A privacy protection-based internet of vehicles data forensics system and method

Abstract

The application discloses a kind of privacy protection-based Internet of Vehicles data forensics system and method, is through distribution pseudonym, and vehicle identity information and location information separate storage and upload, protect vehicle privacy, wherein roadside unit RSU uses random RSU inspection algorithm to the vehicle state information is inspected, ensure the reliability of data source, RSU is driven to the vehicle in jurisdiction using abnormal behavior monitoring algorithm, to reduce the redundancy problem of forensics data.The present application can solve the problems of vehicle privacy leakage, unreliable data source, forensics data redundancy and other problems in Internet of Vehicles data forensics at present stage.

Description

Technical Field

[0001] This invention relates to the field of automotive forensics, specifically a privacy-protected vehicle network data forensics system and method. Background Technology

[0002] The core issue in handling motor vehicle traffic accidents is determining the liability of each party, which relies on evidence collection by relevant law enforcement agencies. Traditional methods of evidence collection in motor vehicle traffic accidents are difficult, leading to challenges in determining liability. Digital evidence collection refers to gathering digital evidence for investigations following illegal acts. As a new form of evidence, digital evidence is bound to appear more and more frequently in judicial activities. Due to its diverse, flexible, and high-tech characteristics in terms of presentation and storage formats, digital evidence collection is suitable for widespread application in connected vehicle scenarios. In a connected vehicle environment, utilizing intelligent devices and sensors for digital evidence collection can easily obtain information such as the vehicle's current location, speed, and route, improving the accuracy and efficiency of evidence collection and aiding in the determination of liability and compensation for losses in cases of motor vehicle traffic accidents.

[0003] Vehicle-to-everything (V2X) data forensics faces a paradoxical challenge: first, it needs to collect as much data as possible from vehicles violating regulations to meet judicial evidence collection requirements; second, it must protect the privacy of innocent vehicles from leakage. Current V2X data forensics solutions either excessively pursue data volume at the expense of privacy, or overemphasize privacy protection, resulting in cumbersome processes for uploading, storing, and forwarding forensic data. Current V2X data forensics technologies primarily suffer from issues such as vehicle privacy leaks, unreliable data sources, and redundant forensic data. Summary of the Invention

[0004] The present invention addresses the shortcomings of the existing technology by proposing a privacy-preserving vehicle network data forensics system and method. This system aims to protect vehicle privacy while ensuring the validity of the forensic data, thereby solving problems such as vehicle privacy leakage, unreliable data sources, and redundant forensic data in current vehicle network data forensics.

[0005] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0006] The present invention provides a privacy-preserving method for obtaining evidence from vehicle network data. This method is applied to a network environment consisting of an ingress gate, an exit gate, roadside units (RSUs), and a cloud server (CLOUD), and is performed according to the following steps:

[0007] Step 1, at the nth entrance G of the highway n At the location, the entrance gate controls the i-th vehicle V entering the highway. i Distribute pseudonyms pi and the pseudonym p i Broadcast to the roadside unit (RSU) to declare that it has a pseudonymous identity p i Vehicle V i Enter the highway; simultaneously, the entrance GATE summarizes the nth entrance G n Information, vehicle V i true identity pseudonym p i Vehicle V i Entry Time The nth entry point G n identity information After packaging them together and encrypting them with the public key K, the ciphertext information is obtained. And uploaded to the cloud server CLOUD; where E is the encryption algorithm, It is the nth entry point G n The private key;

[0008] The cloud server CLOUD uses the private key K Pri For the ciphertext Decryption is performed to obtain the nth entry point G. n Recorded vehicle V i Plain text information of registration Where D is the decryption algorithm;

[0009] The cloud server CLOUD uses the nth entry point G n public key Verify identity information To determine whether the received uploaded information is valid, if valid, proceed to step 2; otherwise, reject the upload from the i-th vehicle V. i The information is displayed, and the process is exited; among them, G represents the nth entry point. n Use private key Digitally sign the information you upload;

[0010] Step 2, vehicles entering the highway V i p under a pseudonym i Real-time vehicle V data is uploaded to the Roadside Units (RSUs) within the jurisdiction. i In t j Status information at any time in, It is vehicle V i In t j Location information at any given time It is vehicle V i In t j Speed ​​information at any given moment It is vehicle V i In tj Acceleration information at any moment It is vehicle V i In t j Heading angle information at any given time It is vehicle V i In t j Angular acceleration information at any given moment;

[0011] Step 3: The cloud server CLOUD randomly selects 3 roadside units (RSUs) to check their status information. Random RSU checks are conducted to ensure that vehicle status information has not been tampered with;

[0012] Step 3.1: Randomly select 3 roadside units (RSUs) and denote them as RSUs. A RSU B RSU C Their positions are respectively denoted as Each receives status information The times are respectively Each distance from vehicle V i In t j The distance between the time and position is denoted as R. A R B R C ;

[0013] Step 3.2: Solve the system of equations shown in equation (1) to obtain the vehicle V. i In t j Location information at any time

[0014]

[0015] In equation (1), l represents vehicle V i The set of points along the highway route; ν represents the speed at which radio waves travel through the air;

[0016] Step 3.3, move vehicle V i In t j Location information at any time With vehicle V i In t j Location information uploaded in real time Perform a comparison, if and If they are not equal, then vehicle V is considered to be... i If the uploaded location information is abnormal, exit the process; otherwise, proceed to step 4.

[0017] Step 4, the roadside unit RSU receives in {t jWithin the time period |j=0,1,2,···,n}, there are m vehicles {V i The status information uploaded by |i=0,1,2,···,m} is statistically analyzed at t j The average speed of m vehicles within the jurisdiction at any given time Mean heading angle average acceleration Mean angular acceleration in, Indicates vehicle V i In t j The speed of the car at any given moment Indicates vehicle V i In t j The heading angle at any moment, Indicates vehicle V i In t j acceleration at any moment Indicates vehicle V i In t j Angular acceleration at time;

[0018] If it is found that the speed, heading angle, acceleration, or turning acceleration of any vehicle at a certain moment exceeds the average of all vehicles in the jurisdiction, and the extent of the excess reaches the set threshold, then the corresponding vehicle is considered to have abnormal driving behavior. The roadside unit (RSU) records and stores the status information uploaded by all vehicles in the jurisdiction for a period of time from the current moment, and uploads it to the cloud server CLOUD.

[0019] Step 5: When a traffic accident occurs and data evidence needs to be collected, retrieve the status information uploaded by the Roadside Unit (RSU) in the jurisdiction where the accident occurred within the corresponding time period from the cloud server CLOUD, and query the real identity of the vehicle based on the pseudonym of the perpetrator.

[0020] The characteristic of the vehicle network data forensics method described in this invention is that when a vehicle exits from a highway exit, the exit GATE node cancels the pseudonym information registered for the corresponding vehicle and broadcasts a statement to the roadside unit (RSU) and the entrance GATE declaring that the corresponding pseudonym identity has expired.

[0021] The present invention discloses a privacy-protected vehicle network data forensics system, comprising a memory and a processor, wherein the memory is used to store a program that supports the processor in executing the vehicle network data forensics method, and the processor is configured to execute the program stored in the memory.

[0022] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0023] 1. This invention utilizes data uploaded by vehicles or roadside units (RSUs) to recreate traffic accident scenes in the cloud using digital twin technology. This eliminates the need for image data during the evidence collection process, thereby reducing the leakage of sensitive vehicle information, including but not limited to license plate numbers and vehicle owner facial information identified from images.

[0024] 2. When a vehicle registers at the entrance, it obtains a temporary pseudonym. The GATE node uploads the vehicle's identity information, while the RSU node uploads the vehicle's location information. The identity information and location information are stored and uploaded separately, thereby reducing the risk of leakage of vehicle owner privacy.

[0025] 3. This invention improves the reliability of data sources through a random RSU verification algorithm. Since the verification occurs at random times, it will not occupy too much channel resources.

[0026] 4. This invention uses an abnormal driving behavior detection algorithm to ensure that the data stored in the Roadside Unit (RSU) is likely to be data before and after a traffic accident, thereby reducing the storage pressure on the RSU and reducing redundancy in evidence collection data. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the vehicle network data forensics system involved in the embodiments of the present invention;

[0028] Figure 2 This is a schematic diagram of the vehicle network data forensics process of the present invention;

[0029] Figure 3 This is a schematic diagram of the random RSU verification algorithm of the present invention;

[0030] Figure 4 This is a schematic diagram of the abnormal driving behavior monitoring of the present invention;

[0031] Figure 5 This is a schematic diagram of the vehicle status data of the present invention;

[0032] Figure 6 This is a schematic diagram illustrating the analysis of the responsible party in a traffic accident within the digital twin environment of this invention. Detailed Implementation

[0033] In this embodiment, a privacy-preserving method for obtaining evidence from vehicle network data is described, such as... Figure 1 The image shows an evidence collection system comprised of nodes such as vehicles, entrance gates, exit gates, roadside units (RSUs), and cloud servers (CLOUD). Figure 2 As shown, this method for obtaining evidence from vehicle network data includes:

[0034] Step 1, at the nth entrance G of the highway n At the entrance gate, the i-th vehicle V enters the highway.i Distribute pseudonyms p i and the pseudonym p i Broadcast to the roadside unit RSU to declare that p has a pseudonymous identity i Vehicle V i Enter the highway; simultaneously, the entrance gate summarizes the nth entrance G. n Information, vehicle V i true identity pseudonym p i Vehicle V i Entry Time The nth entry point G n identity information After packaging them together and encrypting them with the public key K, the ciphertext information is obtained. And uploaded to the cloud server CLOUD; where E is the encryption algorithm, It is the nth entry point G n The private key;

[0035] Cloud server CLOUD uses private key K Pri For ciphertext Decryption is performed to obtain the nth entry point G. n Recorded vehicle V i Plain text information of registration Where D is the decryption algorithm;

[0036] Cloud server CLOUD uses the nth entry point G n public key Verify identity information To determine whether the received uploaded information is valid, if valid, proceed to step 2; otherwise, reject the upload from the i-th vehicle V. i The information is displayed, and the process is exited; among them, G represents the nth entry point. n Use private key Digitally sign the information you upload;

[0037] It should be noted that the cloud server, as an absolutely trusted node, controls the entry point G. n The uploaded information uses database privacy protection technology to ensure that vehicle privacy is not leaked.

[0038] Step 2, vehicles entering the highway V i p under a pseudonym i Real-time vehicle V data is uploaded to the Roadside Units (RSUs) within the jurisdiction. i In t j Status information at any time in, It is vehicle V i In tj Location information at any given time It is vehicle V i In t j Speed ​​information at any given moment It is vehicle V i In t j Acceleration information at any moment It is vehicle V i In t j Heading angle information at any given time It is vehicle V i In t j Angular acceleration information at any given moment;

[0039] Step 3: The cloud server CLOUD randomly selects 3 roadside units (RSUs) to check their status information. Random RSU checks are conducted to ensure that vehicle status information has not been tampered with;

[0040] Step 3.1: Randomly select 3 roadside units (RSUs) and denote them as RSUs. A RSU B RSU C Their positions are respectively denoted as Each receives status information The times are respectively Each distance from vehicle V i In t j The distance between the time and position is denoted as R. A R B R C ;

[0041] Step 3.2: Solve the system of equations shown in equation (1) to obtain the vehicle V. i In t j Location information at any time

[0042]

[0043] In equation (1), l represents vehicle V i The set of points along the highway path; ν represents the speed at which radio waves travel through the air.

[0044] Step 3.3, move vehicle V i In t j Location information at any time With vehicle V i In t j Location information uploaded in real time Perform a comparison, if and If they are not equal, then vehicle V is considered to be...i If the uploaded location information is abnormal, exit the process; otherwise, proceed to step 4.

[0045] Specifically, according to such Figure 3 The method shown calculates the vehicle's position. The vehicle's position is at a distance from the RSU. A Distance R A On the circumference, At the same time, the vehicle was located at a distance from the RSU. B RSU C The radii are respectively R B R C On the circumference, among which ν is the propagation speed of the signal emitted by the vehicle. Using plane geometry, we can find the intersection of the three circles. If this intersection is on a highway, it represents the speed of the vehicle's signal, V. i In t j Location of inspection at all times

[0046] Specifically, RSUs that jointly verify vehicle location information A RSU B RSU C The timing of the joint inspection is random, and the timing of the joint inspection is also random, which can effectively prevent vehicles and multiple RSUs from colluding to upload tampered data.

[0047] It should be noted that, to reduce the channel resource consumption of the random RSU verification algorithm, this algorithm can be triggered at random times, instead of performing verification on every frame of data uploaded by the vehicle. Due to the randomness of the verification time, the vehicle cannot predict when it will verify the uploaded data; therefore, the vehicle must upload valid data at every moment to ensure that the verification passes.

[0048] Furthermore, RSU random checks can increase the frequency of checks on suspicious vehicles with abnormal uploaded location information, while reducing the frequency of checks on honest vehicles with normal uploaded location information.

[0049] It should be understood that there are many methods for calculating vehicle location. The method for calculating vehicle location in the above-mentioned random RSU verification algorithm is only one embodiment of the present invention and does not constitute a limitation of the present invention.

[0050] Although the randomized RSU verification algorithm only checks vehicle location information, it's understandable that after verifying the authenticity of the uploaded location information, the vehicle's trajectory can be calculated based on its real-time location. The derivative of displacement with respect to time in the trajectory represents the vehicle's velocity, the derivative of velocity with respect to time represents acceleration, the direction of the tangent vector of the trajectory represents the direction of the heading angle, and the derivative of the heading angle with respect to time represents angular acceleration. Therefore, other state information can be deduced from the vehicle's location information, allowing for the verification of other uploaded information to ensure that all uploaded information is tamper-proof.

[0051] The reason for requiring vehicles to upload status information including speed, acceleration, heading angle, and turning acceleration is to facilitate the monitoring of abnormal driving behavior in step 4.

[0052] Step 4, the roadside unit (RSU) receives data in {t} j Within the time period |j=0,1,2,···,n}, there are m vehicles {V i The status information uploaded by |i=0,1,2,···,m} is statistically analyzed at t j The average speed of m vehicles within the jurisdiction at any given time Mean heading angle average acceleration Mean angular acceleration in, Indicates vehicle V i In t j The speed of the car at any given moment Indicates vehicle V i In t j The heading angle at any moment, Indicates vehicle V i In t j acceleration at any moment Indicates vehicle V i In t j Angular acceleration at time;

[0053] If any vehicle is found to have a speed, heading angle, acceleration, or turning acceleration that exceeds the average of all vehicles in the jurisdiction at a certain moment, and the excess reaches the set threshold, then the corresponding vehicle is considered to have abnormal driving behavior. The Roadside Unit (RSU) records and stores the status information uploaded by all vehicles in the jurisdiction for a period of time from the current moment, and also uploads it to the cloud server CLOUD.

[0054] In a highway scenario, vehicles do not stop at traffic lights, and highway design standards also have requirements for the radius of curvature. Therefore, under normal circumstances, vehicles traveling on a highway will maintain similar speeds and heading angles. However, if a vehicle exceeds the speed limit, travels at an excessively low speed, or makes a sharp turn or changes lanes, the data representing vehicle status will deviate from the overall average.

[0055] This step allows the RSU to store and upload data only for the time period in which abnormal driving behavior occurred, instead of recording and storing data 24 / 7. Therefore, the data stored by the RSU is highly likely to be data from before and after the traffic accident, thus resolving the problem of redundant evidence data and improving the efficiency of the evidence collection process.

[0056] Figure 4 This is a set of vehicle heading angle monitoring data results. Vehicle No. 2 deviated from the mean heading angle at time = 0.2s, due to abnormal driving behavior such as a sharp turn and lane change. Therefore, the RSU recorded and stored the status information uploaded by all vehicles within a certain period and uploaded the data to a cloud server for later retrieval and analysis when needed for evidence collection.

[0057] After data is uploaded to the RSU, it is stored locally for a certain period of time. If there is no need for forensic investigation, the local data is deleted, and a copy of the data is kept in the cloud. The cloud periodically deletes old data as needed for storage.

[0058] Figure 5 It is a set of vehicle status data uploaded when abnormal driving behavior is detected according to the method of the present invention.

[0059] Step 5: When a traffic accident occurs and data evidence needs to be collected, retrieve the status information uploaded by the Roadside Unit (RSU) in the jurisdiction where the accident occurred within the corresponding time period from the cloud server CLOUD, and query the real identity of the vehicle based on the pseudonym of the perpetrator.

[0060] It is understandable that, such as Figure 6 As shown, the cloud server uses digital twin technology to realistically recreate the vehicle's driving scenario on the road based on the vehicle status data uploaded by the RSU, thus facilitating the identification of the responsible party in a traffic accident. Furthermore, the entire evidence collection process does not require access to image data, reducing the risk of vehicle privacy leaks.

[0061] Specifically, when a vehicle exits the highway, the exit GATE node cancels the vehicle's registered pseudonym information and broadcasts a statement to the RSU and GATE nodes declaring that the pseudonym identity is no longer valid. Since the pseudonym information of vehicles traveling on the highway at the same time is unique, and data uploaded with invalid pseudonyms is not recorded by the RSU, this prevents malicious attackers from forging pseudonyms and sending false information.

[0062] In this embodiment, a privacy-protected vehicle network data forensics system includes a memory and a processor. The memory is used to store programs that support the processor in executing the above-described methods, and the processor is configured to execute the programs stored in the memory.

Claims

1. A privacy-preserving method for obtaining forensic evidence from vehicle network data, characterized by: This is applied to a network environment consisting of an ingress gate, an egress gate, roadside units (RSUs), and a cloud server (CLOUD), and is performed according to the following steps: Step 1, at the nth entrance of the highway At the location, the entrance gate controls the i-th vehicle entering the highway. Distribute pseudonyms and the pseudonym identity Broadcast to the roadside unit (RSU) to declare a pseudonymous identity. vehicles Enter the highway; simultaneously, the entrance GATE summarizes the nth entrance. Information, vehicles true identity False identity ,vehicle Entry Time The nth entry point identity information Then package them together and use the public key After encryption, the ciphertext information is obtained. And uploaded to the cloud server CLOUD; where E is the encryption algorithm, It is the nth entry point. The private key; The cloud server CLOUD uses a private key. For the ciphertext Decryption is performed to obtain the nth entry point. Recorded vehicles Plain text information of registration Where D is the decryption algorithm; The cloud server CLOUD uses the nth entry point. public key Verify identity information The system determines whether the received uploaded information is valid. If valid, proceed to step 2; otherwise, reject the request from the i-th vehicle. The information is displayed, and the process is exited; among them, Indicates the nth entry point Use private key Digitally sign the information you upload; Step 2, vehicles entering the highway Using a pseudonym Real-time vehicle data is uploaded to the Roadside Units (RSUs) within the jurisdiction. exist Status information at any time ,in, It is a vehicle exist Location information at any given time It is a vehicle exist Speed ​​information at any given moment It is a vehicle exist Acceleration information at any moment It is a vehicle exist Heading angle information at any given time It is a vehicle exist Angular acceleration information at any given moment; Step 3: The cloud server CLOUD randomly selects 3 roadside units (RSUs) to check their status information. Random RSU checks are conducted to ensure that vehicle status information has not been tampered with; Step 3.1: Randomly select 3 roadside units (RSUs) and denote them as RSUs. A RSU B RSU C Their positions are respectively denoted as , , Each receives status information. The times are respectively , , Each distance from the vehicle exist The distance between the time and position is denoted as R. A R B R C ; Step 3.2: Solve the system of equations shown in equation (1) to obtain the vehicle... exist Location information at any time : (1) In equation (1), Representative vehicle The set of points along the highway route; Represents the speed at which radio waves travel through the air; Step 3.3, move the vehicle exist Location information at any time With vehicles exist Location information uploaded in real time Perform a comparison, if and If they are not equal, then the vehicle is considered to be... If the uploaded location information is abnormal, exit the process; otherwise, proceed to step 4. Step 4, the roadside unit (RSU) receives data from... Within a given time period, m vehicles within the jurisdiction Uploaded status information and statistics. The average speed of m vehicles within the jurisdiction at any given time Mean heading angle average acceleration Mean angular acceleration ;in, Indicates vehicle exist The speed of the car at any moment Indicates vehicle exist The heading angle at any moment, Indicates vehicle exist acceleration at any moment Indicates vehicle exist Angular acceleration at time; If it is found that the speed, heading angle, acceleration, or turning acceleration of any vehicle at a certain moment exceeds the average of all vehicles in the jurisdiction, and the extent of the excess reaches the set threshold, then the corresponding vehicle is considered to have abnormal driving behavior. The roadside unit (RSU) records and stores the status information uploaded by all vehicles in the jurisdiction for a period of time from the current moment, and uploads it to the cloud server CLOUD. Step 5: When a traffic accident occurs and data evidence needs to be collected, retrieve the status information uploaded by the Roadside Unit (RSU) in the jurisdiction where the accident occurred within the corresponding time period from the cloud server CLOUD, and query the real identity of the vehicle based on the pseudonym of the perpetrator.

2. The method for obtaining evidence from vehicle network data as described in claim 1, characterized in that, When a vehicle exits the highway, the exit GATE node cancels the pseudonym information registered for the corresponding vehicle and broadcasts a statement to the roadside unit (RSU) and the entrance GATE declaring that the corresponding pseudonym identity has expired.

3. A privacy-preserving vehicle network data forensics system, comprising a memory and a processor, characterized in that, The memory is used to store a program that supports the processor in executing the vehicle network data forensics method of claim 1, and the processor is configured to execute the program stored in the memory.

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