An internet of vehicles image encryption authentication method based on AFCSM and selective retransmission

Abstract

The application provides a vehicle networking image encryption authentication method based on AFCSM and selective retransmission, and a vehicle networking image encryption authentication system based on AFCSM and selective retransmission covers a complete closed-loop process from data collection to final delivery; first, the original visual information collected by data sources such as roadside units, vehicle-mounted units and law enforcement departments is gathered to a sender, an initial key is generated through SHA-512 and 4 rounds of Feistel network, and the image is processed in combination with a 2D-AFCSM hyperchaotic sequence. In the encryption stage, the system uses an 8*8 block authentication mechanism to embed SHA-256 codes into the image bit plane, and cooperates with the odd-even bit plane separation technology and the random neighbor diffusion algorithm to generate a ciphertext image, and then the ciphertext image is transmitted through the V2X network; through the selective retransmission mechanism, the communication bandwidth cost in the vehicle networking environment is greatly reduced while ensuring that the image is successfully repaired and restored, and the balance problem among confidentiality, integrity and bandwidth efficiency in the vehicle networking visual transmission is effectively solved.

Description

Technical Field

[0001] This invention relates to the fields of information security and data encryption technology, and in particular to an encryption authentication algorithm for use in Internet of Vehicles (IoV) environments, which has the ability to accurately locate and tamper with the position and perform selective retransmission. Background Technology

[0002] With the development of Intelligent Transportation Systems (ITS), the amount of visual image data captured by vehicle-mounted cameras and other devices in the Internet of Vehicles (IoV) is increasing daily. This data contains highly sensitive information such as license plates and driver biometrics. However, the V2X wireless network on which IoV relies has an inherent openness, making images highly vulnerable to eavesdropping, theft, and malicious tampering during transmission, potentially causing traffic chaos or serious public safety accidents.

[0003] Current image encryption schemes mostly employ chaos theory, which, while offering high confidentiality, still has limitations in the context of connected vehicles (V2X). Firstly, most algorithms lack integrated authentication mechanisms, making it difficult to meet real-time integrity verification requirements. Secondly, V2X network connections are unstable, and traditional verification typically employs a "full retransmission" strategy, meaning that even if partial tampering is detected, the entire image frame must be retransmitted, leading to significant bandwidth waste and communication latency. Therefore, developing an intelligent encryption architecture that balances high-strength encryption with lightweight authentication, accurately locates compromised areas, and enables "selective retransmission" has become a critical requirement for ensuring the security of connected vehicle data. Summary of the Invention

[0004] To address the aforementioned issues and overcome the shortcomings of existing technologies, this invention proposes a vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission. It utilizes a two-dimensional asymmetric feedback coupled Sine map (2D-AFCSM) to provide a cryptographic security foundation, while simultaneously constructing an efficient V2X image encryption and authentication process. The core idea of ​​this method is to first perform independent block processing on the input image, embedding an SHA-256 digest authentication code generated based on the block content during this stage. Subsequently, parity-even plane separation scrambling and random neighbor-based diffusion operations are performed on the watermarked image to finally generate ciphertext. This layered processing architecture, especially the unique embedded block authentication code, enables independent verification of the integrity of local image regions during decryption, thereby achieving precise tamper location and efficient data repair based on the retransmission mechanism.

[0005] A vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission is characterized by the following steps:

[0006] S1: Construct a two-dimensional asymmetric feedback coupled Sine map chaotic system (2D-AFCSM) to provide a chaotic sequence with excellent chaotic properties for encryption algorithms;

[0007] S2: Use a secure hash algorithm combined with a Feistel network to process images and generate initial values ​​and control parameters for a chaotic system related to the plaintext image to be processed;

[0008] S3: Iterate the chaotic system based on the initial value and control parameters to generate five sets of chaotic sequences for different encryption stages: plane pairing sequence SM, position exchange sequence SE, diffusion mask sequence DE, traversal order sequence PS, and random direction sequence DR;

[0009] S4: Divide the plaintext image to be processed into 8×8 pixel blocks, extract the core content of each block to generate an authentication code and embed it into the least significant bit (LSB) plane to give it subsequent anti-tampering and positioning capabilities, and generate a watermarked image.

[0010] S5: Perform odd-even plane separation (OES) scrambling on the watermarked image, and use chaotic sequences SM and SE to achieve synchronous processing at the pixel level and plane level;

[0011] S6: Apply the Random Neighbor Diffusion (RND) algorithm and use the chaotic sequences DE, PS and DR to diffuse and encrypt the scrambled watermarked image pixel data;

[0012] S7: At the receiving end, image decryption and block verification are performed. If tampering is detected, a retransmission request is initiated only for the coordinates of the tampered block and the image is restored.

[0013] The beneficial effects of the above technical solution are as follows:

[0014] (1) The 2D-AFCSM system proposed in this invention has a large Lyapunov exponent and complex nonlinear dynamic characteristics. Combined with a key generation mechanism that is deeply bound to the plaintext content, it can effectively resist differential attacks and known plaintext attacks.

[0015] (2) It integrates a block-based lightweight authentication mechanism. This invention solves the problem of "tampering location blind spot" in the encrypted scenario of vehicle network. It can not only detect tampering, but also accurately locate the damaged area by verifying the authentication code extracted from each block.

[0016] (3) The introduction of a selective retransmission mechanism significantly optimizes the allocation of bandwidth resources in the vehicle network. Experimental analysis shows that, in the case of local tampering, this invention can save bandwidth overhead and greatly improve the real-time response capability of the system. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the application of vehicle-to-everything (V2X) image transmission in this invention.

[0018] Figure 2 This is a schematic diagram illustrating the simulated tampering and location process of the present invention. Detailed Implementation

[0019] Chaos theory, due to its pseudo-randomness, unpredictability, and high sensitivity to initial conditions and parameters, is not only one of the most commonly used but also one of the most effective methods in the field of image encryption. This invention proposes a novel two-dimensional asymmetric feedback-coupled Sine map (2D-AFCSM), which possesses excellent hyperchaotic properties and is more suitable for high-security encryption tasks compared to some commonly used chaotic systems.

[0020] The core architecture of this invention's algorithm is a hierarchical encryption and dynamic verification mode. First, an image content digest is extracted using 8×8 block technology and embedded as a unique authentication code into the least significant bit plane, which is crucial for accurate tamper location. Next, parity-even bit plane separation scrambling is performed on the watermarked image, simultaneously breaking the spatial correlation of data at the pixel and bit plane levels. Finally, a random neighbor diffusion algorithm based on ten random directions is applied to thoroughly destroy the statistical and structural features of the image through a nonlinear feedback mechanism, and a selective retransmission mechanism is used to achieve efficient data repair at the decryption end.

[0021] The specific steps are as follows:

[0022] I. Constructing a two-dimensional asymmetric feedback-coupled Sine map

[0023] All chaotic sequences in this invention are generated by a novel 2D-AFCSM. Its system equations are defined as follows:

[0024]

[0025] in, and It is the first System state variables at the next iteration; These are control parameters. The system possesses excellent statistical properties and hyperchaotic behavior, providing reliable pseudo-randomness for encryption.

[0026] II. Key Generation and Chaotic Sequence Generation

[0027] Step 1: Convert plaintext image Generate a 512-bit hash value using the SHA-512 algorithm. Split into 8 integer blocks .

[0028] Step 2: Initialize the Feistel network, setting the initial left half... The initial right half Perform 4 rounds of iteration:

[0029]

[0030] in, Indicates the number of iteration rounds; Representing the The left half of the data block generated by the wheel, Representing the The right half of the data block generated by the wheel; symbol This indicates a bitwise XOR operation; This indicates a circular left shift by one bit;

[0031] Step 3: Utilize the final state output by Feistel The first six 64-bit blocks The initial values ​​and control parameters of the chaotic system are generated using the following formula:

[0032]

[0033] in, ;

[0034] Step 4: Iterate through the AFCSM system, first execute The next iteration eliminates transients. Continuing the iteration, the system produces a length of... The original sequence, where The resolution size of the image; the original sequence is divided into: lengths of The sequence SM, with a length of The sequence SE, with a length of The sequence DE, with length of The sequence PS and its length are DR sequence.

[0035] III. Image Authentication Code Embedding and Encryption

[0036] 1. Authentication code generation and segmented embedding:

[0037] Step 4: Adjust the size of the plaintext image to be processed, whereby... The data is then divided into H non-overlapping 8×8 pixel blocks. The core content of each block (all 8 bits of data in the R and G channels and the high 7 bits of data in the B channel) is extracted and input into the SHA-256 function to generate an authentication code.

[0038] Step 5: Embed the authentication code bit by bit into the least significant bit (LSB) plane of the B channel of this block for subsequent integrity verification.

[0039] 2. Odd / Even Plane Separation and Scrambling:

[0040] Step 6: Convert the pixel values ​​to 8-bit binary form, and separate the odd-numbered bit planes and even-numbered bit planes corresponding to the R, G, and B channels to obtain 6 bit planes. ,in

[0041] And each The length is MN.

[0042] Step 7: Convert the chaotic sequence Grouping, and for the first The six chaotic values ​​of the group are sorted in ascending order. Specifically, the SM is divided into MN groups based on the six numbers (chaotic values), and the group within each group is sorted in ascending order to generate a random index sequence. ,in .

[0043] Step 8: According to The six planes are paired up to generate three sets of dynamic swap pairs to increase the randomness of the scrambling.

[0044] The pairing specifically refers to obtaining six planar planes in step 6. Based on the random index sequence obtained in step 7 Pairing is performed. For example, if the first six random index sequences are 1, 5, 3, 6, 2, and 4, then three pairs are obtained by pairing them: {1,5}, {3,6}, and {2,4}. In this round, an element in plane 1 will be swapped with an element in plane 5 (the specific element swapped is determined by the index sequence generated in step 9). Similarly, in this round, plane 3 will be swapped with a certain element in plane 6, and plane 2 will be swapped with a certain element in plane 4. This process is repeated for a total of MN rounds.

[0045] Step 9: Use the ascending index sequence generated after sorting the chaotic sequence SE in ascending order. in , The current element in is The position of the element to be swapped. This divides the sorted SE into 6 subsequences. Each corresponding to each This performs element swapping between dynamic swap pairs, thus completing the scrambling.

[0046] 3. Random neighbor diffusion:

[0047] Step 10: Generate the diffused sequence DV using the chaotic sequence DE, as shown in the following formula:

[0048]

[0049] in, , , Corresponding to the three RGB channels; The function is used to round down, and an XOR operation is performed between it and the scrambled image PI to obtain the initial diffusion image DP, as shown in the following formula:

[0050]

[0051] in, , , ;

[0052] Step 11: Use the index PSI generated after sorting the chaotic sequence PS in ascending order to determine the processing order of the DP pixels in the initial diffusion image;

[0053] Step 12: For the current pixel node Based on the directional sequence DRI generated by the chaotic sequence DR, where r, o, and t represent the row, column, and channel of the current node, respectively, a specific directional offset is selected from 10 preset offset vectors. The set of 10 preset offset vectors is: (-1,0,0), (1,0,0), (0,-1,0), (0,1,0), (0,0,-1), (0,0,1), (-1,-1,0), (-1,1,0), (1,-1,0), (1,1,0). Neighboring nodes are then jointly calculated using the following formula. The coordinates are given by the following formula:

[0054]

[0055] Step 13: Perform the following diffusion XOR operation to obtain the ciphertext. :

[0056]

[0057] in, The coordinates of the current node. The coordinates of the neighboring nodes are calculated.

[0058] IV. Image Decryption and Anti-Tampering Authentication Process

[0059] 1. Image decryption process:

[0060] Step 14: Regenerate the chaotic sequences required for each stage using the initial key shared with the encryption end.

[0061] Step 15: Perform the reverse diffusion operation. Based on the sequence Given the determined reverse order, perform the inverse XOR operation of steps 12 and 13 on the ciphertext to restore the intermediate matrix before diffusion.

[0062] Step 16: Perform the reverse scrambling operation. Utilize the sequence... and Restore the spatial location and plane pairing relationship of pixels.

[0063] Step 17: Dimension merging, finally obtaining the decrypted plaintext image containing the authentication code.

[0064] 2. Authentication code extraction and verification process: The specific authentication logic is as follows:

[0065] Step 18: Divide the decrypted plaintext image into 8×8 blocks and extract the embedded original authentication code sequence from the least significant bit (LSB) of the blue (B) channel of each block.

[0066] Step 19: Perform SHA-256 hash calculation on the full data of the red (R) and green (G) channels and the high 7 bits of the B channel of the image block in real time to generate the current recalculated check value.

[0067] Step 20: Compare the authentication code extracted in Step 18 with the recalculated verification value in Step 19 bit by bit. If they match completely, the data block is considered complete; if they do not match, the block is precisely located as a damaged area.

[0068] V. Tampering Detection

[0069] As attached Figure 2 As shown, this demonstrates the system's ability to locate and detect malicious tampering attacks. Figure 2 (a) is the original image. Figure 2 (b)-2(d) represents the unaltered process. Assume the ciphertext is subjected to the following during transmission: Figure 2 The malicious tampering shown in (e) is such that, due to the chaotic nature of the ciphertext, the human eye cannot directly determine the location of the damage from the decrypted image 2(f). This invention, through an authentication comparison mechanism, can capture anomalies during the decryption process, thereby... Figure 2 (g) shows the precise coordinates of the tampered area. This location capability not only enables timely detection of attacks but also provides accurate guidance for subsequent local data restoration.

[0070] Working principle and application process description: as attached Figure 1As shown, the vehicle-to-everything (V2X) image encryption and authentication system based on AFCSM and selective retransmission proposed in this invention covers a complete closed-loop process from data acquisition to final delivery. First, raw visual information collected from data sources such as roadside units, vehicle-mounted units, and law enforcement agencies is aggregated to the sender. An initial key is generated using SHA-512 and a 4-wheel Feistel network, and the image is processed using a 2D-AFCSM hyperchaotic sequence. In the encryption stage, the system uses an 8×8 block authentication mechanism to embed the SHA-256 code into the image bit plane, and combines this with odd-even bit plane separation (OES) technology and random neighbor diffusion (RND) algorithm to generate a ciphertext image, which is then transmitted via the V2X network.

[0071] In complex transmission environments, even if encrypted images are illegally obtained or maliciously tampered with by hackers, the system can still protect the original information thanks to its robust dynamic characteristics. When receiving and decrypting an image, the verifier performs real-time detection of image integrity using a built-in authentication and comparison mechanism. Images that are found to be undamaged are directly approved; however, for images detected as attacked, the verifier can accurately pinpoint the pixel coordinates of the damaged blocks and request the repair of specific data blocks from the sender via a secure channel.

[0072] Through this selective retransmission mechanism, the sender only needs to retransmit the damaged local data, without retransmitting the entire image, thus achieving efficient exchange of transmission keys and coordinate information within a secure channel. This design ensures successful image repair and restoration while significantly reducing communication bandwidth overhead in a connected vehicle environment. Ultimately, the verified and repaired high-quality visual data is delivered to the driver or traffic police, effectively solving the balance problem between confidentiality, integrity, and bandwidth efficiency in connected vehicle visual transmission.

[0073] The above description is only for illustrating the present invention and should be understood as not being limited to the above embodiments. Various modifications that conform to the spirit of the present invention are within the protection scope of the present invention.

Claims

1. A vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission, characterized in that, S1: Construct a two-dimensional asymmetric feedback coupled Sine map chaotic system (2D-AFCSM) to provide a chaotic sequence with excellent chaotic properties for encryption algorithms; S2: Use a secure hash algorithm combined with a Feistel network to process images and generate initial values ​​and control parameters for a chaotic system related to the plaintext image to be processed; S3: Iterate the chaotic system based on the initial value and control parameters to generate five sets of chaotic sequences for different encryption stages: plane pairing sequence SM, position exchange sequence SE, diffusion mask sequence DE, traversal order sequence PS, and random direction sequence DR; S4: Divide the plaintext image to be processed into 8×8 pixel blocks, extract the core content of each block to generate an authentication code and embed it into the least significant bit (LSB) plane to give it subsequent anti-tampering and positioning capabilities, and generate a watermarked image. S5: Perform odd-even plane separation (OES) scrambling on the watermarked image, and use chaotic sequences SM and SE to achieve synchronous processing at the pixel level and plane level; S6: Apply the Random Neighbor Diffusion (RND) algorithm and use the chaotic sequences DE, PS and DR to diffuse and encrypt the scrambled watermarked image pixel data; S7: At the receiving end, image decryption and block verification are performed. If tampering is detected, a retransmission request is initiated only for the coordinates of the tampered block and the image is restored.

2. The vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission according to claim 1, characterized in that, The equations for the 2D-AFCSM system are as follows: in, and It is the first The system state variables at the next iteration These are control parameters that adjust the mapping behavior.

3. The vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission according to claim 2, characterized in that, The specific steps for generating the initial values ​​and control parameters of the chaotic system in step S2 are as follows: S2-1: Input the plaintext image to be processed into the SHA-512 algorithm to generate a 512-bit hash value and split it into 8 64-bit integer blocks. ,in ; S2-2: Construct the initial state, let the left half of the initial block... The initial block in the right half The diffusion is achieved through four rounds of Feistel network, with the following iteration rules: in, Indicates the number of iteration rounds; Representing the The left half of the data block generated by the wheel, Representing the The right half of the data block generated by the wheel; symbol This indicates a bitwise XOR operation; This indicates a circular left shift by one bit; S2-3: Utilizing the final state output by Feistel The first six 64-bit blocks The initial values ​​and control parameters of the chaotic system are generated using the following formula: in, .

4. The vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission according to claim 3, characterized in that, The specific process of generating the chaotic sequence in step S3 is as follows: S3-1: Generate the initial value and control parameters Substitute it into the AFCSM system for iteration and execution. The next iteration discards the resulting sequence to eliminate transient effects, where ; S3-2: Continue iterating to generate a system of length... The original sequence, where The pixel resolution of the image; S3-3: Divide the original sequence into: lengths of... The sequence SM, with a length of The sequence SE, with a length of The sequence DE, with length of The sequence PS and its length are DR sequence.

5. The vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission according to claim 1, characterized in that, The specific process of embedding the authentication code in step S4 is as follows: S4-1: Adjust the size of the plaintext image to be processed, where It is then divided into H non-overlapping 8×8 pixel blocks; S4-2: Extract the red (R) channel data, green (G) channel data, and the first 7 most significant bits (MSB) of the blue (B) channel data of each pixel block as core content information, and use the SHA-256 algorithm to calculate the core content information to generate the corresponding block authentication code; S4-3: Embed the block authentication code bit by bit into the least significant bit (LSB) of the blue (B) channel of the corresponding region of the pixel block to generate a watermarked image.

6. The vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission according to claim 5, characterized in that, The specific process of parity-even plane separation and scrambling in step S5 is as follows: S5-1: Convert the pixel values ​​of the watermarked image into 8-bit binary, separate the odd-numbered and even-numbered bit planes corresponding to the 3 channels, and obtain 6 bit planes. ,in And each The length is MN; S5-2: Chaotic sequence Group the data into sets of 6 numbers, i.e., the chaos values, and then... Sort the 6 chaotic values ​​of the group in ascending order to generate a random index sequence. ,in ; S5-3: According to Pair the six planes together to generate three sets of dynamic swap pairs; S5-4: Index sequence generated by sorting the chaotic sequence SE in ascending order ,in , The current element in is The element to be swapped is located at the current position. The element swap is performed between the dynamic swap pairs to complete the scrambling.

7. The vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission according to claim 6, characterized in that, The specific process of random neighbor diffusion in step S6 is as follows: S6-1: Generate a diffused sequence DV using the chaotic sequence DE, as shown in the following formula: in, , , ; This is the floor function. The initial diffusion image DP is obtained by performing an XOR operation with the scrambled watermarked image PI, as shown in the following formula: in, , , ; S6-2: Use the index sequence PSI generated after sorting the chaotic sequence PS in ascending order to determine the processing order of the DP pixels in the initial diffusion image; S6-3: For the current pixel node determined by PSI The direction sequence DRI is generated by sorting the chaotic sequence DR in ascending order, where r, o, and t represent the row, column, and channel of the current node, respectively. A specific direction offset is selected from 10 preset offset vectors. The set of 10 preset offset vectors is: (-1,0,0), (1,0,0), (0,-1,0), (0,1,0), (0,0,-1), (0,0,1), (-1,-1,0), (-1,1,0), (1,-1,0), (1,1,0), and neighbor nodes are jointly calculated according to the following formula. The coordinates are given by the following formula: S6-4: Perform the following diffusion XOR operation to obtain the ciphertext. : in, The coordinates of the current node. The coordinates of the neighboring nodes.

8. The vehicle-to-everything (V2X) image encryption and authentication method based on AFCSM and selective retransmission according to claim 1, characterized in that, The specific steps of image decryption and block verification in step S7 are as follows: S7-1: Regenerate the chaotic sequences required for each stage using the initial values ​​and control parameters shared with the encryption end; S7-2: Perform the reverse diffusion operation based on the sequence. Given a determined reverse order, perform the inverse XOR operation of random neighbor diffusion step S6 on the ciphertext to restore the intermediate matrix before diffusion; S7-3: Perform the reverse scrambling operation, utilizing the sequence... and Restore the spatial location and bit-plane pairing relationship of pixels; S7-4: Dimension merging, ultimately obtaining the decrypted plaintext image containing the authentication code; S7-5: Divide the decrypted plaintext image into 8×8 blocks, and extract the embedded original authentication code sequence from the least significant bit of the blue (B) channel of each block. S7-6: Perform SHA-256 hash calculation on the full data of the red (R) and green (G) channels and the high 7 bits of the blue (B) channel of the image block in real time to generate the current recalculated check value; S7-7: Compare the authentication code extracted from S7-5 with the recalculated checksum from S7-6 bit by bit; if they are completely consistent, the data block is determined to be complete; if they are inconsistent, the block is accurately located as a damaged area.

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