Unmanned aerial vehicle inspection traffic control system and method based on chaotic system

Abstract

The application discloses a kind of unmanned aerial vehicle inspection traffic control system and method based on chaotic system, comprising: sending end, encryption module and receiving end;Sending end is used to obtain the original inspection image obtained in unmanned aerial vehicle inspection;Encryption module and the sending end carry out data interaction, for the original inspection image is encrypted, obtains the image data after encryption;Receiving end is used to obtain the image data after encryption;In the encryption process, the plaintext association framework of SHA-256 hash function is used, and it is applied to the encrypted original image, to enhance the sensitivity of plaintext;Moreover, the compatibility of encoded data is better, suitable for embedding different structured data formats, ensure data integrity while also taking into account protocol friendliness, have greater chaotic region, stronger theoretical robustness, higher engineering fault tolerance, more flexible system design space, more superior security performance.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of unmanned aerial vehicle inspection, and in particular to an unmanned aerial vehicle inspection traffic control system and method based on a chaotic system. BACKGROUND

[0002] With the rapid development of today's low-altitude economy, unmanned aerial vehicles are commonly used in tasks such as inspection and monitoring, security and emergency, surveying and modeling, etc. Image transmission has become an important part of the work of unmanned aerial vehicles. At the same time, the safety of unmanned aerial vehicle inspection systems when transmitting data such as images has become a focus of attention, especially for digital images containing sensitive information in the fields of military and medical care.

[0003] Currently, images generated during the unmanned aerial vehicle inspection process are mostly transmitted using Base64 encoding as the main transmission method. Although this method has certain universality and convenience, its defects are also very obvious, such as the easy exposure of sensitive information. Therefore, it is necessary to develop an easy-to-use, efficient, and secure image encryption system to encrypt digital images containing sensitive information to protect their confidentiality.

[0004] Based on this, the present disclosure provides an unmanned aerial vehicle inspection traffic control system based on a chaotic system for encrypted transmission of inspection images. SUMMARY

[0005] The present disclosure aims to provide an unmanned aerial vehicle inspection traffic control system and method based on a chaotic system to solve at least one technical problem in the prior art.

[0006] The technical solution of the present disclosure is as follows:

[0007] An unmanned aerial vehicle inspection traffic control system based on a chaotic system, comprising:

[0008] A sending end for obtaining original inspection images obtained during unmanned aerial vehicle inspection;

[0009] An encryption module for data interaction with the sending end, for encrypting the original inspection images to obtain encrypted image data;

[0010] A receiving end for data interaction with the encryption module, for obtaining the encrypted image data;

[0011] The encryption module encrypts the original inspection images through the following process:

[0012] Collecting original inspection images obtained during unmanned aerial vehicle inspection and performing a hash operation to generate a hash value;

[0013] Grouping the hash value and converting any group from binary to decimal to obtain two key parameters;

[0014] Setting initial values, and selecting at least two initial values and iteration number N0 as the key input to the chaotic system for iteration, forming ciphertext;

[0015] The sending end sends the key parameters, initial values and iteration number N0 as the key of the encryption algorithm, and the ciphertext to the receiving end.

[0016] The setting initial values, and selecting at least two initial values and iteration number N0 as the key input to the chaotic system for iteration, forming ciphertext, comprises:

[0017] Using the chaotic system to iterate any initial value xi for N0+2 times, discarding the first N0 iteration results, obtaining at least two chaotic sequences Xi;

[0018] Splicing all the chaotic sequences into a final sequence X, and generating a permutation sequence Y and a diffusion sequence Z;

[0019] Forming ciphertext according to the permutation sequence Y and the diffusion sequence Z.

[0020] Splicing all the chaotic sequences into a final sequence X, and generating a permutation sequence Y and a diffusion sequence Z, comprises:

[0021] ;

[0022] ;

[0023] Wherein, X is a chaotic sequence; MxN is the size of the picture.

[0024] Forming ciphertext according to the permutation sequence Y and the diffusion sequence Z, comprises:

[0025] Using the permutation sequence Y to perform permutation operation on the preset string b64Str, converting the Base64 code at this time into the corresponding index, obtaining b64index;

[0026] Using the diffusion sequence Z to perform diffusion operation on the b64index, obtaining b64diffused;

[0027] Taking the b64diffused as ciphertext.

[0028] Using the diffusion sequence Z to perform diffusion operation on the index Index to obtain b64diffused, comprises:

[0029] b64diffused = b64index ⊕ Z;

[0030] wherein represents an exclusive or operation.

[0031] The preset character string b64Str includes:

[0032] A pseudo-random sequence is generated by iterating a chaotic system.

[0033] Three basic grayscale images are obtained, each with a size of MxN.

[0034] The three basic grayscale images are combined into an RGB color image as red, green, and blue channels, respectively.

[0035] The RGB color image is encoded into a Base64 string b64Str using Base64 encoding, with a size of 4xMxN.

[0036] The chaotic system includes:

[0037]

[0038] wherein n represents the number of iterations of the chaotic system; is the value of the chaotic system at the nth iteration; r is a control parameter used to adjust the chaotic behavior of the system; is an exponential function with base e, the base of the natural logarithm, is the exponential; is the value of the chaotic system at the (n-1)th iteration, i.e., the result of the previous iteration.

[0039] The key parameter acquisition includes:

[0040] SHA-256 hash operation is performed on the original inspection image to generate a 256-bit hash value h.

[0041] The hash value h is divided into 8 groups, each with 32 bits.

[0042] Each group is converted from binary to decimal to obtain 8 parameters R1, R2, …, R8.

[0043] Two key parameters h1 and h2 are generated through an exclusive or operation.

[0044] The key parameter acquisition includes:

[0045] ;

[0046] .

[0047] An unmanned aerial vehicle (UAV) inspection traffic control method based on a chaotic system, based on the UAV inspection traffic control system, comprising:

[0048] The original inspection image obtained in the unmanned aerial vehicle inspection is collected and a hash operation is performed to generate a hash value;

[0049] The hash value is grouped, and binary-to-decimal conversion is performed on any group to obtain two key parameters;

[0050] An initial value is set, and at least two initial values and an iteration number N0 are selected as key inputs to the chaotic system for iteration to form a ciphertext;

[0051] The sending end uses the key parameters, the initial value, and the iteration number N0 as the key of the encryption algorithm, and sends the ciphertext to the receiving end.

[0052] Beneficial effects:

[0053] The beneficial effects of the present disclosure include at least:

[0054] The unmanned aerial vehicle inspection traffic control system based on a chaotic system according to the present disclosure obtains the original inspection image obtained in the unmanned aerial vehicle inspection through a sending end; an encryption module is used to encrypt the original inspection image to obtain encrypted image data; the receiving end interacts with the encryption module to obtain the encrypted image data; the original image is encrypted by the encryption module to form encoded data; the encoded data has better compatibility, is suitable for embedding different structured data formats, ensures data integrity while taking into account protocol friendliness, reduces errors that may occur during transmission, improves transmission advantages and the high application value in network transmission. Moreover, the chaotic system is used for encryption in the present disclosure, which has more complex dynamic behavior, reduces output unevenness, and has a larger chaotic range; at the same time, the initial value and the control parameter in the encryption process have higher sensitivity, resist brute force cracking, and improve the advantages of application in the security field; and the chaotic system has a larger chaotic region, stronger theoretical robustness, higher engineering fault tolerance, more flexible system design space, and superior security performance. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 is a system block diagram of the present disclosure;

[0056] Figure 2 is a chaotic characteristic diagram of the present disclosure and other chaotic systems when the control parameter is large;

[0057] Figure 3 is a chaotic characteristic diagram of the present disclosure and other chaotic systems when the control parameter is small;

[0058] Figure 4 is a sample entropy curve diagram of the present disclosure and other chaotic systems;

[0059] Figure 5 is a 0-1 test K value graph of the present disclosure;

[0060] Figure 6 is a 0-1 test K value graph of the present disclosure and other chaotic systems;

[0061] Figure 7 is an initial value sensitivity test graph of the present disclosure;

[0062] Figure 8 is a control parameter sensitivity test graph of the present disclosure;

[0063] Figure 9 is an original image, an encrypted image, a correct key decryption, and an incorrect key decryption image in the method embodiment of the present disclosure;

[0064] Figure 10 is a flowchart of the method of the present disclosure. DETAILED DESCRIPTION

[0065] Hereinafter, various embodiments of the present disclosure will be described more fully. The present disclosure can have various embodiments, and adjustments and changes can be made therein. However, it should be understood that there is no intention to limit various embodiments of the present disclosure to the specific embodiments disclosed herein, but the present disclosure should be understood to encompass all adjustments, equivalents, and / or alternatives falling within the spirit and scope of various embodiments of the present disclosure.

[0066] Hereinafter, the term "include" or "may include" used in various embodiments of the present disclosure indicates the presence of the disclosed function, operation, or element, and does not limit the addition of one or more functions, operations, or elements. In addition, as used in various embodiments of the present disclosure, the terms "include", "have", and their cognates merely mean to indicate a specific feature, number, step, operation, element, component, or combination of the foregoing, and should not be understood as first excluding the presence or addition of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing, or the possibility of one or more features, numbers, steps, operations, elements, components, or combinations of the foregoing.

[0067] In various embodiments of the present disclosure, the expression "or" or "at least one of A or / and B" includes any combination of the listed terms or all combinations thereof. For example, the expression "A or B" or "at least one of A or / and B" can include A, can include B, or can include both A and B.

[0068] The expressions used in the various embodiments of the disclosure, such as "first", "second", etc., can modify various constituent elements in the various embodiments, but can not limit the corresponding constituent elements. For example, the above expressions do not limit the order and / or importance of the elements. The above expressions are only for the purpose of distinguishing one element from other elements. For example, the first user device and the second user device indicate different user devices, although both are user devices. For example, without departing from the scope of the various embodiments of the disclosure, a first element can be referred to as a second element, and likewise, a second element can be referred to as a first element.

[0069] It should be noted that if a description connects one constituent element to another constituent element, the first constituent element can be directly connected to the second constituent element, and a third constituent element can be "connected" between the first constituent element and the second constituent element. Conversely, when one constituent element is "directly connected" to another constituent element, it can be understood that there is no third constituent element between the first constituent element and the second constituent element.

[0070] The term "user" used in the various embodiments of the disclosure can indicate a person using an electronic device or a device (for example, an artificial intelligence electronic device) using an electronic device.

[0071] The terms used in the various embodiments of the disclosure are only for the purpose of describing specific embodiments and are not intended to limit the various embodiments of the disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly dictates otherwise. Unless otherwise defined, all terms used herein, including technical terms and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of the disclosure belong. The terms such as those defined in a generally used dictionary will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of the disclosure.

[0072] The defects of the existing unmanned aerial vehicle inspection system image encryption algorithm are as follows:

[0073] 1. Encryption efficiency problem and insufficient support for multi-image encryption technology:

[0074] Some existing image encryption algorithms have low efficiency when processing large-scale image data. For example, some encryption algorithms based on complex mathematical transformations (such as compressed sensing) have high security, but require a large number of matrix operations during encryption, resulting in long encryption time.

[0075] Many existing image encryption algorithms mainly focus on single image encryption, and lack effective integration solutions for multiple image encryption. In practical applications, unmanned aerial vehicle image data transmission often needs to transmit multiple images simultaneously, while existing encryption algorithms mostly need to encrypt each image separately, increasing the computational complexity and data transmission overhead.

[0076] 2. Lack of intrinsic safety:

[0077] Base64 encoding is essentially a way to convert binary data into printable ASCII characters. It was not designed for data encryption, but only to ensure smooth transmission of data in certain environments. This means that once the image data transmitted using Base64 encoding is received, anyone with basic decoding tools can easily restore the original data, making sensitive information obtained by unmanned aerial vehicle inspection, such as details of critical infrastructure and images of classified areas, completely insecure, and easily causing data leakage, posing a serious threat to national security. As an encoding mechanism, it only achieves data format conversion and lacks real encryption protection.

[0078] 3. Data expansion causes transmission bottleneck:

[0079] Base64 encoding causes data volume to expand by 33%. Actual data shows that in a 4G network environment, the transmission delay of 1080P inspection images increases by 40-60ms, and when performing high-definition three-dimensional modeling, the data transmission time for a single task is extended by more than 12 minutes. The present invention uses a new image encryption system that encrypts images based on their characteristics, which is more efficient than traditional schemes that first encode images as text and then encrypt them.

[0080] 4. Poor adaptability to network transmission

[0081] Most image encryption algorithms in existing unmanned aerial vehicle inspection systems do not fully consider the characteristics of network transmission. During transmission, image data may be affected by factors such as network protocols and data formats. For example, some algorithms may not be suitable for direct transmission in the network after encryption, requiring additional encoding or format conversion, increasing the complexity and likelihood of errors in transmission.

[0082] A chaotic system is a nonlinear dynamic system. Due to its pseudo-randomness, sensitivity to initial conditions, non-periodicity and long-term unpredictability, chaotic systems are very suitable for image encryption with large data volume and strong correlation. Applying chaotic systems to image encryption is more secure and efficient than classical cryptographic systems. The shortcomings of existing chaotic systems are as follows:

[0083] 1. Lack of behavioral complexity:

[0084] Existing chaotic systems, such as the Logistic chaotic system, while having certain chaotic characteristics, may exhibit lower dynamic complexity within certain parameter ranges. For example, the Logistic chaotic system exhibits periodicity in its output sequence when the parameter is less than 3.56, rather than a true chaotic state. This makes encryption algorithms based on such chaotic systems less secure when faced with complex attacks.

[0085] 2. Insufficient sensitivity to initial values and control parameters:

[0086] Some existing chaotic systems do not have high enough sensitivity to initial values and control parameters. In encryption algorithms, the sensitivity to initial values and control parameters is an important indicator of algorithm security. If the sensitivity of a chaotic system to these parameters is not high enough, an attacker may be able to crack the encryption algorithm through minor adjustments.

[0087] 3. Limited chaotic region:

[0088] Existing chaotic systems, such as the Logistic-Sine-Cosine chaotic system, may have a relatively narrow chaotic region in the parameter space. This means that within certain parameter ranges, the chaotic system may not be able to maintain a chaotic state, affecting the security of the encryption algorithm. In addition, existing chaotic systems exhibit non-chaotic states within certain parameter intervals, which limits the parameter selection for encryption algorithms based on these chaotic systems and makes them vulnerable to attackers finding the appropriate parameter range to crack.

[0089] To address the above problems, the present disclosure provides the following embodiments. Specific embodiment 1:

[0091] The present disclosure provides an embodiment:

[0092] An unmanned aerial vehicle (UAV) inspection traffic control system based on a chaotic system includes a sending end 100, an encryption module 200, and a receiving end 300. The sending end 100 is configured to obtain original inspection images obtained during UAV inspection. The encryption module 200 interacts with the sending end 100 to encrypt the original inspection images and obtain encrypted image data. The receiving end 300 interacts with the encryption module 200 to obtain the encrypted image data.

[0093] The encryption module 200 encrypts the original inspection images through the following process:

[0094] The original inspection image obtained in the unmanned aerial vehicle inspection is collected, and a hash operation is performed to generate a hash value; the hash value is grouped, and binary-to-decimal conversion is performed on any group to obtain two key parameters; initial values are set, and at least two initial values and an iteration number N0 are selected as keys to input into the chaotic system for iteration to form a ciphertext; the sending end sends the key parameters, initial values, and iteration number N0 as the keys of the encryption algorithm to the receiving end together with the ciphertext.

[0095] Specifically, a pseudo-random sequence is generated by iteration of the chaotic system proposed in the application, and the mathematical expression of the chaotic system is as follows:

[0096] ;

[0097] Wherein, r is a control parameter for adjusting the chaotic behavior of the system;

[0098] Three gray-scale images are input, and each image has a size of MxN;

[0099] The three gray-scale images are combined into an RGB color image img(MxNx3) as red, green, and blue channels;

[0100] The RGB color image is encoded into a Base64 string b64Str using Base64 encoding, and the size is 4xMxN;

[0101] The original image is subjected to SHA-256 hash operation to generate a 256-bit hash value h;

[0102] The hash value h is divided into 8 groups, each with 32 bits;

[0103] Each group is converted from binary to decimal to obtain 8 parameters R1, R2, …, R8;

[0104] Two key parameters h1 and h2 are generated by XOR operation:

[0105] ;

[0106] ;

[0107] Select 8 initial values x i ,i=1,2,…,8, and an iteration number N0 as keys to input into the chaotic system proposed in the application;

[0108] Each initial value x i is iterated N0+2 times using the chaotic system, and the first N0 iteration results are discarded to obtain 8 chaotic sequences X i ;

[0109] Modify the N0+2th chaotic value:

[0110] For : ;

[0111] For :

[0112] Continue iterating 2M×N times to get 8 chaotic sequences X i ;

[0113] Concatenate the 8 chaotic sequences into a final sequence X, and generate two control sequences:

[0114] ;

[0115] .

[0116] Use the permutation sequence Y to perform a permutation operation on the Base64 string b64Str, and the permutation operation is as follows:

[0117] Starting from the 1st character, process each character in the Base64 string b64Str one by one until the 4×M×Nth character, which is the end of the Base64 string. Here, 4×M×N is the length of the Base64 encoded string, corresponding to the size of the original image.

[0118] For the character b64Str(i) at the current index i, store its value temporarily in the variable temp. This step is to preserve the value of the current character for subsequent operations.

[0119] Replace the character b64Str(i) at index i with the character b64Str(Y(i)) at the corresponding position in the permutation sequence Y.

[0120] Then, assign the temporarily stored character temp (i.e., the original b64Str(i)) to position Y(i).

[0121] This step actually exchanges the characters b64Str(i) and b64Str(Y(i)), achieving the obfuscation effect based on the permutation sequence Y.

[0122] The permutation operation pseudo code is as follows:

[0123] for i = 1 to 4 × M × N:

[0124] temp = b64Str(i)

[0125] b64Str(i) = b64Str(Y(i))

[0126] b64Str(Y(i)) = temp

[0127] Convert the Base64 code at this time into the corresponding index Index, and the table shows that Char represents the Base64 character, and the table is as follows

[0128]

[0129] Diffuse the index Index using the diffusion sequence Z to obtain b64diffused, wherein represents the exclusive or operation

[0130] b64diffused(i) = b64index(i) ⊕ Z(i)

[0131] Re-encode b64diffused according to the table into Base64 code, and the encryption algorithm is completed

[0132] The sender sends the key h1 and h2, 8 initial values xi (i = 1, 2, …, 8) and the number of iterations N0 as the encryption algorithm key, and b64diffused as the encrypted ciphertext to the receiver.

[0133] In summary, the system described in the embodiment can have higher encryption efficiency in a short time, and the encryption effect is better, so it is more suitable for network transmission; moreover, it can solve the problems of traditional single-image encryption algorithm in processing multi-image scenes, such as low efficiency and inability to fully utilize the correlation between images, etc. Three gray-scale pictures can be encrypted at a time, multi-image encryption can be realized, security, robustness and computing efficiency can be ensured; the encryption algorithm based on Base64 coding proposed in the embodiment can well adapt to network transmission, convert image data into ASCII characters, construct a new discrete chaotic system (1D-SLCM), and test its chaotic performance.

[0134] By using 1D-SLCM and Base64 coding, the embodiment constructs a multi-image system. In work, a new plaintext correlation framework using SHA-256 hash function is proposed and applied to encrypt the original image to enhance the sensitivity of the plaintext. The complete simulation experiment proves the security and reliability of the system. The coded data has better compatibility, is suitable for embedding different structured data formats, ensures data integrity while also considering protocol friendliness, reduces possible errors in the transmission process, improves transmission advantages and high application value in network transmission.

[0135] Meanwhile, for the chaotic system used in this embodiment, in view of the low complexity of the dynamic behavior of the traditional chaotic system, the uneven output, the small chaotic range and other characteristics, this embodiment has more complex dynamic behavior, reduces the uneven output and has a larger chaotic range; moreover, the initial value and the control parameter have higher sensitivity, resist brute force cracking and improve the advantages of its application in the security field; meanwhile, it has a larger chaotic region and stronger theoretical robustness, and can be directly converted into: higher engineering fault tolerance, more flexible system design space and more superior security performance.

[0136] Verification link:

[0137] I. Test of chaotic system: the chaotic system in this embodiment is called 1D-SLCM.

[0138] 1. Lyapunov exponent (Lyapunov Exponent, LE): By calculating the maximum Lyapunov exponent, it can be determined whether the system has chaotic characteristics. If the maximum exponent is positive, it indicates that the system is extremely sensitive to initial conditions, and the trajectory diverges exponentially, which belongs to a chaotic system; if it is negative, the system tends to be stable. A positive LE value indicates that the system has chaotic characteristics. The positive and negative of the Lyapunov exponent and its size reflect the stability of the system in different directions in the phase space. Negative values indicate that the perturbation decays (stable), and positive values indicate that the perturbation grows (unstable). When all exponents are negative, the system may converge to a fixed point or a periodic orbit. The larger the positive Lyapunov exponent value, the more sensitive the system is to initial conditions, and the worse the long-term predictability.

[0139] As Figures 2-3 , based on the test results of the Lyapunov exponent, the 1D-SLCM system exhibits significant advantages in chaotic characteristics. Through systematic testing of its parameter space, as shown in the figure, the 1D-SLCM continuously has a larger LE value in a wide parameter range, and a higher positive LE value indicates that the divergence rate of the 1D-SLCM trajectory is faster, and the sensitivity of the system to small differences in initial conditions is stronger, much higher than the diffusion amplitude of the comparative system. This characteristic can be converted into higher key sensitivity in the encryption system. Faster divergence speed and higher unpredictability are important for encryption systems. The 1D-SLCM exhibits a larger positive LE value in a wider parameter range, indicating that it has a high sensitivity to initial conditions, which is superior to other chaotic systems (such as Logistic-Sine-Cosine, 1-DFCS, 1-DSP, etc.). The high positive LE characteristic and parameter adaptability of the 1D-SLCM make it an ideal candidate system for the next generation of chaotic engineering (such as secure communication, biomedical signal encryption).

[0140] 2. Sample entropy (Sample Entropy, SE):

[0141] In the field of time series analysis, sample entropy (SE) is a crucial analytical metric with extremely important testing purposes. Its core function is to accurately measure the self-similarity and complexity of a time series through rigorous quantitative methods. In principle, sample entropy is primarily calculated based on the degree of repetition of patterns in the time series. Lower pattern repetition in a time series indicates greater randomness and uncertainty, resulting in a higher sample entropy value; conversely, higher pattern repetition suggests stronger regularity, leading to a lower sample entropy value. Therefore, a higher SE value intuitively reflects a more complex internal structure and dynamic characteristics within the time series, indicating greater complexity. This test is used to measure the self-similarity and complexity of a time series.

[0142] like Figure 4 In this test of time series generated by various chaotic systems, the time series generated by 1D-SLCM exhibited significantly higher sample entropy values ​​than those generated by other chaotic systems. This result fully demonstrates that the time series generated by 1D-SLCM performs exceptionally well in terms of complexity, and is significantly superior to other chaotic systems in terms of self-similarity and complexity characteristics.

[0143] 3. 0-1 test:

[0144] The chaotic behavior of a system is determined by the 0-1 test. When the K value approaches 1, it indicates that the system is in a chaotic state, exhibiting high uncertainty, irregularity, and an exponential amplification effect on small disturbances. When the K value approaches 0, it indicates that the system is in a regular or periodic state.

[0145] The calculation method is as follows:

[0146] ;

[0147] X(i) is the sequence of generated iterations.

[0148] like Figures 5-6 According to the test results, the 0-1 test result of 1D-SLCM is close to 1 in a wide range of parameters (r∈(1.4,350)), which indicates that the system has good chaotic properties in this parameter range.

[0149] 4. Initial value sensitivity and parameter sensitivity test

[0150] The chaotic system was iterated using initial values ​​and parameters that differed by 10^-15.

[0151] Verify whether 1D-SLCM is highly sensitive to small changes in the initial value, ensuring that it meets the core requirements of key security in cryptography.

[0152] Figures 7-8 The red and blue parts represent chaotic sequences generated by iterating with different values, indicating that the chaotic system has good sensitivity to initial values ​​and parameters.

[0153] 5. NIST SP 800-22 test:

[0154] The randomness of sequences generated by the chaotic system 1D-SLCM was evaluated using NIST tests to ensure its suitability for image encryption. The sequences were verified to meet internationally accepted cryptographic security standards through 15 NIST tests.

[0155] Test results: The sequences generated by 1D-SLCM passed all 15 NIST tests, and the P-values ​​of all subtests were within the range of (0.001,1), meeting the passing standard. This indicates that the generated sequences have good randomness, meet the stringent requirements of encryption systems for randomness, resist statistical attacks, effectively protect information security, and are suitable for image encryption.

[0156]

[0157] In summary, through the above-mentioned various testing methods, the chaotic system proposed in this embodiment outperforms other existing chaotic systems in terms of chaotic characteristics, complexity, and randomness.

[0158] II. Verification of Image Transmission Encryption Effectiveness:

[0159] Test environment:

[0160] Platform: Matlab 2021a;

[0161] Hardware configuration: CPU 2.60GHz, 16GB RAM, Windows 11 operating system;

[0162] Test images: Multiple grayscale images (such as Pepper, Baboon, Sailboat, etc.) with a resolution of 512×512 were used;

[0163] Encryption and decryption effects:

[0164] Encrypted images: The encrypted images are completely unrecognizable from the original images and appear as noisy images.

[0165] Image decryption: Using the correct key, the original image can be fully recovered, while using the wrong key will prevent the recovery of any meaningful information, such as... Figure 9 . Figure 9 In the example, (a) is the original image; (b) is the encrypted image; (c) is the image decrypted using the correct key; and (d) is the image decrypted using the wrong key.

[0166] 2. Encryption time analysis;

[0167] Objective: To verify the running efficiency of the algorithm.

[0168] Test images: Three gray-scale images (Pepper, Baboon, Sailboat), with sizes of 512x512, 256x256 respectively.

[0169] Results: (average encryption time of each gray-scale image)

[0170] 512x512 image: 0.3004 seconds;

[0171] 256x256 image: 0.1229 seconds;

[0172] Time complexity: The time complexity of the encryption algorithm proposed in the present application is measured using the big O time complexity. Taking an MxN image as an example, the operation time complexity of encoding it into Base64 encoding is O(MxN), the time complexity of the permutation operation is O(4MxN / 3), and the time complexity of the diffusion operation is O(4MxN). There is no operation in the algorithm with a time complexity of O(MN), so the final algorithm time complexity is O(MN);

[0173] Conclusion: The algorithm has good running efficiency while ensuring security, and is suitable for real-time encryption and large-scale data processing.

[0174] 3. Peak signal-to-noise ratio (PSNR) analysis;

[0175] PSNR is used to measure the difference between two images. The larger the PSNR value, the more similar the two images are. If the two images are exactly the same, the size of MSE is 0, and the PSNR at this time is infinite. Therefore, when evaluating the difference between the encrypted image and the original image, a low PSNR value indicates better encryption effect.

[0176] The calculation method is as follows:

[0177]

[0178] where P is the original image, C is the ciphertext image, and M and N represent the size of the image.

[0179] The test results are as follows:

[0180] Pepper image: 8.8260 dB;

[0181] Baboon image: 9.5098 dB;

[0182] Sailboat image: 8.2186 dB.

[0183] 4. Plain text sensitivity test

[0184] Encrypt two images that differ by only one pixel, and calculate the difference of the encrypted images. Thus, verify the sensitivity of the algorithm to the plaintext, resist differential attacks and chosen plaintext attacks.

[0185] Calculation method:

[0186]

[0187] Test results:

[0188] The average value of the standard test image NPCR is 99.6072% (the theoretical optimal value is about 99.6094%), and the average value of UACI is 33.4634% (the theoretical optimal value is about 33.4635). It can be seen that the algorithm has high sensitivity to single-pixel differences, close to the theoretical limit.

[0189] In the extreme image test, the encryption results of pure white and pure black images show that the ciphertext is completely randomized, and the NPCR and UACI values meet the standards, proving that the algorithm can still resist attacks under extreme conditions.

[0190]

[0191] In summary, the system described in this embodiment uses a new one-dimensional chaotic system (1D-SLCM), which has passed 0-1 test and initial value sensitivity and parameter sensitivity tests to verify its good chaotic characteristics, higher dynamic complexity, initial value and parameter sensitivity. The pseudo-random sequence generated by the 1D-SLCM is combined with the SHA-256 hash operation and the permutation diffusion operation, so that small changes can be diffused throughout the image, ensuring the unpredictability and security of the key, significantly enhancing the anti-attack ability of the encryption algorithm, and effectively resisting the data integrity threat of the unmanned aerial vehicle when transmitting image data, protecting sensitive information.

[0192] Moreover, the embodiment converts image data into ASCII characters by Base64 encoding, improves the adaptability of encrypted images in network transmission, avoids possible errors in the transmission process, does not require additional encoding or format conversion, and reduces transmission complexity and error probability. Compared with traditional AES and other block cipher algorithms, the stream cipher characteristics of chaotic encryption are more suitable for high-throughput data stream processing in unmanned aerial vehicle scenarios, while avoiding the complexity of key management. It is worth mentioning that this technical solution has passed the NIST SP800-22 randomness test, confirming the cryptographic strength of its key stream, providing technical support for the compliance deployment of the unmanned aerial vehicle inspection system. In the plaintext sensitivity test, the average value of the standard test image NPCR is 99.6072% (the theoretical optimal value is about 99.6094%) and the average value of UACI is 33.4634% (the theoretical optimal value is about 33.4635), close to the theoretical limit; in the extreme image test, the encryption results of the pure white and pure black images show that the ciphertext is completely randomized, and the NPCR and UACI values meet the standards, so it can be seen that the algorithm still has good attack resistance under extreme conditions and can efficiently and securely encrypt unmanned aerial vehicle inspection images containing sensitive information to protect their confidentiality. Embodiment 2:

[0194] The present disclosure also provides an embodiment:

[0195] As Figure 10 A method for unmanned aerial vehicle inspection traffic control based on a chaotic system, based on the unmanned aerial vehicle inspection traffic control system described in Embodiment 1, comprising: collecting the original inspection images obtained in the unmanned aerial vehicle inspection and performing a hash operation to generate a hash value; grouping the hash value and converting any group from binary to decimal to obtain two key parameters; setting an initial value and selecting at least two initial values and an iteration number N0 as the key input to the chaotic system for iteration to form ciphertext; using the sending end to send the key parameters, the initial value and the iteration number N0 as the key of the encryption algorithm to the receiving end together with the ciphertext. Embodiment 3:

[0197] The present disclosure also provides an embodiment:

[0198] An electronic device comprising: a storage medium, a processing unit; wherein the storage medium is used to store a computer program; the processing unit exchanges data with the storage medium, and is used to execute the computer program by the processing unit when transmitting unmanned aerial vehicle inspection images, and perform the steps of the method for unmanned aerial vehicle inspection traffic control based on a chaotic system as described in Embodiment 2.

[0199] The CPU described above can perform various appropriate actions and processes according to a program stored in a storage medium. The electronic device also includes an input section including a keyboard, a mouse, and the like, and can also include an output section including a cathode ray tube (CRT), a liquid crystal display (LCD), and the like, and a speaker, and the like.

[0200] The present disclosure also provides an embodiment of:

[0201] A readable storage medium: the readable storage medium stores a computer program; the computer program, when running, executes the steps of the unmanned aerial vehicle inspection traffic control method based on a chaotic system as described in embodiment 2.

[0202] In the embodiment, the computer readable storage medium can be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, the computer readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which bears computer readable program code. Such a propagated data signal can take any of a variety of forms, including but not limited to electro-magnetic, optical, or any suitable combination thereof. The computer readable signal medium can also be any computer readable medium that is not a storage medium and that can communicate, propagate or transport program for use by or in connection with an instruction execution system, apparatus, or device. Program code contained on a computer readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, optical fiber cable, RF, and the like, or any suitable combination thereof.

[0203] The above disclosure is only a few specific implementation scenarios of the present disclosure, but the present disclosure is not limited thereto, and any changes that can be thought of by those skilled in the art should fall within the protection scope of the present disclosure. The above-mentioned serial numbers of the present disclosure are only for description, and do not represent the advantages and disadvantages of the implementation scenarios.

Claims

1. A chaos system based unmanned aerial vehicle inspection traffic control system, characterized in that, The application relates to a method for encrypting an original inspection image obtained in unmanned aerial vehicle inspection, comprising the following steps: a sending end is used for acquiring the original inspection image obtained in unmanned aerial vehicle inspection; an encryption module is used for interacting with the sending end, and the original inspection image is encrypted to obtain encrypted image data; a receiving end is used for interacting with the encryption module and acquiring the encrypted image data; the encryption module encrypts the original inspection image through the following process: an original inspection image obtained in unmanned aerial vehicle inspection is collected, and a hash value is generated through hash operation; the hash value is grouped, and binary-to-decimal conversion is performed on any group to obtain two key parameters; initial values are set, at least two initial values and an iteration number N0 are selected as key inputs of the chaotic system for iteration to form a ciphertext; the sending end sends the key parameters, the initial values and the iteration number N0 as encryption algorithm keys to the receiving end together with the ciphertext; the key parameters are acquired through the following steps: SHA-256 hash operation is performed on the original inspection image to generate a 256-bit hash value h; the hash value h is divided into 8 groups, each group having 32 bits; binary-to-decimal conversion is performed on each group to obtain 8 parameters R1, R2,..., R8; two key parameters h1 and h2 are generated through XOR operation; the key parameters are acquired through the following steps:

2. The unmanned aerial vehicle patrol traffic control system based on chaotic system according to claim 1, characterized in that, the initial values are set, at least two initial values and an iteration number N0 are selected as key inputs of the chaotic system for iteration to form a ciphertext, which comprises the following steps: using the chaotic system for any initial value x i performing N0+2 iterations, discarding the first N0 iterations, obtaining at least 2 chaotic sequences X i ; all the chaotic sequences are spliced into a final sequence X, and a permutation sequence Y and a diffusion sequence Z are generated; the ciphertext is formed according to the permutation sequence Y and the diffusion sequence Z.

3. The unmanned aerial vehicle patrol traffic control system based on chaotic system according to claim 2, characterized in that, the all the chaotic sequences are spliced into a final sequence X, and a permutation sequence Y and a diffusion sequence Z are generated, which comprises the following steps: wherein X is a chaotic sequence; MxN is the size of the picture.

4. The unmanned aerial vehicle patrol traffic control system based on chaotic system according to claim 2, characterized in that, the ciphertext is formed according to the permutation sequence Y and the diffusion sequence Z, which comprises the following steps: the permutation sequence Y is used to perform permutation operation on a preset string b64Str, so that the Base64 code at the moment is converted into a corresponding index to obtain b64index; the diffusion sequence Z is used to perform diffusion operation on the b64index to obtain b64diffused; the b64diffused is used as the ciphertext.

5. The unmanned aerial vehicle patrol traffic control system based on chaotic system according to claim 4, characterized in that, the diffusion sequence Z is used to perform diffusion operation on the index Index to obtain b64diffused, which comprises the following steps: wherein represents an exclusive OR operation.

6. The unmanned aerial vehicle patrol traffic control system based on chaotic system according to claim 4, characterized in that, the preset string b64Str comprises the following steps: a pseudo-random sequence is generated through chaotic system iteration; three basic gray images are acquired, each image having a size of MxN; the three basic gray images are combined into an RGB color image as red, green and blue channels respectively; the RGB color image is encoded into a Base64 string b64Str through Base64 encoding, and the size of the Base64 string b64Str is 4xMxN.

7. The unmanned aerial vehicle patrol traffic control system based on chaotic system according to claim 1 or 2 or 6, characterized in that, the chaotic system comprises the following steps: where n represents the number of iterations of the chaotic system; x n is the value of the chaotic system at the nth iteration; r is a control parameter used to adjust the chaotic behavior of the system; is an exponential function with base e, the natural logarithm, x n-1 is the exponent; x n-1 is the value of the chaotic system at the n-1th iteration, i.e., the result of the previous iteration.

8. A method for unmanned aerial vehicle inspection of traffic control based on a chaotic system, based on the unmanned aerial vehicle inspection of traffic control system of claim 1, characterized in that, the original inspection image obtained in unmanned aerial vehicle inspection is collected, and a hash value is generated through hash operation; the hash value is grouped, and binary-to-decimal conversion is performed on any group to obtain two key parameters; ​ Setting initial values, and selecting at least two initial values and iteration number N0 as the key input to the chaotic system for iteration, forming ciphertext; Using the sending end to send the key parameters, initial values and iteration number N0 as the key of the encryption algorithm, and the ciphertext to the receiving end.

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