Visual safety brain modeling and early warning platform of highway toll collection system

Abstract

The invention belongs to the technical field of data safety, and particularly relates to a visual safety brain modeling and early warning platform of an expressway toll collection system, which comprises a data capturing module used for acquiring real-time interaction data and a toll station three-dimensional model of the expressway toll collection system, and constructing an expressway toll station panoramic three-dimensional model in a three-dimensional environment; the dynamic display module comprises a first floating information board, a second floating information board, a third floating information board, a fourth floating information board and a fifth floating information board; the early warning module is used for analyzing the real-time interaction data acquired by the data capturing module to find abnormal data and tracing an abnormal event; and the adjusting module provides a dynamic adjusting mechanism according to the matching result. According to the method, the distribution strategy is adjusted in real time to cope with changes of emergency situations and tasks, the empty window period occurring in the adjustment process is avoided as much as possible, and network security management vulnerabilities of the highway toll collection system can be prevented.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of data security, and particularly relates to a visual security brain modeling and early warning platform of a highway toll collection system. BACKGROUND

[0002] The highway toll collection system is an important infrastructure for guaranteeing the operation, maintenance and management of highways. The toll collection system realizes investment recovery, debt repayment and road maintenance by collecting tolls, however, it often needs to face security problems such as continuously upgraded network threats in the process of the Internet of Things.

[0003] In daily use, the network security of the highway toll collection system cannot be ignored. For example, according to the search, there is a network security monitoring method based on user analysis with a publication number CN116866024A. The login data and historical behavior data of the user are obtained. The user identity data and login behavior data are generated according to the login data, the first-level monitoring evaluation value is generated according to the user identity data, the login abnormal value is generated according to the login behavior data, and the second-level monitoring evaluation value is generated according to the login abnormal value. The historical evaluation value is generated according to the historical behavior data, the third-level monitoring evaluation value is generated according to the historical evaluation value, the monitoring parameter is set according to the third-level monitoring evaluation value, and it is judged whether there is an abnormal operation state of the user according to different monitoring evaluation values.

[0004] The highway toll collection system involves manual operation and networking operation of equipment. Although the toll collection system can discover abnormal operation through the monitoring evaluation value, when an abnormality occurs in a certain item in the manual operation or the networking operation of the equipment, it is difficult to adjust the distribution in time, so that a window period occurs in the adjustment process, which may cause a network security management vulnerability of the highway toll collection system. SUMMARY

[0005] The purpose of the present application is to provide a visual security brain modeling and early warning platform of a highway toll collection system, which can adjust the distribution strategy in real time to respond to emergency situations and changes in tasks, and avoid the window period that occurs in the adjustment process as much as possible, thereby preventing network security management vulnerabilities of the highway toll collection system.

[0006] The technical solutions adopted by the present application are as follows: The visual security brain modeling and early warning platform of the highway toll collection system comprises: A data grabbing module is used to obtain real-time interaction data of the highway toll collection system, and the real-time interaction data is used to monitor the running state of the highway toll collection system after data processing; A toll station three-dimensional model is used to construct a panoramic three-dimensional model of the highway toll station in a three-dimensional environment; The dynamic display module comprises a first floating information board, a second floating information board, a third floating information board, a fourth floating information board and a fifth floating information board for the three-dimensional model of the toll station. The early warning module analyzes the real-time interaction data obtained by the data grabbing module to find abnormal data for tracing abnormal events. The adjustment module obtains a set of tracing data according to the abnormal events H The set of tracing data H is matched with the real-time interaction data obtained by the data grabbing module, and a dynamic adjustment mechanism is given according to the matching result.

[0007] As an optional solution, the data grabbing module comprises: The first supervision unit is used to collect first administrator login authorization data a , second administrator login authorization data b and third administrator login authorization data c , and the order of the three in the management of the toll station is ; The second supervision unit is used to collect user data d , The user data d is used to protect the privacy of the user; The third supervision unit is used to collect infrastructure data e ; The fourth supervision unit is used to collect order data of each lane and each station-level toll system p , and the order data p represents the income status of the highway toll system.

[0008] As an optional solution, the user data includes vehicle pass records, user payment data, user identity data, and intelligent OBU device communication data.

[0009] As an optional solution, the infrastructure data e includes: Messages from the intelligent OBU device of the vehicle ; Electric barrier lifting instruction data ; Alarm instruction data of the emergency alarm subsystem .

[0010] As an optional solution, the order data p includes entry information of each lane passing vehicle and entry information of each station-level toll system passing vehicle .

[0011] As an optional solution, the toll station three-dimensional model comprises a virtual lane, an electric barrier model, and a toll booth model; Wherein, the virtual lane accesses the GPS data of the passing vehicles through the Fleet Management system, and the virtual lane represents the vehicle flow direction and density through particle flow; The electric barrier model is lifted at to keep the lane unblocked; Or the electric barrier model is lowered at to block the vehicles at the lane.

[0012] As an optional solution, the first floating information board is arranged on the front of each toll booth model to display the first administrator login authorization data a , the second administrator login authorization data b , the third administrator login authorization data c , or the ETC authorization data , forming a first floating data pool , which is updated in real time at to ensure the safety and credibility of the operation and maintenance services and data flow.

[0013] As an optional solution, the third floating information board is arranged on the electric barrier model to display the infrastructure data e , forming a second floating data pool , which is refreshed according to the frequency of the license plate number obtained through the camera-assisted vehicle type identification.

[0014] As an optional solution, the early warning module comprises: A data comparison unit compares the real-time interaction data generated at each lane at time n with the preset data, and if there is a difference, the data is marked as abnormal data on the fifth floating information board for display and tracing; A scoring unit sets the initial score of the lane per day as X =100, and deducts 1 point for each abnormal data, so that the evaluation score of the lane at time n is recorded as , and the evaluation score of the toll station is recorded as , and and are displayed in real time on the toll station three-dimensional model; The fifth floating information board with the deducted score is marked in red.

[0015] As an optional solution, the dynamic adjustment mechanism is as follows: If Then stop. Based on the permissions of the first administrator, the adjacent second administrator is scheduled to replace the first administrator on the same day; like Then stop. Based on the permissions of the second administrator, the adjacent third administrator is scheduled to replace the second administrator on the same day; like Then stop. Based on the permissions of the corresponding third administrator, schedule the adjacent third administrator to replace the current third administrator on the same day; like Then stop. Based on the ETC authorization permissions, the adjacent first, second, or third administrators are scheduled to be on duty at the ETC-authorized lane toll booth on the same day; like Then stop. Based on the permissions of the corresponding third administrator, schedule the adjacent third administrator to replace the current third administrator on the same day; like Then, the adjacent third-party administrator will call the data comparison unit to verify the daily entry information for each lane. and the accounting information of each station-level toll collection system And screen the corresponding first floating data pool. Second floating data pool Find the abnormal data and repeat the above operation.

[0016] The technical effects achieved by this invention are as follows: This invention constructs a visualized data platform to provide a quantifiable and scoreable cybersecurity risk assessment mechanism when an anomaly occurs in any aspect of manual operation or networked equipment operation. It can streamline the existing security management workflow of the highway network toll system to form a standardized management strategy, realize the standardization of tasks and dynamic adjustment mechanism, and adjust the allocation strategy in real time to deal with emergencies and changes in tasks, minimizing the window period that occurs during the adjustment process. This helps to prevent cybersecurity management vulnerabilities in the highway toll system and ensure the security and reliability of operation and maintenance services and data flow.

[0017] This invention combines a visualized 3D model of a toll station with a data pool to intuitively reflect the operational status of highway toll stations. Furthermore, by strengthening the data chain correlation between different real-time interactive data through the data pool, it enables the detection of abnormal data based on the data chain when a single data point is abnormal, facilitating timely dispatch and improving the quality and speed of network security management for highway toll systems.

[0018] The values ​​output by this invention after data processing can be stored in the database of highway toll stations and can be accessed or queried at any time through the computers at highway toll stations. Furthermore, the use of 3D visualization data platform technology to organize these values ​​helps to intuitively optimize the existing network security management process of the highway network toll system. By adopting classified, hierarchical, and time-based operations, the daily workflow is simplified and visualized, forming a standardized management strategy. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the highway toll collection system of the present invention; Figure 2 This is a system block diagram of the visualized safety brain modeling and early warning platform for the highway toll system of the present invention; Figure 3 This is a structural schematic diagram of the data capture module of the present invention. Detailed Implementation

[0020] To make the objectives and advantages of this invention clearer, the invention will be specifically described below with reference to embodiments. It should be understood that the following text is merely used to describe one or more specific embodiments of the invention and does not strictly limit the scope of protection specifically claimed by the invention.

[0021] The construction and operation of highway toll systems directly affect road operation quality and management efficiency. (See also...) Figure 1 Generally, a highway toll system consists of lane-level toll collection systems, station-level toll collection systems, central toll collection systems, and settlement center systems, as follows: Lane-level toll collection system: Satellite positioning subsystem, such as Beidou satellite positioning equipment; intelligent OBU (On-Board Unit) device, with built-in Beidou satellite positioning module and DSRC / C-V2X communication chip. This on-board terminal is linked to the payment account through ETC card or electronic license plate (RFID) to support contactless payment; RSU (Road Side Unit) device; or manual toll collection (MTC) subsystem; each lane can also be equipped with lidar, camera to assist in vehicle type recognition, and traffic light display equipment and electric barriers; Station-level toll collection system: consists of toll lanes, monitoring subsystem, internal wired intercom subsystem, emergency alarm subsystem, toll data management server, and image data management system; Centralized toll collection system: consists of station-level toll collection system, centralized toll collection business server, centralized monitoring system, and image management system; Settlement Center System: Composed of toll collection systems at each road segment level and toll collection business servers at the settlement center.

[0022] like Figures 1-3 As shown, the visualized security brain modeling and early warning platform for highway toll collection systems includes the following components: The data capture module is used to acquire real-time interactive data from the highway toll collection system. This data can be replaced with the neighborhood mean or median to filter and reduce noise. The processed output values ​​are convenient for monitoring the operational status of the highway toll collection system. See [link / reference]. Figure 2 and Figure 3 The data acquisition module includes a first monitoring unit, a second monitoring unit, a third monitoring unit, and a fourth monitoring unit, which are used for data collection at time n.

[0023] The first monitoring unit is used to collect login authorization data from the first administrator. a Second administrator login authorization data b And third-party administrator login authorization data c The order of authority for managing toll stations among the three entities is as follows: .

[0024] For example, the first administrator could be a junior employee at the toll station, capable of managing the manual toll collection work at their assigned toll booth; the second administrator could be a senior employee at the toll station, capable of managing all toll collection work at each lane; and the third administrator could be the station manager at the toll station, capable of managing all toll collection work at the toll station.

[0025] in, , , .

[0026] The second monitoring unit is used to collect user data. d , User data d This confirmation is used to protect user privacy.

[0027] In this embodiment, each lane of the highway toll system records user data, which includes vehicle passage records, user payment data, user identity data, and communication data of the smart OBU device.

[0028] For example, the monitoring subsystem captures license plate data of passing vehicles, compares the license plate data with the vehicle data pre-entered in the station-level toll system to obtain user identity data, and combines the location data of vehicles entering the highway in the central-level toll system and settlement center system, and associates the location data with the toll station to obtain the corresponding vehicle passage record.

[0029] The third regulatory unit is used to collect infrastructure data.e Infrastructure data e Communication information originates from the RSU device belonging to each lane and the communication information from the lower-level machine.

[0030] For example, RSU devices can use short-range communication based on the PC5 interface or long-range communication based on 4G / 5G to receive BSM (Broadcast Surveying Meter) messages from the vehicle's intelligent OBU device. It can directly obtain vehicle speed information reported by the vehicle, and the communication information of the lower-level machine includes electric barrier lifting command data. Alarm command data of the emergency alarm subsystem That is .

[0031] The fourth monitoring unit is used to collect order data for each lane and each toll station system. p Order data p This indicates the revenue status of the highway toll system.

[0032] The accounting information for each lane's passing vehicles is recorded as follows: Each toll station system records the accounting information for passing vehicles as follows: That is .

[0033] The values ​​output after data processing can be stored in the database of highway toll stations and can be accessed or queried at any time through the computers at the highway toll stations. However, these values ​​are just a string of numbers or characters, which are not intuitive to display. In addition, the volume of these values ​​is huge, and manual screening is time-consuming and laborious. Therefore, it is necessary to use 3D visualization data platform technology to sort out these values. This embodiment simplifies and visualizes the daily workflow by sorting out the existing network security management process of the highway network toll collection system and adopting classification, hierarchical and time-based operations to form a standardized management strategy.

[0034] A 3D model of the toll station is created by constructing a panoramic 3D model of the highway toll station in a 3D environment using software such as WebGL, Three.js, or Babylon.js. This 3D model defines... m Each virtual lane is connected to GPS data of passing vehicles through the FleetManagement system. Particle flow is used to represent the direction and density of traffic flow, while the particle flow effect is turned off for lanes that are not in use.

[0035] Furthermore, this embodiment configures a rotatable electric barrier model and a toll booth model for each virtual lane, which can be displayed on a configured computer screen. This computer can be deployed in toll booths, toll station duty rooms, central service halls, and settlement control centers.

[0036] Electric barrier model, in At that time, the preset program controls the electric barrier model to rise, keeping the lane clear; And in At that time, the preset program controls the electric barrier model to lower and block vehicles in the lane.

[0037] Toll booth model, in When the preset program controls the toll booth model to turn into a bright color, the bright color can be selected as, for example, green, yellow, or orange; And in At that time, the preset program controls the toll booth model to turn white or gray.

[0038] The dynamic display module includes a first floating information board, a second floating information board, a third floating information board, a fourth floating information board, and a fifth floating information board. The first, second, third, and fourth floating information boards are all used in the toll station's 3D model, and their data refresh cycle is set to [period missing]. The fifth floating information sign is displayed as a pop-up window outside the 3D model of the toll station.

[0039] The first floating information board, installed on the front of each toll booth model, is used to display the login authorization data of the first administrator. a Second administrator login authorization data b Third-party administrator login authorization data c or ETC authorization data This forms the first floating data pool. This first floating data pool is based on a zero-trust mechanism and blockchain technology, and... The system is updated in real time as a key means of building a security risk management system for the operation and maintenance services of the highway network toll collection system, ensuring the security and reliability of operation and maintenance services and data flow.

[0040] A second floating information board is installed in each virtual lane to display user data. d The second floating information board contains four floating windows, which respectively display vehicle passage records, user payment data, user identity data, and smart OBU device communication data.

[0041] The floating window used to display vehicle passage records is divided into two columns. The two columns of floating windows indicate the locations where passing vehicles entered and exited the highway and move with the particle flow area. The floating windows used to display user payment data, user identity data, and smart OBU device communication data are fixed in designated areas of the virtual lane.

[0042] The third floating information board, installed on the electric barrier model, is used to display infrastructure data. e This forms a second floating data pool. The second floating data pool is refreshed based on the frequency of license plate numbers obtained by camera-assisted vehicle model recognition, so that each passing vehicle has corresponding floating information.

[0043] The fourth floating information board, located at the top of the virtual lanes, displays order data for each lane and each toll station. p .

[0044] The accounting information for each lane is recorded as follows: Arranged vertically in chronological order K Okay, beyond K The data entry for each toll station is no longer displayed; instead, the billing information for each toll station is displayed separately at the top of the toll station's 3D model. .

[0045] The fifth floating information board is used to display abnormal data from the first, second, third, or fourth floating information boards in order to trace the source of abnormal events.

[0046] Cybersecurity operation and maintenance risk management of highway toll systems is generally fragmented, reflected in the separation of personnel management and infrastructure management. However, with the popularization and application of Internet of Things (IoT) technology, cyberattacks on infrastructure occur frequently, which may lead to security issues such as network vulnerabilities and loss of user data. Therefore, it is very important to detect abnormal cybersecurity events in a timely manner.

[0047] The early warning module, based on a zero-trust mechanism, analyzes real-time interaction data generated by passing vehicles in each lane to detect abnormal data for tracing the source of abnormal events. This early warning module includes a data comparison unit and a scoring unit, as detailed below: The data comparison unit compares any real-time interactive data generated at time n in each lane with other synchronous data and preset data. If there is a difference in the data, the data is marked as abnormal data and can be displayed on the fifth floating information board for easy tracing. Suppose that it is generated at time n. p＇ Then there should be synchronized data. and At this point, the data will be synchronized. With preset data Perform comparisons and synchronize data. With preset data The data is compared, and if a difference is found, the data is marked as abnormal. If the first floating data pool If any abnormal data is found, it is marked as an internal violation; Second floating data pool If any abnormal data is found, it will be marked as a network security vulnerability; like p If the data is abnormal, it will be marked as a business anomaly, such as a skipped payment or a malicious software attack. This embodiment uses a single real-time interactive data generated at time n to specifically screen the corresponding first floating data pool and second floating data pool, so as to promptly detect abnormal data in the form of a data chain and trace the source of the abnormal data. The scoring unit evaluates each lane using a 100-point scale, with an initial score set for each lane each day. X =100, and 1 point is deducted for each abnormal data point. Therefore, the lane's evaluation score at time n is denoted as: The corresponding evaluation score for the toll station is recorded as follows: ,Will and The information will be displayed in real time on the 3D model of the toll station. The fifth floating information board that has deducted points will be marked in red, while the fifth floating information board that has not deducted points will remain in its original color for easy differentiation.

[0048] The adjustment module, based on the real-time interactive data obtained by the data capture module and the abnormal events screened by the early warning module, obtains a source tracing data set. H , to trace the data set H The system matches the real-time interactive data obtained by the data capture module and provides a dynamic adjustment mechanism based on the matching results, as follows: like Then stop. Based on the permissions of the first administrator, the adjacent second administrator is scheduled to replace the first administrator on the same day; like Then stop. Based on the permissions of the second administrator, the adjacent third administrator is scheduled to replace the second administrator on the same day; like Then stop. Based on the permissions of the corresponding third administrator, schedule the adjacent third administrator to replace the current third administrator on the same day; like Then stop. Based on the ETC authorization permissions, the adjacent first, second, or third administrators are scheduled to be on duty at the ETC-authorized lane toll booth on the same day; like Then stop. Based on the permissions of the corresponding third administrator, schedule the adjacent third administrator to replace the current third administrator on the same day; like Then, the adjacent third-party administrator will call the data comparison unit to verify the daily entry information for each lane. and the accounting information of each station-level toll collection system And screen the corresponding first floating data pool. Second floating data pool Find the abnormal data and repeat the above operation.

[0049] In summary, this invention, by constructing a visualized data platform, provides a quantifiable and scoreable cybersecurity risk assessment mechanism when an anomaly occurs in any aspect of manual operation or networked equipment operation. This mechanism can streamline the existing security management workflow of the highway network toll collection system to form a standardized management strategy, realize the standardization and dynamic adjustment mechanism of tasks, and adjust the allocation strategy in real time to cope with emergencies and changes in tasks. It minimizes the window period that occurs during the adjustment process, which is conducive to preventing cybersecurity management vulnerabilities in the highway toll collection system and ensuring the security and reliability of operation and maintenance services and data flow.

[0050] The above description is merely an optional embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention, unless otherwise specified or limited, shall be implemented according to conventional means in the art.

Claims

1. A visualized security brain modeling and early warning platform for highway toll collection systems, characterized in that, include: The data capture module is used to acquire real-time interactive data from the highway toll collection system. After data processing, the real-time interactive data is used to monitor the operation status of the highway toll collection system. Toll station 3D model: A panoramic 3D model of a highway toll station is constructed in a 3D environment. The dynamic display module includes a first floating information board, a second floating information board, a third floating information board, a fourth floating information board, and a fifth floating information board for the three-dimensional model of the toll station; The early warning module analyzes the real-time interactive data acquired by the data capture module to detect abnormal data and trace the source of abnormal events. The adjustment module obtains a set of source tracing data based on abnormal events. H , to trace the data set H It matches the real-time interactive data obtained by the data capture module and provides a dynamic adjustment mechanism based on the matching results.

2. The visual security brain modeling and early warning platform according to claim 1, characterized in that: The data capture module includes: The first monitoring unit is used to collect login authorization data from the first administrator. a Second administrator login authorization data b And third-party administrator login authorization data c The order of authority for managing toll stations among the three entities is as follows: ; The second monitoring unit is used to collect user data. d , User data d The confirmation is used to protect user privacy; The third regulatory unit is used to collect infrastructure data. e ; The fourth monitoring unit is used to collect order data for each lane and each toll station system. p Order data p This indicates the revenue status of the highway toll system.

3. The visual security brain modeling and early warning platform according to claim 2, characterized in that: The user data includes vehicle passage records, user payment data, user identity data, and smart OBU device communication data.

4. The visual security brain modeling and early warning platform according to claim 2, characterized in that: The infrastructure data e include: Message from vehicle intelligent OBU device ; Electric barrier lifting command data ; Alarm command data of the emergency alarm subsystem .

5. The visual security brain modeling and early warning platform according to claim 2, characterized in that: The order data p Including the accounting information for vehicles passing through each lane. And the accounting information of vehicles passing through each station-level toll system .

6. The visual security brain modeling and early warning platform according to claim 4, characterized in that: The 3D model of the toll station includes a virtual lane, an electric barrier model, and a toll booth model. The virtual lanes are connected to GPS data of passing vehicles through the Fleet Management system, and the virtual lanes represent the direction and density of traffic flow through particle flow. The electric railing model is in It is raised periodically to keep the lane clear; Or the electric guardrail model in It is lowered at times and used to block vehicles in the lane.

7. The visual security brain modeling and early warning platform according to claim 6, characterized in that: The first floating information board is installed on the front of each toll booth model to display the login authorization data of the first administrator. a Second administrator login authorization data b Third-party administrator login authorization data c or ETC authorization data This forms the first floating data pool. The first floating data pool is The system is updated in real time to ensure the security and reliability of operation and maintenance services and data flow.

8. The visual security brain modeling and early warning platform according to claim 6, characterized in that: The third floating information board is installed on the electric barrier model and is used to display infrastructure data. e This forms a second floating data pool. The second floating data pool is refreshed based on the frequency of license plate numbers obtained by camera-assisted vehicle model recognition.

9. The visual security brain modeling and early warning platform according to claim 1, characterized in that: The early warning module includes: The data comparison unit compares the synchronous data of any real-time interactive data generated at time n in each lane with the preset data. If there is a difference in the data, the data is marked as abnormal data and displayed on the fifth floating information board for tracing. The scoring unit sets the initial score for each lane per day as follows: X =100, and 1 point is deducted for each abnormal data point. Therefore, the lane's evaluation score at time n is denoted as: The corresponding evaluation score for the toll station is recorded as follows: ,Will and Displayed in real-time on the 3D model of the toll station; The fifth floating information board that will appear when points are deducted will be marked in red.

10. The visual security brain modeling and early warning platform according to claim 1, characterized in that: The dynamic adjustment mechanism is as follows: like Then stop. Based on the permissions of the first administrator, the adjacent second administrator is scheduled to replace the first administrator on the same day; like Then stop. Based on the permissions of the second administrator, the adjacent third administrator is scheduled to replace the second administrator on the same day; like Then stop. Based on the permissions of the corresponding third administrator, schedule the adjacent third administrator to replace the current third administrator on the same day; like Then stop. Based on the ETC authorization permissions, the adjacent first, second, or third administrators are scheduled to be on duty at the ETC-authorized lane toll booth on the same day; like Then stop. Based on the permissions of the corresponding third administrator, schedule the adjacent third administrator to replace the current third administrator on the same day; like Then, the adjacent third-party administrator will call the data comparison unit to verify the daily entry information for each lane. and the accounting information of each station-level toll collection system And screen the corresponding first floating data pool. Second floating data pool Find the abnormal data and repeat the above operation.

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