An ai security situation awareness protection system and method for outdoor display content of a highway

Abstract

This invention discloses an AI-powered security situation awareness and protection system and method for outdoor highway displays, belonging to the field of outdoor display security technology. By cataloging displays and traffic sign information, the system records the display status of tasks remotely controlled by staff in real time, forming dynamic display behavior clusters. Based on the urban highway network, the system classifies these dynamic display behavior clusters by identifying the locations of the displays along the highway. Through intrusion logs of the displays recorded by an AI cloud platform, the system analyzes the risk level of abnormal displays of different types of traffic sign information along traffic routes. It assesses the AI ​​security situation awareness capability on each traffic route, quantifies the protection level of the intrusion range of outdoor highway displays, and provides real-time early warnings. The system can perceive intrusion behavior of display devices in real time and characterize the protection level of the intrusion range of outdoor highway displays by analyzing the affected area of ​​display anomalies, thereby improving the security of outdoor displays.

Description

Technical Field

[0001] This invention relates to the field of outdoor display safety technology, specifically to an AI-based safety situation awareness and protection system and method for highway outdoor display content. Background Technology

[0002] Various highway display screens serve as important windows for disseminating traffic condition information and guidance, playing a vital role in highway traffic operations. Highway display screens utilize multiple display formats, including text, images, and numbers, to provide different types of traffic information, such as highway weather information, road construction information, highway closure information, major highway traffic incidents, highway operational status information, and suggested detour routes. This helps drivers adjust their driving behavior, thereby alleviating traffic congestion, reducing traffic accidents, and improving the capacity of the road network.

[0003] However, outdoor highway displays are also remotely controlled and displayed through various display devices. During the transmission of content to the broadcast control screen, improper operation, hacking attacks, or deliberate sabotage can lead to the dissemination of inappropriate information, causing serious social consequences. Current technologies primarily rely on network security measures and operational regulations to control the intrusion of displays. Network security mainly employs traditional technologies such as firewalls and data encryption. However, with the rapid evolution of network technology, new vulnerabilities are constantly being exploited by hackers, making it difficult to completely eliminate the potential risks of network intrusions using a single technology. Operational regulations rely on strict operational and maintenance management processes and the self-discipline of operators, such as comprehensive protection measures for public displays, including pre-screening, in-process control, and post-incident evidence collection, to ensure information security. However, the lack of effective technical means makes it difficult to accurately and quickly resolve repetitive and tedious screening work, inevitably leading to prolonged negligence and accidents. Summary of the Invention

[0004] The purpose of this invention is to provide an AI-based security situation awareness and protection system and method for outdoor highway display content, in order to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] An AI-powered security situation awareness and protection system for outdoor highway display content, comprising: a display information module, a sample classification module, an intrusion detection and processing module, and an early warning analysis module;

[0007] The information display module uses an AI cloud platform to archive display and traffic sign information, and records the display status of the display tasks remotely controlled by staff in real time, forming a dynamic display behavior cluster.

[0008] The sample classification module, based on the urban road network, classifies dynamic display behavior clusters by identifying the location of the display on the side of the road, and generates a display sample set.

[0009] The intrusion detection and processing module uses the intrusion logs of the displays recorded by the AI ​​cloud platform to lock the display sample set and analyze the degree of abnormal display risk of different types of traffic sign information on traffic routes; based on the degree of abnormal display risk, it assesses the AI ​​security situation awareness capability of each traffic route.

[0010] The early warning analysis module, based on AI security situation awareness capabilities, analyzes the protection level of the area where the highway outdoor display has been intruded upon, and issues real-time early warnings.

[0011] Furthermore, the information display module includes a filing unit and a dynamic behavior statistics unit;

[0012] The cataloging unit catalogs all the displays in use. These displays are located along the roadside and are used to display traffic information. Each display consists of at least two screens joined together. The traffic information is designed by staff, and the traffic information is categorized by type, denoted as TI. i Where i represents the type tag number;

[0013] The dynamic behavior statistics unit is used to establish dynamic display behavior clusters. The display behavior refers to display tasks remotely controlled by staff at the backend. The display task refers to controlling different displays to show the same traffic information, and the type of traffic information is tagged with TI. i This constitutes the dynamic display behavior cluster, denoted as D. r (TI i )={S e |e∈[1,E]}, where D r (TI i S represents the dynamic display behavior cluster formed when the r-th display task is executed. e This indicates the e-th display in the file, where E represents the total number of displays.

[0014] Furthermore, the method for generating the display sample set includes:

[0015] The city's road network is acquired and cataloged. Based on the monitor's position along the roadside, the road network is adaptively assembled. The assembly method is as follows:

[0016] Let the j-th traffic route be denoted as TR. j Based on dynamic display behavior cluster D r (TI i ), for traffic routes TR j The displays on the screen are classified to obtain display category clusters, denoted as... and And constitutes the traffic route TR j The displayed sample set is denoted as Where I represents the maximum value of the type tag number.

[0017] Furthermore, the intrusion detection processing module includes an intrusion log unit, a risk assessment unit, and a perception analysis unit;

[0018] The intrusion log unit records the intrusion log of each display in real time through the AI ​​cloud platform. The intrusion refers to the display failing to display content according to the traffic instructions designed by the staff during the execution of the display task. The intrusion log records the type of traffic instructions designed by the staff for display on the display, and the traffic route where the display is located.

[0019] The risk assessment unit, based on the intrusion logs, identifies the display sample set by analyzing the traffic routes along the display's location. If the display... Then lock the display sample set K(TR) j );

[0020] Based on locking behavior, the risk level of abnormal display of different types of traffic signage information on traffic routes is analyzed and calculated, using the following formula:

[0021] In the formula, DS(i|TR) j The type of traffic instruction information is indicated by the TI tag. i On the traffic route TR j The anomaly display indicates the level of risk. IF[·] represents a counting function; if... If it is an empty set, then let like If it is not an empty set, then Indicates displaying the classification clusters The number of displays included;

[0022] The perception and analysis unit assesses and calculates the traffic route TR based on the level of risk indicated by anomalies. j The AI-powered security situation awareness capability is expressed by the following formula:

[0023] In the formula, SC(TR) j ) indicates the traffic route TR j The AI ​​security situation awareness capability on the platform, where μ represents the average level of anomaly risk display, and σ 2 The variance represents the degree of risk associated with anomalies, and NUM[K(TR j )] indicates that the sample set K(TR) is displayed. j The total number of display clusters included in )

[0024] According to the above method, the underlying big data quantified in this invention is traffic instruction information. Since there are many types of traffic instruction information and the purposes of each display are different, it is difficult to capture the overall security situation of outdoor displays. Correcting the display content of a single display based solely on its abnormal display behavior is time-consuming and laborious. Furthermore, it is not conducive to characterizing and analyzing the attacker's attack scope and objectives, nor to taking effective early warning measures to promptly remedy the intrusion risk. This invention uses the route conditions of the traffic network to coordinate the abnormal display situations of each display, thereby assessing the degree of abnormal display risk of different types of traffic instruction information on traffic routes. Therefore, the AI ​​security situation awareness capability on each traffic route is assessed based on the degree of abnormal display risk. The more displays with abnormal displays on different traffic routes, the greater the degree of abnormal display risk, and the stronger the AI ​​security situation awareness capability.

[0025] Furthermore, the early warning analysis module includes an intrusion range analysis unit and an early warning prompt unit;

[0026] The intrusion range analysis unit, based on AI security situation awareness capabilities, analyzes and calculates the protection level of the intrusion range of the highway outdoor display, using the following formula:

[0027] In the formula, RS represents the protection level of the area where the highway outdoor display is intruded upon, max{·} represents the maximum value sign, J represents the total number of traffic routes, and P is the preset protection safety factor;

[0028] The early warning unit is used to preset a protection early warning threshold. If the range protection level is greater than or equal to the protection early warning threshold, an early warning will be sent to the staff port.

[0029] According to the above method, AI security situation awareness capability is a probabilistic assessment value. The stronger the AI ​​security situation awareness capability, the greater the probability of highway outdoor displays being intruded, the greater the protection of the scope of highway outdoor displays being intruded, and the higher the overall security risk of highway outdoor displays being intruded.

[0030] An AI-based security situation awareness and protection method for outdoor highway display content, comprising the following steps:

[0031] Step S1: The AI ​​cloud platform archives the display and traffic sign information respectively, and records the display status of the display tasks remotely controlled by the staff in real time, forming a dynamic display behavior cluster;

[0032] Step S2: Based on the urban road network, the dynamic display behavior clusters are classified by identifying the location of the displays on the side of the road, and a display sample set is generated;

[0033] Step S3: By using the intrusion logs of the displays recorded by the AI ​​cloud platform, lock the display sample set and analyze the degree of risk of abnormal display of different types of traffic sign information on traffic routes; based on the degree of risk of abnormal display, assess the AI ​​security situation awareness capability on each traffic route.

[0034] Step S4: Based on AI security situation awareness capabilities, analyze the protection level of the intrusion range of highway outdoor displays and issue real-time warnings.

[0035] Furthermore, the specific implementation process of step S1 includes:

[0036] All displays in use are cataloged. These displays are located along the roadside and are used to display traffic information. Each display consists of at least two screens joined together. The traffic information is designed by staff, and is categorized by type, denoted as TI. i Where i represents the type tag number;

[0037] Establish a dynamic display behavior cluster, where the display behavior refers to a display task remotely controlled by the staff in the backend, and the display task refers to controlling different displays to display the same traffic instruction information, with TI tagged based on the type of traffic instruction information. i This constitutes the dynamic display behavior cluster, denoted as D. r (TI i )={S e |e∈[1,E]}, where D r (TI i S represents the dynamic display behavior cluster formed when the r-th display task is executed. e This indicates the e-th display in the file, where E represents the total number of displays.

[0038] Furthermore, the specific implementation process of step S2 includes:

[0039] The city's road network is acquired and cataloged. Based on the monitor's position along the roadside, the road network is adaptively assembled. The assembly method is as follows:

[0040] Let the j-th traffic route be denoted as TR. j Based on dynamic display behavior cluster D r (TI i ), for traffic routes TR j The displays on the screen are classified to obtain display category clusters, denoted as... and And constitutes the traffic route TR j The displayed sample set is denoted as Where I represents the maximum value of the type tag number.

[0041] Furthermore, the specific implementation process of step S3 includes:

[0042] Establish an AI-based security situation awareness model:

[0043] The AI ​​cloud platform records the intrusion log of each display in real time. The intrusion refers to the display failing to display content according to the traffic instructions designed by the staff during the execution of the display task. The intrusion log records the type of traffic instructions designed by the staff for display on the display, and the traffic route where the display is located.

[0044] Based on the intrusion logs, the display sample set is located by tracking the traffic routes along the monitor's location. If the monitor... Then lock the display sample set K(TR) j );

[0045] Based on locking behavior, the risk level of abnormal display of different types of traffic signage information on traffic routes is analyzed and calculated, using the following formula:

[0046] In the formula, DS(i|TR) j The type of traffic instruction information is indicated by the TI tag. i On the traffic route TR j The anomaly display indicates the level of risk. IF[·] represents a counting function; if... If it is an empty set, then let like If it is not an empty set, then Indicates displaying the classification clusters The number of displays included;

[0047] Based on the level of risk indicated by anomalies, assess and calculate the traffic route TR. j The AI-powered security situation awareness capability is expressed by the following formula:

[0048] In the formula, SC(TR) j ) indicates the traffic route TR j The AI ​​security situation awareness capability on the platform, where μ represents the average level of anomaly risk display, and σ 2 The variance represents the degree of risk associated with anomalies, and NUM[K(TR j )] indicates that the sample set K(TR) is displayed. j The total number of display clusters included in ).

[0049] Furthermore, the specific implementation process of step S4 includes:

[0050] Based on AI-powered security situation awareness capabilities, the protection level of outdoor highway displays under intrusion is analyzed and calculated using the following formula:

[0051] In the formula, RS represents the protection level of the area where the highway outdoor display is intruded upon, max{·} represents the maximum value sign, J represents the total number of traffic routes, and P is the preset protection safety factor;

[0052] A preset protection warning threshold is set. If the range protection level is greater than or equal to the protection warning threshold, a warning message will be sent to the staff port.

[0053] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: The AI ​​security situation awareness and protection system and method for highway outdoor display content provided by this invention records the display status of remotely controlled display tasks by staff in real time through filed displays and traffic sign information, forming dynamic display behavior clusters; based on the urban road network, the dynamic display behavior clusters are classified by identifying the location of the displays on the roadside; the abnormal display risk level of different types of traffic sign information on traffic routes is analyzed through the intrusion logs of the displays recorded by the AI ​​cloud platform; the AI ​​security situation awareness capability on each traffic route is assessed, the protection level of the intrusion range of highway outdoor displays is quantified, and real-time early warning is provided; while simultaneously sensing the intrusion behavior of display devices in real time, the protection level of the intrusion range of highway outdoor displays is characterized and analyzed by the affected range of display anomalies, thereby improving the security of outdoor displays. Attached Figure Description

[0054] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0055] Figure 1This is a schematic diagram of the structure of an AI-based safety situation awareness and protection system for outdoor highway display content according to the present invention;

[0056] Figure 2 This is a schematic diagram illustrating the steps of an AI-based security situation awareness and protection method for outdoor display content on highways, as described in this invention. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] Please see Figure 1 In this first embodiment: an AI security situation awareness and protection system for highway outdoor display content is provided. The system includes: a display information module, a sample classification module, an intrusion detection and processing module, and an early warning analysis module.

[0059] The information display module uses an AI cloud platform to archive display and traffic sign information, and records the display status of remotely controlled display tasks by staff in real time, forming a dynamic display behavior cluster.

[0060] Prioritize the display of information modules, which include a filing unit and a dynamic behavior statistics unit;

[0061] The documentation unit documents all displays in use. These displays are located along the roadside and are used to display traffic information. Each display consists of at least two screens joined together. The traffic information is designed by staff, and the information is categorized based on its type, denoted as TI. i Where i represents the type tag number;

[0062] The dynamic behavior statistics unit is used to establish dynamic display behavior clusters. Display behavior refers to display tasks remotely controlled by staff at the back end. Display tasks refer to controlling different displays to show the same traffic instruction information. TI is tagged based on the type of traffic instruction information. i This constitutes a dynamic display behavior cluster, denoted as D. r (TI i )={S e |e∈[1,E]}, where D r (TI i S represents the dynamic display behavior cluster formed when the r-th display task is executed. e This indicates the e-th display in the file, where E represents the total number of displays;

[0063] The sample classification module, based on the city's road network, classifies dynamic display behavior clusters by identifying the location of the displays along the roadside, and generates a display sample set.

[0064] Preferred methods for generating the sample set include:

[0065] Obtain and catalog the city's road network. Based on the monitor's position along the road, adaptively assemble the road network as follows:

[0066] Let the j-th traffic route be denoted as TR. j Based on dynamic display behavior cluster D r (TI i ), for traffic routes TR j The displays on the screen are classified to obtain display category clusters, denoted as... and And constitutes the traffic route TR j The displayed sample set is denoted as Where I represents the maximum value of the type marker number;

[0067] The intrusion detection and processing module uses the intrusion logs of the displays recorded by the AI ​​cloud platform to lock the display sample set and analyze the degree of risk of abnormal display of different types of traffic sign information on traffic routes; based on the degree of risk of abnormal display, it assesses the AI ​​security situation awareness capability of each traffic route.

[0068] Priority is given to the intrusion detection and processing module, which includes an intrusion log unit, a risk assessment unit, and a perception and analysis unit.

[0069] The intrusion log unit records the intrusion log of each display in real time through the AI ​​cloud platform. Intrusion refers to the display failing to display content according to the traffic instructions designed by the staff during the execution of the display task. The intrusion log records the type of traffic instructions designed by the staff for display on the display, and the traffic route where the display is located.

[0070] The risk assessment unit, based on the intrusion logs, identifies the display sample set by analyzing the traffic routes along the display's location. If the display... Then lock the display sample set K(TR) j );

[0071] Based on locking behavior, the risk level of abnormal display of different types of traffic signage information on traffic routes is analyzed and calculated, using the following formula:

[0072] In the formula, DS(i|TR) jThe type of traffic instruction information is indicated by the TI tag. i On the traffic route TR j The anomaly display indicates the level of risk. IF[·] represents a counting function; if... If it is an empty set, then let like If it is not an empty set, then Indicates displaying the classification clusters The number of displays included;

[0073] The perception and analysis unit assesses and calculates the traffic route TR based on the level of risk indicated by anomalies. j The AI-powered security situation awareness capability is expressed by the following formula:

[0074] In the formula, SC(TR) j ) indicates the traffic route TR j The AI ​​security situation awareness capability on the platform, where μ represents the average level of anomaly risk display, and σ 2 The variance represents the degree of risk associated with anomalies, and

[0075] The early warning and analysis module, based on AI security situation awareness capabilities, analyzes the protection level of the area where highway outdoor displays have been intruded upon and provides real-time early warnings.

[0076] Priority is given to the early warning analysis module, which includes an intrusion range analysis unit and an early warning prompt unit.

[0077] The intrusion range analysis unit, based on AI security situation awareness capabilities, analyzes and calculates the protection level of the intrusion range of highway outdoor displays, using the following formula:

[0078] In the formula, RS represents the protection level of the area where the highway outdoor display is intruded upon, max{·} represents the maximum value sign, J represents the total number of traffic routes, and P is the preset protection safety factor;

[0079] For example, P can be set as needed; generally, the AI ​​security situation awareness capability can be set to 0.5.

[0080] The early warning unit is used to preset the protection early warning threshold. If the range protection level is greater than or equal to the protection early warning threshold, an early warning will be issued to the staff port.

[0081] Please see Figure 2 In this second embodiment: an AI-based security situation awareness and protection method for outdoor highway display content is provided, which includes the following steps:

[0082] Step S1: The AI ​​cloud platform archives the display and traffic sign information respectively, and records the display status of the display tasks remotely controlled by the staff in real time, forming a dynamic display behavior cluster;

[0083] For example, all displays in use are cataloged. These displays are located along the roadside and used to display traffic information. Each display consists of at least two screens joined together. The traffic information is designed by staff, and is categorized based on its type, denoted as TI. i Where i represents the type tag number;

[0084] Establish a dynamic display behavior cluster. Display behavior refers to the display task remotely controlled by the staff in the backend. Display task refers to controlling different displays to display the same traffic instruction information. TI is tagged based on the type of traffic instruction information. i This constitutes a dynamic display behavior cluster, denoted as Dr(TI). i )={S e |e∈[1,E]}, where Dr(TI i S represents the dynamic display behavior cluster formed when the r-th display task is executed. e This indicates the e-th display in the file, where E represents the total number of displays;

[0085] Step S2: Based on the urban road network, the dynamic display behavior clusters are classified by identifying the location of the displays on the side of the road, and a display sample set is generated;

[0086] For example, the city's road network is acquired and cataloged. Based on the display's position on the roadside, the road network is adaptively assembled as follows:

[0087] Let the j-th traffic route be denoted as TR. j Based on dynamic display behavior cluster D r (TI i ), for traffic routes TR j The displays on the screen are classified to obtain display category clusters, denoted as... and And constitutes the traffic route TR j The displayed sample set is denoted as Where I represents the maximum value of the type marker number;

[0088] Step S3: By using the intrusion logs of the displays recorded by the AI ​​cloud platform, lock the display sample set and analyze the degree of risk of abnormal display of different types of traffic sign information on traffic routes; based on the degree of risk of abnormal display, assess the AI ​​security situation awareness capability on each traffic route.

[0089] For example, establish an AI security situation awareness model:

[0090] The AI ​​cloud platform records the intrusion logs of each monitor in real time. An intrusion occurs when a monitor fails to display content according to the traffic instructions designed by the staff during the execution of a display task. The intrusion log records the type of traffic instructions designed by the staff for displaying on the monitor, as well as the traffic route where the monitor is located.

[0091] Based on the intrusion logs, the display sample set is located by tracking the traffic routes along the monitor's location. If the monitor... Then lock the display sample set K(TR) j );

[0092] Based on locking behavior, the risk level of abnormal display of different types of traffic signage information on traffic routes is analyzed and calculated, using the following formula:

[0093] In the formula, DS(i|TR) j The type of traffic instruction information is indicated by the TI tag. i On the traffic route TR j The anomaly display indicates the level of risk. IF[·] represents a counting function; if... If it is an empty set, then let like If it is not an empty set, then Indicates displaying the classification clusters The number of displays included;

[0094] Based on the level of risk indicated by anomalies, assess and calculate the traffic route TR. j The AI-powered security situation awareness capability is expressed by the following formula:

[0095] In the formula, SC(TR) j ) indicates the traffic route TR j The AI ​​security situation awareness capability on the platform, where μ represents the average level of anomaly risk display, and σ 2 The variance represents the degree of risk associated with anomalies, and

[0096] Step S4: Based on AI security situation awareness capabilities, analyze the protection level of the area where the highway outdoor display has been intruded and issue real-time warnings;

[0097] For example, based on AI security situational awareness capabilities, the protection level of the range of intrusion into highway outdoor displays is analyzed and calculated using the following formula:

[0098] In the formula, RS represents the protection level of the area where the highway outdoor display is intruded upon, max{·} represents the maximum value sign, J represents the total number of traffic routes, and P is the preset protection safety factor;

[0099] A preset protection warning threshold is set. If the range protection level is greater than or equal to the protection warning threshold, a warning message will be sent to the staff port.

[0100] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0101] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for AI-based security situation awareness and protection of outdoor display content on highways, characterized in that, The method includes the following steps: Step S1: The AI ​​cloud platform archives the display and traffic sign information respectively, and records the display status of the display tasks remotely controlled by the staff in real time, forming a dynamic display behavior cluster; Step S2: Based on the urban road network, the dynamic display behavior clusters are classified by identifying the location of the displays on the side of the road, and a display sample set is generated; Step S3: By using the intrusion logs of the displays recorded by the AI ​​cloud platform, lock the display sample set and analyze the degree of risk of abnormal display of different types of traffic sign information on traffic routes; based on the degree of risk of abnormal display, assess the AI ​​security situation awareness capability on each traffic route. Step S4: Based on AI security situation awareness capabilities, analyze the protection level of the area where the highway outdoor display has been intruded and issue real-time warnings; The specific implementation process of step S1 includes: All displays in use are cataloged. These displays are located along the roadside and are used to display traffic information. Each display consists of at least two screens joined together. The traffic information is designed by staff, and is categorized based on its type, denoted as follows: Where i represents the type tag number; Establish a dynamic display behavior cluster, where each display behavior refers to a display task remotely controlled by staff in the backend. Each display task refers to controlling different displays to show the same traffic information, based on the type of traffic information. This constitutes the dynamic display behavior cluster, denoted as... ,in, This represents the dynamic display behavior cluster formed when the r-th display task is executed. This indicates the e-th display in the file, where E represents the total number of displays; The specific implementation process of step S2 includes: The city's road network is acquired and cataloged. Based on the monitor's position along the road, the road network is adaptively assembled. The assembly method is as follows: Let the j-th traffic route be denoted as Based on dynamic display behavior clusters Regarding transportation routes The displays on the screen are classified to obtain display category clusters, denoted as... ,and and constitute transportation routes The displayed sample set is denoted as , where I represents the maximum value of the type marker number; The specific implementation process of step S3 includes: Establish an AI-based security situation awareness model: The AI ​​cloud platform records the intrusion log of each display in real time. The intrusion refers to the display failing to display content according to the traffic instructions designed by the staff during the execution of the display task. The intrusion log records the type of traffic instructions designed by the staff for display on the display, and the traffic route where the display is located. Based on the intrusion logs, the display sample set is located by tracking the traffic routes along the monitor's location. If the monitor... Then lock the display sample set. ; Based on locking behavior, the risk level of abnormal display of different types of traffic signage information on traffic routes is analyzed and calculated, using the following formula: In the formula, Type marker indicating traffic instruction information In transportation routes The anomaly displayed indicates the level of risk. Represents a counting function, if If it is an empty set, then let ,like If it is not an empty set, then Indicates displaying the classification clusters The number of displays included; Based on the level of risk indicated by anomalies, assess and calculate traffic routes. The AI-powered security situation awareness capability is expressed by the following formula: In the formula, Indicates transportation routes AI-powered security situation awareness capabilities This represents the average level of risk indicated by anomalies, and , The variance represents the degree of risk associated with anomalies, and , Indicates displaying the sample set The total number of display clusters included.

2. The AI-based security situation awareness and protection method for outdoor highway display content according to claim 1, characterized in that, The specific implementation process of step S4 includes: Based on AI-powered security situation awareness capabilities, the protection level of outdoor highway displays under intrusion is analyzed and calculated using the following formula: In the formula, This indicates the extent of intrusion protection displayed on the outdoor highway. The maximum value is indicated by the symbol J, which represents the total number of traffic routes, and P is the preset safety factor. A preset protection warning threshold is set. If the range protection level is greater than or equal to the protection warning threshold, a warning message will be sent to the staff port.

3. An AI-based security situation awareness and protection system for outdoor highway display content, characterized in that, The system includes: an information display module, a sample classification module, an intrusion detection and processing module, and an early warning analysis module; The information display module uses an AI cloud platform to archive display and traffic sign information, and records the display status of the display tasks remotely controlled by staff in real time, forming a dynamic display behavior cluster. The sample classification module, based on the urban road network, classifies dynamic display behavior clusters by identifying the location of the display on the side of the road, and generates a display sample set. The intrusion detection and processing module uses the intrusion logs of the displays recorded by the AI ​​cloud platform to lock the display sample set and analyze the degree of abnormal display risk of different types of traffic sign information on traffic routes; based on the degree of abnormal display risk, it assesses the AI ​​security situation awareness capability of each traffic route. The early warning analysis module, based on AI security situation awareness capabilities, analyzes the protection level of the area where the highway outdoor display has been intruded and provides real-time early warnings. The information display module includes a filing unit and a dynamic behavior statistics unit; The filing unit files all the displays in use. These displays are located along the roadside and are used to display traffic information. Each display consists of at least two screens joined together. The traffic information is designed by staff, and the information is categorized based on its type, denoted as follows: Where i represents the type tag number; The dynamic behavior statistics unit is used to establish dynamic display behavior clusters. The display behavior refers to display tasks remotely controlled by staff at the backend. The display task refers to controlling different displays to show the same traffic information, based on the type of traffic information. This constitutes the dynamic display behavior cluster, denoted as... ,in, This represents the dynamic display behavior cluster formed when the r-th display task is executed. This indicates the e-th display in the file, where E represents the total number of displays; The methods for generating the display sample set include: The city's road network is acquired and cataloged. Based on the monitor's position along the road, the road network is adaptively assembled. The assembly method is as follows: Let the j-th traffic route be denoted as Based on dynamic display behavior clusters Regarding transportation routes The displays on the screen are classified to obtain display category clusters, denoted as... ,and and constitute transportation routes The displayed sample set is denoted as , where I represents the maximum value of the type marker number; The intrusion detection and processing module includes an intrusion log unit, a risk assessment unit, and a perception and analysis unit. The intrusion log unit records the intrusion log of each display in real time through the AI ​​cloud platform. The intrusion refers to the display failing to display content according to the traffic instructions designed by the staff during the execution of the display task. The intrusion log records the type of traffic instructions designed by the staff for display on the display, and the traffic route where the display is located. The risk assessment unit, based on the intrusion logs, identifies the display sample set by analyzing the traffic routes along the display's location. If the display... Then lock the display sample set. ; Based on locking behavior, the risk level of abnormal display of different types of traffic signage information on traffic routes is analyzed and calculated, using the following formula: In the formula, Type marker indicating traffic instruction information In transportation routes The anomaly displayed indicates the level of risk. Represents a counting function, if If it is an empty set, then let ,like If it is not an empty set, then Indicates displaying the classification clusters The number of displays included; The perception and analysis unit assesses and calculates traffic routes based on the level of risk indicated by anomalies. The AI-powered security situation awareness capability is expressed by the following formula: In the formula, Indicates transportation routes AI-powered security situation awareness capabilities This represents the average level of risk indicated by anomalies, and , The variance represents the degree of risk associated with anomalies, and , Indicates displaying the sample set The total number of display clusters included.

4. The AI-based security situation awareness and protection system for outdoor highway display content according to claim 3, characterized in that: The early warning analysis module includes an intrusion range analysis unit and an early warning prompt unit; The intrusion range analysis unit, based on AI security situation awareness capabilities, analyzes and calculates the protection level of the intrusion range of the highway outdoor display, using the following formula: In the formula, This indicates the extent of intrusion protection displayed on the outdoor highway. The maximum value is indicated by the symbol J, which represents the total number of traffic routes, and P is the preset safety factor. The early warning unit is used to preset a protection early warning threshold. If the range protection level is greater than or equal to the protection early warning threshold, an early warning notification is sent to the staff port.

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