is a key feature of the local active memristor, which can be judged by the power-off plot (POP). If there are two or more negative slope intersections between the x-axis and the POP curve at the same time, the memristor is non-volatile. Assuming v(n) = 0, I = 0, then equation (1) can be rewritten as:

[0061]

[0062] Assuming q = 0.95, γ = 0.46, f = 2000, c = 1e-4, d = 1e-7, simulation processing is performed to obtain the POP curve of the fractional-order local active discrete memristor, as shown in Figure 4 As shown. Figure 4It can be seen that there are 5 intersection points between the x-axis and the POP curve, Q1(-2,0), Q3(0,0), Q5(2,0) are stable points with negative slopes, and Q2(-1,0), Q4(1,0) are unstable points with positive slopes. According to the non-volatility theory, the proposed fractional-order discrete memristor is non-volatile.

[0063] On the other hand, the local active characteristic can be judged by the DC-VI graph: if there is a negative slope area on the DC-VI graph at the same time, the memristor is locally active.

[0064] set up and I = 0, then equation (1) can be rewritten as:

[0065]

[0066] Assuming q = 0.95, γ = 0.46, f = 2000, c = 1e-4, -3 < z(n) < 3, the DC-VI diagram of the discrete memristor is obtained by simulation, as shown in Figure 5 shown. Figure 5 In the figure, the gray curve has a negative slope and the black curve has a positive slope, so the proposed fractional-order discrete memristor is locally active.

[0067] After the above verification, see Figure 6 , the constructed fractional-order locally active discrete memristor is introduced into a fractional-order chaotic map, and then the fractional-order memristor chaotic map is obtained.

[0068] in,

[0069] h2(x(n))=x(n)(1-(ex(n)+(|x(n)+1|-|x(n)-1|)))-1|))).

[0070] The mathematical equation of fractional-order chaotic mapping is:

[0071]

[0072] Among them, μ and a are constants, b is the system parameter, k is the coupling coefficient, q is the fractional order, x(n), y(n), z(n) are state variables, and x(0), y(0), z(0) are the initial values ​​of the corresponding state variables.

[0073] Assume q = 0.95, a = 5.5, μ = γ = 0.46, c = -0.55, k = 0.1, d = 1.3, f = 2000. When b∈[0.45,0.49], the mathematical equation exhibits controllable multistability. At this time, the maximum Lyapunov exponent is greater than 0, indicating that it is in a chaotic state.

[0074] The calculation formula of the fixed point (x, y, z) of the fractional-order memristor chaotic mapping is:

[0075]

[0076] Since it is impossible to solve equation (5) analytically, equation (5) is rewritten as:

[0077]

[0078] Without loss of generality, let a = 5.5, b = 0, μ = γ = g = 0.46, c = -0.55, e = 1, k = 0.1, d = 1.3, f = 2000, then the intersection of the curves L1(y, z) and L2(y, z) is the fixed point of equation (4).

[0079] See also Figure 7 , taking the three cases of I = 0, 1, and 2 as examples, the generation mechanism of fixed points is explained. When I = 0, 1, and 2, the fractional-order memristor chaotic mapping generates 6, 10, and 14 fixed points, respectively, which are divided into two columns and arranged along the z-axis.

[0080] See also Figure 8 , showing the corresponding graphs of fixed points and coexistence attractors when I = 1. The existence of two fixed points (such as S1 and S2) enables the fractional-order memristive chaotic mapping to produce coexistence attractors. When I = 0, 1, 2, only three, five, and seven groups of points can produce coexistence attractors from the fractional-order memristive chaotic mapping.

[0081] Fixed b = 0.46, see Fig. 9 , showing the bifurcation diagram and the corresponding phase diagram when the initial value z(0) changes continuously under different parameters I. These coexistence attractors have the same topological structure but different positions, and are homogeneous coexistence attractors; and the number of coexistence attractors and the memristor parameter I satisfy the quantitative relationship of 2I+3. At this time, the mapping shows a homogeneous multistable state controlled by the memristor parameter I. The resulting controllable homogeneous coexistence attractor can provide a continuous and stable enhanced chaotic sequence, and its oscillation amplitude can be flexibly and losslessly switched by controlling the initial value.

[0082] The above verifies that the constructed fractional-order memristor chaotic mapping has the characteristics of controllable multi-stability.

[0083] Based on this controllable multi-stable fractional-order memristor chaotic mapping, a continuous and stable enhanced chaotic sequence can be generated for subsequent video encryption.

[0084] The generation method of the enhanced chaotic sequence includes:

[0085] Let I=1, q=0.95, a=5.5, b=0.46, μ=γ=0.46, c=-0.55, k=0.1, d=1.3, f=2000;

[0086] The fractional-order memristor chaotic mapping generates five coexisting chaotic attractors;

[0087] The fractional-order memristor chaotic mapping is iterated M×N times to obtain 5 sets of enhanced chaotic sequences i2=1,2,3,4,5;

[0088] Among them, M and N represent P jR , P jG , P jB The number of rows and columns, that is, P jR , P jG , P jB It is a matrix structure with M rows and N columns.

[0089] 5 groups of enhanced chaotic sequences It is subsequently divided into three parts: the first part includes Z1, Z2, and Z3, the second part includes Z4, and the third part includes Z5.

[0090] Subsequent video encryption methods include:

[0091] First, extract and store all the frame images P of the original video j , j=1,2,3,…。

[0092] Then, the extracted frame image P j Decomposed into a pixel matrix P of three channels: R, G, and B jR , P jG , P jB .

[0093] Next, for P jR , P jG , P jB Perform chaos encryption.

[0094] Afterwards, H R , H G , H B Reshape into the encrypted frame image P' j .

[0095] Finally, all the encrypted frame images P' j Reconstructed as encrypted video.

[0096] Compared with the existing video encryption method, the difference of this embodiment 1 mainly lies in the different chaotic encryption method.

[0097] See also Figure 2The method for performing chaotic encryption in this embodiment 1 includes:

[0098] Step 401, using the first part of the enhanced chaotic sequence to jR , P jG , P jB Perform scrambling operation to obtain the scrambled matrix V R 、V G 、V B .

[0099] Specifically, P jR For example, step 401 includes:

[0100] Step 4011, arrange the first M values ​​of Z1 in ascending order to obtain index vector Q1;

[0101] P jR The rows of scrambled to get the matrix C R , where C R (l,:)=P jR (Q1(l),:), l = 1, ..., M;

[0102] Step 4012, sort the first N values ​​of Z2 in descending order to obtain index vector Q2;

[0103] C R The columns of scrambled to get the matrix D R , where D R (:,m)=C R (:,Q2(m)), m=1,...,N;

[0104] Step 4013, arrange the first M×N values ​​of Z3 in ascending order to obtain index vector Q3;

[0105] The matrix D R Convert to a one-dimensional vector E R , for D R Perform global scrambling to obtain a one-dimensional vector F R , where F R (o) = E R (Q3(o)), o=1,...,M×N;

[0106] Step 4014, F R Reshape into a two-dimensional V R .

[0107] Similarly, if P jG , the R in the above subscript is changed to G, and P is obtained jG The scrambled matrix V G ;

[0108] If PjB , the R in the above subscript is changed to B, and P is obtained jB The scrambled matrix V B .

[0109] Step 402, see Fig.10 Using the second part of the enhanced chaotic sequence to R 、V G 、V B Perform shift diffusion to obtain the shift diffused pixel matrix V' R 、V' G 、V' B .

[0110] Specifically, step 402 includes:

[0111] From V R 、V G 、V B Take out a value and convert it into an 8-bit binary number to get vector W;

[0112] Step 4022, process Z4 to obtain index vector Q4;

[0113] in,

[0114]

[0115] Let T(i3)=W(Q4(i3)) and obtain vector T.

[0116] Step 4023, divide the vector T into T L and T R Two groups, each with 12 elements; then T L Shift left by 4 bits and change T R Shift right 4 bits;

[0117] Step 4024, disrupt T again L , T R The position of the elements in the vector U is obtained;

[0118] in,

[0119]

[0120] Step 4025, converting the vector U into decimal pixel values ​​corresponding to the three channels of R, G, and B;

[0121] Step 4026, V R 、V G 、V B All pixel values ​​of 4021 to 4025 are executed to obtain the corresponding decimal pixel values ​​and form V' R 、V' G、V' B .

[0122] Step 403, using the third part of the enhanced chaotic sequence to V' R 、V' G 、V' B Perform XOR diffusion to obtain the pixel matrix H after XOR diffusion R , H G , H B .

[0123] Specifically, V R 'For example, step 403 includes:

[0124] Step 4031, process Z5 to obtain a pseudo-random sequence S in the interval [0,255];

[0125] Where S = floor (mod (10 10 ×(Z5-floor(abs(Z5))×10 5 ),256));

[0126] Step 4032, V R 'Convert to a one-dimensional vector A R , and then perform a bitwise XOR operation with S to obtain vector B R ;

[0127] in, B R0 =0;

[0128] Step 4033, vector B R Reshape to H R .

[0129] Similarly, if V' G , the R in the above subscript is changed to G, and V' G Pixel matrix H after XOR diffusion G ;

[0130] If V' B , the R in the above subscript is changed to B, and V' is obtained B Pixel matrix H after XOR diffusion B .

[0131] After the above processing, P jR , P jG , P jB Encrypted into H R , H G , H B , the next step is based on H R , H G , H BReconstruct the video, specifically, H R , H G , H B Reshape into a three-dimensional matrix, which constitutes the encrypted frame image P' j , and then all the encrypted frame images P' j Reconstructed as encrypted video.

[0132] Of course, decrypting the encrypted video generated by this method is achieved through the inverse process of encryption, which will not be repeated here.

[0133] This embodiment 1 also simultaneously discloses a video encryption device, that is, a video encryption method using the above-mentioned fractional-order memristor chaotic mapping based on controllable multi-stable state.

[0134] The video encryption device comprises a chaotic sequence generation module, a video processing module, an image decomposition module, a chaotic encryption module, a matrix reshaping module and a video reconstruction module.

[0135] The chaotic sequence generation module is used to construct fractional-order memristor chaotic mapping and generate a continuous and stable enhanced chaotic sequence. The video processing module is used to extract and store all frame images P of the original video. j , j = 1, 2, 3, ... The image decomposition module is used to extract the frame image P j Decomposed into a pixel matrix P of three channels: R, G, and B jR , P jG , P jB The matrix reshaping module is used to transform H R , H G , H B Reshape into the encrypted frame image P' j The video reconstruction module is used to convert all encrypted frame images P' j Reconstructed as encrypted video.

[0136] The chaotic encryption module includes a scrambling submodule, a shift diffusion submodule, and an XOR diffusion submodule. The scrambling submodule is used to use the first part of the enhanced chaotic sequence to encrypt P jR , P jG , P jB Perform scrambling operation to obtain the scrambled matrix V R 、V G 、V B The shift diffusion submodule is used to use the second part of the enhanced chaotic sequence to R 、V G 、V B Perform shift diffusion to obtain the shift diffused pixel matrix V' R 、V' G 、V' BThe XOR diffusion submodule is used to use the third part of the enhanced chaotic sequence to V' R 、V' G 、V' B Perform XOR diffusion to obtain the pixel matrix H after XOR diffusion R , H G , H B .

[0137] Example 2

[0138] This embodiment 2 discloses a specific example of the video encryption method based on embodiment 1, and uses the video encryption method of embodiment 1 to process a sample test video.

[0139] The test video uses the standard YUV test video News. Fig.11 , shows the effects of the original frame, encrypted frame and decrypted frame of the test video, and selects the 1st, 91st, 139th, 186th and 300th frames. The results show that the encrypted video completely loses the original information, and the proposed encryption algorithm can encrypt the video file well.

[0140] See also Fig.12 , showing the histograms of the R, G, and B channels of the original frame and the encrypted frame (91st frame) of the test video. Fig.12 It can be seen that the histogram of the original frame reflects the distribution of the overall pixel values, which is uneven. On the contrary, the pixel values ​​of the encrypted frame are evenly distributed and lose the original statistical characteristics, which shows that the encrypted image is difficult to crack.

[0141] See Table 1, which shows the correlation coefficients of the R, G, and B channels of the original frame and the encrypted frame (91st frame) of the test video in the horizontal, vertical, and diagonal directions.

[0142] Table 1 Correlation coefficients of the original frame and the encrypted frame in the horizontal, vertical and diagonal directions of the test video (91st frame)

[0143]

[0144] It can be seen from Table 1 that the correlation coefficient of the original frame is high, while the adjacent pixel values ​​of the encrypted frame lose their original correlation and are almost zero.

[0145] See also Fig.13 , showing the correlation of the R channel of the original frame and the encrypted frame (91st frame) of the test video in the horizontal, vertical and diagonal directions. Fig.13 It can be seen that the adjacent pixel values ​​of the original frame have a strong correlation in the three directions, while the adjacent pixel values ​​of the encrypted frame have almost no correlation in the three directions.

[0146] See Table 2, which shows the information entropy of the test video (91st frame). Information entropy reflects the randomness of the encrypted frame. When the information entropy is close to the theoretical value of 8, it indicates that the randomness of the encrypted frame is very strong. According to Table 2, this value is close to the theoretical value of 8, indicating that the video encryption method can effectively encrypt video information.

[0147] In addition, in this embodiment 2, the key is set to (x(0), y(0), z(0), q, b, k). After experiments, when the key changes by more than 10 -28 Therefore, the key space of this embodiment is (10 28 ) 6 =10 168 ≈2 560 , which shows that this video encryption method is highly sensitive to the key.

[0148] This embodiment 2 also tests the robustness, that is, by introducing salt and pepper noise and data loss of different intensities into the encrypted video, the robustness of the encryption algorithm against noise and data loss is tested. Fig.14 , Fig.15 ,Under the interference of different intensities of noise and data loss, the decrypted video can still identify most of the valid information, indicating that the ,present video encryption method is highly robust to noise or disturbance.

[0149] In addition, it should be noted that the test video used in Example 2 is a color video, and the original frame is also a color image (therefore it has three channels of R, G, and B), because the current application requirements adjust it to a grayscale image. To facilitate the examiner's review, the applicant simultaneously submitted a color image as other supporting documents.

[0150] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0151] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping, used to process original video into encrypted video, characterized in that: The video encryption method comprises: Construct fractional-order memristor chaotic mapping and generate continuous and stable enhanced chaotic sequences; Among them, the method of constructing fractional-order memristor chaotic mapping includes: Construct a local active discrete memristor with multi-segment nonlinear functions and introduce it into fractional-order chaotic mapping to generate fractional-order memristor chaotic mapping; The mathematical equation of the fractional-order memristor chaotic mapping is: Among them, u(z(n)) is the internal state variable function of the memristor; c, d, and I are internal parameters of the memristor, b is a system parameter, f, μ, γ, and a are constants, k is a coupling coefficient, q is a fractional order, x(n), y(n), and z(n) are state variables, and x(0), y(0), and z(0) are the initial values ​​of the corresponding state variables; The method for generating the enhanced chaotic sequence comprises: Let I=1, q=0.95, a=5.5, b=0.46, μ=γ=0.46, c=-0.55, k=0.1, d=1.3, f=2000; The fractional-order memristor chaotic mapping generates five coexisting chaotic attractors; The fractional-order memristor chaotic mapping is iterated M×N times to obtain 5 sets of enhanced chaotic sequences Z i2 , i2=1,2,3,4,5; Among them, M and N represent P jR , P jG , P jB The number of rows and columns; 5 groups of enhanced chaotic sequences Z i2 It includes the first part, the second part and the third part. The first part is Z1, Z2 and Z3, the second part is Z4 and the third part is Z5. Extract and store all frame images P of the original video j , j = 1, 2, 3, ...; The extracted frame image P j Decomposed into a pixel matrix P of three channels: R, G, and B jR , P jG , P jB ; P jR , P jG , P jB Performing chaotic encryption; wherein the method for performing chaotic encryption includes: Step 401, using the first part of the enhanced chaotic sequence to jR , P jG , P jB Perform scrambling operation to obtain the scrambled matrix V R 、V G 、V B ; Step 402, using the second part of the enhanced chaotic sequence to R 、V G 、V B Perform shift diffusion to obtain the shift diffused pixel matrix V′ R , V′ G , V′ B ; Step 403, using the third part of the enhanced chaotic sequence to R , V′ G , V′ B Perform XOR diffusion to obtain the pixel matrix H after XOR diffusion R , H G , H B ; H R , H G , H B Reshape into the encrypted frame image P′ j ; All encrypted frame images P′ j Reconstructed as encrypted video.

2. The video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping according to claim 1 is characterized in that: Step 401 includes: Step 4011, arrange the first M values ​​of Z1 in ascending order to obtain index vector Q1; P jR The rows of scrambled to get the matrix C R , where C R (l,:)=P jR (Q1(l),:), l = 1, ..., M; P jG The rows of scrambled to get the matrix C G , where C G (l,:)=P jG (Q1(l),:); P jB The rows of scrambled to get the matrix C B , where C B (l,:)=P jB (Q1(l),:); Step 4012, sort the first N values ​​of Z2 in descending order to obtain index vector Q2; C R The columns of scrambled to get the matrix D R , where D R (:,m)=C R (:,Q2(m)), m=1,...,N; C G The columns of scrambled to get the matrix D G , where D G (:,m)=C G (:,Q2(m)); C B The columns of scrambled to get the matrix D B , where D B (:,m)=C B (:,Q2(m)); Step 4013, arrange the first M×N values ​​of Z3 in ascending order to obtain index vector Q3; The matrix D R Convert to a one-dimensional vector E R , for D R Perform global scrambling to obtain a one-dimensional vector F R , where F R (o) = E R (Q3(o)), o=1,...,M×N; The matrix D G Convert to a one-dimensional vector E G , for D G Perform global scrambling to obtain a one-dimensional vector F G , where F R (o) = E R (Q3(o)); The matrix D B Convert to a one-dimensional vector E B , for D B Perform global scrambling to obtain a one-dimensional vector F B , where F B (o) = E B (Q3(o)); Step 4014, F R Reshape into a two-dimensional V R , F G Reshape into a two-dimensional V G , F B Reshape into a two-dimensional V B .

3. The video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping according to claim 2 is characterized in that: Step 402 includes: Step 4021, sequentially from V R 、V G 、V B Take out a value and convert it into an 8-bit binary number to get vector W; Step 4022, process Z4 to obtain index vector Q4; in, Let T(i3)=W(Q4(i3)), and we get vector T; Step 4023, divide the vector T into T L and T R Two groups, each with 12 elements; then T L Shift left by 4 bits and change T R Shift right 4 bits; Step 4024, disrupt T again L 、T R The position of the elements in the vector U is obtained; in, Step 4025, converting the vector U into decimal pixel values ​​corresponding to the three channels of R, G, and B; Step 4026, V R 、V G 、V B All pixel values ​​of perform steps 4021 to 4025 to obtain the corresponding decimal pixel values ​​and form V′ R , V′ G , V′ B .

4. The video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping according to claim 3 is characterized in that: Step 403 includes: Step 4031, process Z5 to obtain a pseudo-random sequence S in the interval [0,255]; Where S = floor (mod (10 10 ×(Z5-floor(abs(Z5))×10 5 ),256)); Step 4032: V′ R Convert to a one-dimensional vector A R , and then perform a bitwise XOR operation with S to obtain vector B R ; in, V′ G Convert to a one-dimensional vector A G , and then perform a bitwise XOR operation with S to obtain vector B G ; in, V′ B Convert to a one-dimensional vector A B , and then perform a bitwise XOR operation with S to obtain vector B B ; in, Step 4033, vector B R Reshape to H R , vector B G Reshape to H G , vector B B Reshape to H B .

5. The video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping according to claim 4 is characterized in that: H R , H G , H B Reshape into the encrypted frame image P′ j include: H R , H G , H B Reshape into a three-dimensional matrix, which constitutes the encrypted frame image P′ j .

6. A video encryption device, characterized in that: A video encryption method based on controllable multi-stable fractional-order memristor chaotic mapping as described in any one of claims 1 to 5 is used; The video encryption device comprises: A chaotic sequence generation module, which is used to construct a fractional-order memristor chaotic map and generate a continuous and stable enhanced chaotic sequence; The video processing module is used to extract and store all the frame images P of the original video. j , j = 1, 2, 3, ...; The image decomposition module is used to extract the frame image P j Decomposed into a pixel matrix P of three channels: R, G, and B jR , P jG , P jB ; Chaotic encryption module, which is used to jR , P jG , P jB Perform chaotic encryption to obtain H R , H G , H B ; Wherein, the chaotic encryption module includes a scrambling submodule, a shift diffusion submodule, and an XOR diffusion submodule; the scrambling submodule is used to use the first part of the enhanced chaotic sequence to P jR , P jG , P jB Perform scrambling operation to obtain the scrambled matrix V R 、V G 、V B The shift diffusion submodule is used to use the second part of the enhanced chaotic sequence to V R 、V G 、V B Perform shift diffusion to obtain the shift diffused pixel matrix V′ R , V′ G , V′ B The XOR diffusion submodule is used to use the third part of the enhanced chaotic sequence to V′ R , V′ G , V′ B Perform XOR diffusion to obtain the pixel matrix H after XOR diffusion R , H G , H B ; The matrix reshaping module is used to transform H R , H G , H B Reshape into the encrypted frame image P′ j ; as well as The video reconstruction module is used to convert all encrypted frame images P' j Reconstructed as encrypted video.

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