Method, system and equipment for verifying authenticity in rural road condition detection

Abstract

The invention provides an authenticity verification method, system and device applied to rural road condition detection, and the method comprises the steps: carrying out the complete shooting, storage and Hash chain encryption of an original rural road condition image at a detection side, obtaining an encrypted original image, and carrying out the recognition of the original image in the shot original rural road condition image according to a capturing rule, on the verification side, the consistency verification of the Hash chain, the encrypted original image and the encrypted captured image can be carried out, so that the authenticity of the original rural road condition detection is verified, the effectiveness of the detection is ensured, and the detection efficiency is improved. And the device is low in cost and suitable for any detection vehicle speed.

Description

Technical Field

[0001] The present application relates to the field of encryption and decryption technology, and in particular to an authenticity verification method, system and device used in rural road condition detection. Background Art

[0002] Due to the long distances and varying construction dates of rural roads, some roads are characterized by low technical standards and complex types of defects (cracks, potholes, broken slabs, etc.). Regular automated road condition monitoring is essential, and precise maintenance is then implemented based on the results. Key sections require more frequent monitoring. Rural road condition monitoring covers six core indicators, including pavement damage rate and smoothness.

[0003] Road condition test results are stored in the form of photos, and the sheer number of photos presents a risk of tampering. To address this issue, existing technologies offer a blockchain-based evidence storage technology that, through a distributed ledger, ensures that test results cannot be tampered with. However, blockchain-based evidence storage requires the deployment of additional blockchain node equipment, costing at least 2,000 yuan per kilometer. Furthermore, data uploading typically experiences a 3-5 second delay, making it difficult to adapt to dynamic testing scenarios where test vehicles travel at speeds exceeding 40 km / h. Furthermore, capturing photos of road condition test results in a fixed number and frequency increases the risk of tampering. Summary of the Invention

[0004] This application proposes an authenticity verification method, system and equipment for rural road condition detection, which can solve one of the problems existing in the background technology.

[0005] To achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, a method for verifying the authenticity of a rural road condition is provided, the method comprising:

[0007] On the detection side, a unified hash chain is used to perform hash encryption operations on the original rural road condition image and the captured image captured from the original rural road condition image according to the capture rules, thereby obtaining an encrypted original image and an encrypted captured image;

[0008] On the verification side, a consistency check is performed on the hash chain, the encrypted original image and the encrypted captured image to obtain an authenticity check result of the original rural road condition detection.

[0009] Based on the above technical solution, the original rural road condition image is completely captured, stored, and hash chain encrypted on the detection side to obtain an encrypted original image. At the same time, in the original rural road condition image captured, the captured image is captured according to the capture rules and encrypted using the same hash chain to obtain an encrypted captured image. On the verification side, the hash chain, encrypted original image, and encrypted captured image can be checked for consistency to verify the authenticity of the original rural road condition detection. In this way, not only the effectiveness of the detection is guaranteed, but also the cost is low and it is adaptable to any detection vehicle speed.

[0010] In a possible design of the first aspect, the crawling rule is:

[0011] Determine the current number of crawls based on the mileage difference between the current time period and the previous time period; and

[0012] The captured images corresponding to the current captured number are captured.

[0013] In a possible design of the first aspect, the current crawl quantity is determined by:

[0014] N 抓取 =L 里程 ×K d

[0015] K d =K b ×f(v,u)

[0016]

[0017] Among them, N 抓取 is the current number of crawls, L 里程 is the mileage difference between the current time period and the previous time period, K d is the dynamic grasping coefficient, K b is the basic coefficient, v is the speed of the detection vehicle, u is the bump index of the detection vehicle, f is the nonlinear function, p t is the number of pulses in the current time period, p t-1 is the number of pulses in the previous time period, t is the current time period, t-1 is the previous time period, D is the wheel diameter, and PPR is the number of pulses per revolution of the encoder.

[0018] In a possible design of the first aspect, the nonlinear function is Among them, v0 is the vehicle speed reference value, which is used to standardize the actual vehicle speed, W is the road bumpiness index, W0 is the bumpiness index reference value, which is used to standardize the actual bumpiness index, and n and m are both exponential coefficients of the nonlinear function, which determine the degree of nonlinearity of the function with changes in vehicle speed and bumpiness.

[0019] In a possible design of the first aspect, the bump index is obtained by a sensor and is used to measure the degree of bumpiness during operation of the vehicle, and the vehicle is placed on the detection side.

[0020] In a possible design manner of the first aspect, the hash value in the hash chain is determined by the binary data of the captured image, the capture timestamp, and the mileage difference.

[0021] In a second aspect, a authenticity verification system for rural road condition detection is provided, the system comprising:

[0022] The detection side device uses a unified hash chain to perform hash encryption operations on the original rural road condition image and the captured image captured from the original rural road condition image according to the capture rule, thereby obtaining an encrypted original image and an encrypted captured image; and

[0023] The verification side device performs consistency verification on the hash chain, the encrypted original image and the encrypted captured image to obtain the authenticity verification result of the original rural road condition detection.

[0024] In a third aspect, an electronic device is provided, comprising: a processor, and a memory coupled to the processor, the memory being used to store a computer program; and the processor being used to execute the computer program stored in the memory, so that the electronic device performs the method as any possible implementation in the first aspect.

[0025] In a fourth aspect, a computer-readable storage medium is provided, comprising a computer program or instructions, which, when executed on a computer, causes the computer to execute the method of any possible implementation of the first aspect.

[0026] In a fifth aspect, a computer program product is provided, comprising: a computer program or instructions, which, when the computer program or instructions are run on a computer, causes the computer to execute the method of any possible implementation of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0028] Figure 1This is a flow chart of a method for verifying the authenticity of rural road condition detection data based on dynamic encryption and decryption of key indicators of source data provided by an embodiment of the present application;

[0029] Figure 2 This is a schematic diagram of the authenticity verification results of the client software provided in the embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0031] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0032] 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 this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0033] The embodiment of the present application provides a method for verifying the authenticity of rural road condition detection data based on dynamic encryption and decryption of key indicators of source data. Through the collaboration of software and hardware, it prevents tampering of source data and ensures the integrity and authenticity of detection data.

[0034] 1. The embodiments of the present application aim to solve the following major technical problems existing in the existing rural road condition detection:

[0035] 1. Data authenticity risk:

[0036] The original file is detected and stored as plain text, and the Exchangeable Image File Format (EXIF) information (such as GPS coordinates and timestamp) can be tampered with by image editing software or the image content can be directly replaced.

[0037] 2. Insufficient verification methods:

[0038] Although GPS positioning bound to photo coordinates can associate location information, it cannot prevent positioning tampering and data replacement; random inspections are limited by the low proportion of random inspections (the proportion of on-site random inspections at the provincial level in previous years was 5%), a large time span (the time difference between county-level self-inspections and provincial-level random inspections can be up to 4 months), differences in equipment accuracy (such as measurement deviations between laser profilers and ordinary cameras) and inconsistent standard implementation (such as the high subjectivity in determining crack width), making it difficult to detect systematic data distortion problems.

[0039] 3. Technical limitations:

[0040] Although blockchain technology can ensure that data cannot be tampered with, it requires additional hardware investment and system transformation. In addition, its high-concurrency write performance cannot meet the real-time needs of massive rural road inspection data, and there is a processing delay problem.

[0041] 4. Poor environmental adaptability:

[0042] Fixed grabbing frequency cannot adapt to the dynamic adaptability of vehicle speed changes and road bumps.

[0043] 2. To solve the above technical problems, this embodiment provides a method for verifying the authenticity of rural road condition detection data based on dynamic encryption and decryption of key indicators of source data. The method dynamically adjusts the capture strategy in real time based on vehicle speed and bumpiness index, and ensures data authenticity through encryption and hash verification, including:

[0044] 1. Client software installation and deployment:

[0045] Install the client software on the inspection vehicle control computer and interact with the inspection equipment encoder and sensor in real time through the API interface.

[0046] The software includes a dynamic capture module, an encryption storage module, an authenticity verification module and a data communication module.

[0047] 2. Dynamic capture and encrypted storage:

[0048] When the inspection vehicle starts inspection work, it is necessary to simultaneously enable the client software to capture the inspection data in real time and encrypt and store it using the AES-256+RSA algorithm.

[0049] 3. Data authenticity verification:

[0050] The captured data packets are decrypted by the client software and compared with the detection reported data to analyze the authenticity and integrity of the data.

[0051] 3. Technical Details

[0052] (1) Dynamic crawling

[0053] The number of grabs is dynamically adjusted based on real-time mileage and a dynamic coefficient, ensuring unpredictable capture rates. This algorithm uses onboard encoders to calculate mileage and speed, and sensors to calculate a bump index in real time. It then dynamically adjusts the frequency of grabs based on these factors, allowing for more flexible adaptation to varying road conditions and detection requirements.

[0054] Real-time mileage calculation: Real-time mileage is calculated and detected through data such as encoder pulse number, wheel diameter and wheel circumference.

[0055] Dynamic coefficient adjustment: Dynamically adjust the grip coefficient through a nonlinear function based on vehicle speed (V) and road bump index (D).

[0056] Dynamic grab quantity formula: The dynamic grab quantity is calculated by combining real-time mileage and dynamic grab coefficient.

[0057] 1. Dynamic crawling algorithm:

[0058] Encoders and sensors calculate mileage, vehicle speed, and road bump index in real time to dynamically adjust the number of grabs. This, combined with a random grab mechanism, prevents artificial substitution of photo data at specific mileages, ensuring an unpredictable number of grabs. Dynamic coefficient adjustment considers the influence of vehicle speed and bump index, dynamically adjusting the grab coefficient using a nonlinear function.

[0059] (1) Real-time mileage calculation:

[0060]

[0061] Among them, L 里程 To detect real-time mileage difference

[0062] p t 、p t-1 is the number of pulses per unit time

[0063] D is the wheel diameter (mm)

[0064] πD is the wheel circumference (mm)

[0065] PPR is the number of pulses per revolution of the encoder

[0066] (2) Dynamic coefficient adjustment:

[0067] Dynamically adjust the number of grabs based on vehicle speed (v) and road bump index (u):

[0068] K d =K b ×f(v,u,…)

[0069] Among them, K d Dynamic grab coefficient

[0070] u is the bump index

[0071] K b : Basic coefficient (default value 0.8)

[0072] f(·): nonlinear function.

[0073] Among them, v0 is the vehicle speed reference value, which is used to standardize the actual vehicle speed, W is the road bumpiness index, W0 is the bumpiness index reference value, which is used to standardize the actual bumpiness index, and n and m are both exponential coefficients of the nonlinear function, which determine the degree of nonlinearity of the function with changes in vehicle speed and bumpiness.

[0074] (3) Dynamic capture quantity formula:

[0075] N 抓取 =L 里程 ×K d

[0076] Among them, N 抓取 :Dynamic crawl quantity

[0077] L 里程 :Detect real-time mileage

[0078] K d : Dynamic grab coefficient

[0079] 2. Hash processing and chain storage:

[0080] The captured original photos are hashed and the hash values ​​are stored in a chain for later data authenticity verification.

[0081] (1) Hash generation algorithm:

[0082] Generate photo hash value using SHA-256 algorithm:

[0083] H i =SHA256(P i ||T i ||L i )

[0084] Among them, P i : Binary data of the i-th photo

[0085] T i : Grab timestamp

[0086] L i : Real-time mileage difference

[0087] (2) Hash chain construction:

[0088] Concatenate the hash values ​​in chronological order to form a chain structure:

[0089] HashChain=H1→H2→…→H n

[0090] Each new hash value needs to be XORed with the previous hash value:

[0091]

[0092] 3. Data encryption storage:

[0093] (1) Use AES-256+RSA algorithm to generate encrypted packets for the regularly captured data;

[0094] (2) Use a cyclic overwriting method to retain only the latest encrypted package to save storage space.

[0095] 4. Dynamic crawling process:

[0096] (1) Read encoder and sensor data and calculate the real-time mileage L 里程 , vehicle speed (V) and road bump index (u);

[0097] (2) Generate the dynamic system K by vehicle speed and bump index d ;

[0098] (3) Trigger crawling at a fixed time and calculate the number of dynamic crawls;

[0099] (4) Randomly capture the original photo data generated in real time by the detection equipment based on the dynamic capture quantity;

[0100] (5) Write a unique hash value to the metadata of each captured original photo and update the hash chain synchronously;

[0101] (6) The captured photo data is encrypted and stored using the AES-256+RSA algorithm (the data in the encrypted package includes photo data and hash chain files).

[0102] (2) Authenticity Verification

[0103] Authenticity verification is achieved by comparing the hash values ​​of the original and captured photos to verify the consistency of the photo data. The photo data generated in real time by the detection device is encrypted using a hash chain. A unique hash value is generated by combining the encoder data and the AES-256 algorithm and embedded in the metadata of the original and captured photos, forming an irreversible chain structure.

[0104] 1. Authenticity Verification Algorithm

[0105] Check equation:

[0106] H original =H grbbed =H chain

[0107] Among them, H original : Original photo hash value

[0108] H grbbed : Get photo hash value

[0109] H chain : The hash value of the corresponding node in the hash chain

[0110] 2. Authenticity Verification Process

[0111] (1) Decrypt the captured data encryption package using the private key;

[0112] (2) Extract the metadata hash value H of the original photo original ;

[0113] (3) Extract the metadata hash value H of the captured photo grbbed ;

[0114] (4) Read the hash value H of the corresponding node from the hash chain chain .

[0115] (5) Perform hash check to verify equation H original =H grbbed =H chain Are they consistent? If they are consistent, the data is considered to be true, otherwise it is considered to be abnormal.

[0116] (6) Verification result output: If the verification is passed, the client program will automatically mark it as a normal road section, otherwise it will be marked as an abnormal road section.

[0117] like Figure 1 As shown, the authenticity verification method of rural road condition detection data based on dynamic encryption and decryption of key indicators of source data in this embodiment includes:

[0118] Dynamic crawling implementation steps:

[0119] S1. Initialization phase: After the inspection vehicle is started, the client software reads the wheel diameter and PPR parameters.

[0120] S2, real-time data acquisition: read encoder and sensor data every 0.5 seconds and perform calculations.

[0121] S3. Dynamic coefficient calculation: Calculate K according to the formula d value.

[0122] S4. Data capture and encryption: According to N 抓取 The value randomly selects photos and hashes them and stores them encrypted.

[0123] S5. Storage management: A circular overwriting strategy is adopted to retain only the most recently captured data encryption package.

[0124] Authenticity verification implementation steps:

[0125] S6. Data synchronization: After the detection is completed, the captured data (encrypted package) and the original detection data (encrypted) are reported together.

[0126] S7. Data decryption: Auditors or administrators decrypt captured encrypted package data through client software.

[0127] S8, Hash chain verification: By extracting the reported original photo, the captured photo and the hash chain file, the three are subjected to hash consistency verification, such as Figure 2 shown.

[0128] S9. Exception handling: If the hash verification fails, the route detection data will be automatically marked as abnormal.

[0129] The present application also provides an authenticity verification system for rural road condition detection, the system comprising:

[0130] The detection side device uses a unified hash chain to perform hash encryption operations on the original rural road condition image and the captured image captured from the original rural road condition image according to the capture rule, thereby obtaining an encrypted original image and an encrypted captured image; and

[0131] The verification side device performs consistency verification on the hash chain, the encrypted original image and the encrypted captured image to obtain the authenticity verification result of the original rural road condition detection.

[0132] An embodiment of the present application also provides an electronic device, comprising: a processor, and a memory coupled to the processor, wherein the memory is used to store a computer program; and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the method described in any one of the above embodiments.

[0133] The electronic device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The electronic device may include, but is not limited to, a processor and a memory.

[0134] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, connecting various parts of the entire device using various interfaces and lines.

[0135] The memory may be used to store the computer program, and the processor implements various functions of the electronic device by running or executing the computer program stored in the memory and calling the data stored in the memory.

[0136] The memory may primarily include a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application required for a function, and the like; and the data storage area may store data created based on the use of the mobile phone, and the like. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a flash memory card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0137] The embodiment of the present application also provides a storage medium, which is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0138] An embodiment of the present application further provides a computer program product, including: a computer program or instructions, which, when executed on a computer, causes the computer to execute any of the above-mentioned possible implementation methods.

[0139] The above is a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications are also considered to be within the scope of protection of the present application.

Claims

1. A method for verifying the authenticity of rural road conditions, characterized in that: The method comprises: On the detection side, a unified hash chain is used to perform hash encryption operations on the original rural road condition image and the captured image captured from the original rural road condition image according to the capture rules, thereby obtaining an encrypted original image and an encrypted captured image; On the verification side, a consistency check is performed on the hash chain, the encrypted original image and the encrypted captured image to obtain an authenticity check result of the original rural road condition detection.

2. The method according to claim 1, wherein: The crawling rules are: Determine the current number of crawls based on the mileage difference between the current time period and the previous time period; and The captured images corresponding to the current captured number are captured.

3. The method according to claim 2, wherein: The current crawl quantity is determined as follows: N 抓取 =L 里程 ×K d K d =K b ×f(v,u) Among them, N 抓取 is the current number of crawls, L 里程 is the mileage difference between the current time period and the previous time period, K d is the dynamic grasping coefficient, K b is the basic coefficient, v is the speed of the detection vehicle, u is the bump index of the detection vehicle, f is the nonlinear function, p t is the number of pulses in the current time period, p t-1 is the number of pulses in the previous time period, t is the current time period, t-1 is the previous time period, D is the wheel diameter, and PPR is the number of pulses per revolution of the encoder.

4. The method according to claim 3, wherein: The nonlinear function is Among them, v0 is the vehicle speed reference value, which is used to standardize the actual vehicle speed, W is the road bumpiness index, W0 is the bumpiness index reference value, which is used to standardize the actual bumpiness index, and n and m are both exponential coefficients of the nonlinear function, which determine the degree of nonlinearity of the function with changes in vehicle speed and bumpiness.

5. The method according to claim 3, wherein: The bump index is obtained by a sensor and is used to measure the bumpiness of the vehicle during operation. The vehicle is placed on the detection side.

6. The method according to claim 2, wherein: The hash value in the hash chain is determined by the binary data of the captured image, the capture timestamp and the mileage difference.

7. An authenticity verification system used in rural road condition detection, characterized in that: The system comprises: The detection side device uses a unified hash chain to perform hash encryption operations on the original rural road condition image and the captured image captured from the original rural road condition image according to the capture rule, thereby obtaining an encrypted original image and an encrypted captured image; and The verification side device performs consistency verification on the hash chain, the encrypted original image and the encrypted captured image to obtain the authenticity verification result of the original rural road condition detection.

8. An electronic device, characterized in that: The electronic device includes: a processor, and a memory coupled to the processor, The memory is used to store computer programs; and The processor is configured to execute the computer program stored in the memory, so that the electronic device executes the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a computer program or instructions. When the computer program or instructions are run on a computer, the computer is caused to perform the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product comprises: a computer program or instructions, and when the computer program or instructions are run on a computer, the computer is caused to perform the method according to any one of claims 1 to 6.

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