Park asset information security management system based on artificial intelligence

Abstract

The invention belongs to the technical field of park asset information management, and particularly relates to an artificial intelligence-based park asset information safety management system, which comprises a park management platform and a park operation end, and is characterized in that the park management platform comprises an asset information base, an information safety monitoring module, an intelligent early warning module, a safety protection module and a management decision module; through comprehensive monitoring, early warning, protection and management of the park asset information, the safety and management efficiency of the park asset information are improved, powerful technical support is provided for intelligent development of the park, and the information risk degree of the asset information base in the monitoring period is analyzed through the information risk assessment module, so that the safety of the park asset information is improved. The safety test is performed and the test performance is comprehensively evaluated when the risk controllable signal is generated, and the on-duty condition of the administrator in the area where the park operation end is located in the monitoring period is analyzed when the safety test qualified signal is generated, so that the safety of the asset information base is remarkably improved, and the intelligent level is high.

Description

Technical Field

[0001] The present invention relates to the technical field of park asset information management, and in particular to an artificial intelligence-based park asset information security management system. Background Art

[0002] Park asset information covers all relevant information of resources with economic value and physical form in the park, including basic information, classification information, location information, status information and value information. This information is of great significance for improving park management efficiency, optimizing resource allocation, preventing asset losses and supporting decision-making.

[0003] At present, it is difficult to conduct comprehensive monitoring, early warning, protection and management of park asset information when managing park asset information, and it is impossible to reasonably analyze and accurately judge the risk level and safety performance test performance faced by park asset information, which is not conducive to ensuring the security of park asset information. The security management of park asset information is difficult and the degree of intelligence is low;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an artificial intelligence-based park asset information security management system, which solves the problem that the existing technology is difficult to comprehensively monitor, warn, protect and manage park asset information, and is unable to reasonably analyze and accurately judge the risk level and safety performance test performance faced by park asset information, which is not conducive to ensuring the security of park asset information.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An artificial intelligence-based park asset information security management system includes a park management platform and a park operation terminal, wherein the park management platform includes an asset information database, an information security monitoring module, an intelligent early warning module, a security protection module and a management decision-making module; the asset information database is used to store park asset information, and the information security monitoring module is used to build a security monitoring model based on deep learning, automatically classify, label and identify asset information, and use artificial intelligence technology to monitor the asset information database in real time, analyze changes in asset information, identify abnormal behaviors and potential security threats, and send the analysis results to the intelligent early warning module;

[0008] Based on the analysis results of the information security monitoring module, the intelligent early warning module automatically triggers the early warning mechanism when abnormal behavior or potential security threats are found, and sends early warning information to the management decision-making module and the security protection module, where the early warning information includes the type, time, location and impact range of the abnormal behavior or potential security threat; the security protection module performs security protection on the park asset information, including data encryption, access control and firewall settings, and takes corresponding security protection measures according to the early warning information sent by the intelligent early warning module; the management decision-making module adjusts the security strategy and optimizes the security protection measures according to the early warning information and the implementation of the security protection measures, and sends the management decision results to the park operation end.

[0009] Furthermore, the park management platform also includes an asset rental and sales management module, a property supervision module, an intelligent ledger module and an enterprise service module.

[0010] Furthermore, the asset leasing and sales management module is used to realize online and offline contract collaboration, edit contract templates online and manage contract changes, renewals and lease terminations, and send reminders to tenants' clients in real time to remind them of expiration and payment dates;

[0011] The property supervision module is used to supervise the park property, record the work records, performance, time spent and customer satisfaction of each property repair personnel and on-site processing personnel, as well as record the material consumption and cost generated by each work order, and send the recorded information to the property end;

[0012] The intelligent ledger module is used to quickly achieve financial write-off matching, automatically calculate the monthly amortization amount of rights and responsibilities, and check financial statements in real time; the enterprise service module is used to provide highly reliable enterprise value-added services to enterprises in the park, and push the park's corresponding service policy information to the tenant's client.

[0013] Furthermore, the intelligent early warning module is communicated with the information risk assessment module. The information risk assessment module is used to set a monitoring period of T1 days. When the number of days reaches T1, the information risk level of the asset information database within the monitoring period is analyzed, and a risk alarm signal or a risk controllable signal is generated through the analysis. The risk alarm signal or the risk controllable signal is sent to the park operation end, and the park operation end issues a corresponding early warning when receiving the risk alarm signal.

[0014] Furthermore, the specific analysis process of the information risk assessment module includes:

[0015] The total number of abnormal behaviors or potential security threats that occur in the asset information database during the monitoring period is collected and marked as the abnormal threat frequency, and the identification time of the corresponding abnormal behavior or potential security threat is marked as the target time, and the time when the corresponding abnormal behavior or potential security threat is eliminated is marked as the termination time, and the interval between the termination time and the corresponding target time is marked as the non-safety time;

[0016] The non-safe time duration is numerically compared with the corresponding preset non-safe time duration threshold. If the non-safe time duration exceeds the corresponding preset non-safe time duration threshold, the corresponding non-safe time duration is marked as a hidden danger time duration; the number of hidden danger time durations within the monitoring period is obtained and marked as information hidden danger frequency, and the abnormal threat frequency and information hidden danger frequency are numerically compared with the preset abnormal threat frequency threshold and the preset information hidden danger frequency threshold respectively. If the abnormal threat frequency or the information hidden danger frequency exceeds the corresponding preset threshold, a risk alarm signal is generated.

[0017] Furthermore, if the frequency of abnormal threats and the frequency of information risks do not exceed the corresponding preset thresholds, all abnormal behaviors or potential security threats occurring during the monitoring period are classified, and several groups of abnormal threat types are obtained accordingly. The corresponding abnormal threat types are marked as target types i, and i is a natural number greater than or equal to 1;

[0018] The number of occurrences of abnormal behaviors or potential security threats corresponding to target type i in the monitoring period is obtained and marked as the risk matching value, and the ratio of the number of hidden danger durations corresponding to target type i in the monitoring period to the risk matching value is marked as the response abnormality value; and the ratio of the corresponding unsafe duration to the corresponding preset unsafe duration threshold is marked as the duration ratio value, and the average of all duration ratio values ​​corresponding to target type i in the monitoring period is calculated to obtain the response time table value;

[0019] The abnormal threat alarm value is obtained by numerically calculating the risk matching value, the response abnormal value and the response time table value of the target type i, and the abnormal threat alarm value is numerically compared with the corresponding preset abnormal threat alarm threshold. If the abnormal threat alarm value exceeds the corresponding preset abnormal threat alarm threshold, the target type i is marked as a non-controllable type; if a non-controllable type exists within the monitoring period, a risk alarm signal is generated; if a non-controllable type does not exist within the monitoring period, a risk controllable signal is generated.

[0020] Furthermore, the information risk assessment module is communicated with the information security testing module. The information risk assessment module sends a risk controllable signal to the information security testing module. When the information security testing module receives the risk controllable signal, it performs several security tests on the asset information database, simulates various attack scenarios, and verifies the security performance of the asset information database.

[0021] Furthermore, the information security test module communicates with the test performance evaluation module. After completing the test, the information security test module sends the test evaluation scores of each security test to the test performance evaluation module. The test performance evaluation module conducts a comprehensive evaluation and analysis of the test performance based on the test evaluation scores of each security test, and generates a security test pass signal or a security test fail signal through the analysis, and sends the security test pass signal or the security test fail signal to the park operation end.

[0022] Furthermore, the specific analysis process of the comprehensive evaluation and analysis of test performance is as follows:

[0023] Collect the test evaluation scores of each security test, compare the test evaluation scores with the corresponding preset test evaluation score thresholds, and if the test evaluation scores do not exceed the corresponding preset test evaluation score thresholds, mark the corresponding security test as a vulnerability test; if there is a vulnerability test, generate a security test failure signal;

[0024] If there is no vulnerability test, the ratio of the test evaluation score of the corresponding security test to the corresponding preset test evaluation score threshold is marked as the test performance value, and a set of preset weight values ​​is set in advance for each security test. The product of the test performance value of the corresponding security test and the corresponding preset weight value is marked as the test analysis value. The test analysis values ​​of all security tests are summed up to obtain a test comprehensive evaluation value, and the test comprehensive evaluation value is numerically compared with the preset test comprehensive evaluation threshold. If the test comprehensive evaluation value exceeds the preset test comprehensive evaluation threshold, a security test qualified signal is generated; if the test comprehensive evaluation value does not exceed the preset test comprehensive evaluation threshold, a security test unqualified signal is generated.

[0025] Furthermore, the test performance evaluation module is connected to the background supervision and evaluation module in communication, and the test performance evaluation module sends a safety test pass signal to the background supervision and evaluation module. When the background supervision and evaluation module receives the safety test pass signal, it analyzes the on-the-job status of the administrators in the area where the park operation end is located during the monitoring period. When there is no administrator in the area where the park operation end is located, it is judged that it is in a state of management omission;

[0026] The total duration that the park operation end is in a management omission state during the monitoring period is obtained and marked as the total management omission time value, and the number of occurrences in which the single continuous duration of the park operation end in the management omission state during the monitoring period exceeds the corresponding preset time threshold is marked as the management omission risk frequency value, and the background supervision evaluation value is obtained by numerically calculating the total management omission time value and the management omission risk frequency value, and the background supervision evaluation value is numerically compared with the preset background supervision evaluation threshold. If the background supervision evaluation value exceeds the preset background supervision evaluation threshold, a background supervision alarm signal is generated and sent to the park operation end. The park operation end issues a corresponding warning when receiving the background supervision alarm signal.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] 1. In the present invention, the asset information database is monitored in real time through artificial intelligence technology. When abnormal behavior or potential security threats are found, the early warning mechanism is automatically triggered, and corresponding security protection measures are taken according to the early warning information, thereby realizing comprehensive monitoring, early warning, protection and management of the park's asset information, improving the security and management efficiency of the park's asset information, and providing strong technical support for the intelligent development of the park;

[0029] 2. In the present invention, the information risk level of the asset information database within the monitoring period is analyzed through the information risk assessment module, and a security test is performed and the test performance is comprehensively evaluated when a risk controllable signal is generated. When a security test qualified signal is generated, the on-the-job status of the administrators in the area where the park operation end is located during the monitoring period is analyzed, and when a risk alarm signal, a security test unqualified signal or a background supervision alarm signal is generated, the park operation end issues an early warning, which is beneficial to significantly improve the security of the asset information database and has a high level of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0031] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0032] Figure 2 This is a system block diagram of Embodiment 2, Embodiment 3 and Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] Embodiment 1: Figure 1 As shown, the present invention proposes an artificial intelligence-based park asset information security management system, including a park management platform and a park operation terminal. It should be noted that the park management platform includes an asset information library, an information security monitoring module, an intelligent early warning module, a security protection module, and a management decision module;

[0035] The asset information database stores all data including park asset information. The information security monitoring module builds a security monitoring model based on deep learning to automatically classify, label and identify asset information, improve the accuracy and efficiency of monitoring, and use artificial intelligence technology to monitor the asset information database in real time, analyze changes in asset information, identify abnormal behaviors and potential security threats, and send the analysis results to the intelligent early warning module;

[0036] Based on the analysis results of the information security monitoring module, the intelligent early warning module automatically triggers the early warning mechanism when abnormal behavior or potential security threats are found, and sends early warning information to the management decision module and the security protection module. The early warning information includes detailed information such as the type, time, location and impact range of the abnormal behavior or potential security threat;

[0037] The security protection module provides security protection for the park's asset information, including data encryption, access control, and firewall settings. According to the warning information sent by the intelligent warning module, corresponding security protection measures are taken, such as isolating abnormal devices, restricting access rights, and starting firewalls, to prevent the occurrence of information security incidents.

[0038] The management decision module adjusts the security strategy and optimizes the security measures according to the early warning information and the implementation of the security measures, and sends the management decision results to the park operation end, which is conducive to ensuring the security of the park's asset information. The present invention realizes the comprehensive monitoring, early warning, protection and management of the park's asset information, improves the security and management efficiency of the park's asset information, and thus provides strong technical support for the intelligent development of the park.

[0039] Furthermore, the park management platform also includes asset leasing and sales management module, property supervision module, intelligent ledger module and enterprise service module; among them, the asset leasing and sales management module is used to realize online and offline contract collaboration, edit contract templates online and manage contract changes, renewals and terminations, and send reminder information to tenants' clients in real time to remind tenants of expiration and payment dates;

[0040] The property supervision module conducts park property supervision, records the work records, performance, time spent and customer satisfaction of each property repair personnel and on-site processing personnel, and records the material consumption and cost generated by each work order, so as to facilitate the effective assessment of front-line property personnel, ensure the continuous satisfaction of customers, and send the recorded information to the property end;

[0041] The intelligent ledger module is used to quickly achieve financial write-off matching, automatically calculate the monthly amortization amount, and check financial statements in real time to avoid calculation errors; the enterprise service module is used to provide highly reliable enterprise value-added services to enterprises in the park, increase the stickiness of operators and incubated enterprises, improve occupancy rate and renewal rate, and push the park's corresponding service policy information to tenants' clients;

[0042] By integrating rental and sales management, property supervision, intelligent ledgers and enterprise service push functions, it is conducive to effective communication between operators, property owners and tenants, and realizes effective management of park assets. It has a high level of intelligence and further promotes the intelligent development of the park.

[0043] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the intelligent early warning module is connected to the information risk assessment module in communication, and the information risk assessment module is used to set a monitoring period of T1. When the number of days reaches T1, preferably, T1 is forty days; the information risk level of the asset information database within the monitoring period is analyzed, and a risk alarm signal or a risk controllable signal is generated through the analysis;

[0044] The risk alarm signal or risk controllable signal is sent to the park operation end. When the park operation end receives the risk alarm signal, it issues a corresponding warning to remind the administrator to strengthen the security supervision of the asset information database, which is conducive to the administrator to reasonably formulate corresponding supervision measures and optimize the security protection strategy, and significantly improve the security of the asset information database; the specific analysis process of the information risk assessment module is as follows:

[0045] The total number of abnormal behaviors or potential security threats that occur in the asset information database during the monitoring period is collected and marked as the abnormal threat frequency, and the identification time of the corresponding abnormal behavior or potential security threat is marked as the target time, and the time when the corresponding abnormal behavior or potential security threat is eliminated is marked as the termination time, and the interval between the termination time and the corresponding target time is marked as the non-safety time; wherein, the larger the value of the non-safety time, the less timely the response to the corresponding abnormal behavior or potential security threat is, and the greater the hidden danger to the asset information database;

[0046] The non-safe time is numerically compared with the corresponding preset non-safe time threshold. If the non-safe time exceeds the corresponding preset non-safe time threshold, the corresponding non-safe time is marked as hidden danger time; the number of hidden danger time in the monitoring period is obtained and marked as information hidden danger frequency, and the abnormal threat frequency and information hidden danger frequency are numerically compared with the preset abnormal threat frequency threshold and the preset information hidden danger frequency threshold respectively. If the abnormal threat frequency or the information hidden danger frequency exceeds the corresponding preset threshold, it indicates that the security risk of the asset information database in the monitoring period is relatively large, and a risk alarm signal is generated.

[0047] Furthermore, if the frequency of abnormal threats and the frequency of information risks do not exceed the corresponding preset thresholds, all abnormal behaviors or potential security threats that occur during the monitoring period are classified, and several groups of abnormal threat types (such as data leakage, denial of service attacks, malicious code injections, and unauthorized operations, etc.) are obtained accordingly. The corresponding abnormal threat type is marked as target type i, and i is a natural number greater than or equal to 1;

[0048] The number of occurrences of abnormal behaviors or potential security threats corresponding to target type i in the monitoring period is obtained and marked as the risk matching value, and the ratio of the number of hidden danger durations corresponding to target type i in the monitoring period to the risk matching value is marked as the response abnormality value; and the ratio of the corresponding unsafe duration to the corresponding preset unsafe duration threshold is marked as the duration ratio value, and the average of all duration ratio values ​​corresponding to target type i in the monitoring period is calculated to obtain the response time table value;

[0049] The risk matching value TLi of target type i, the response abnormal value WYi and the response time table value SWi are numerically calculated by the formula Pi=t×TLi+q×WYi+g×SWi to obtain the abnormal threat alarm value Pi; wherein t, q, g are preset weight coefficients with values ​​greater than zero, q>g>t>0; and the larger the value of the abnormal threat alarm value Pi, the greater the threat posed by target type i to the information security of park assets during the monitoring period;

[0050] The abnormal threat alarm value Pi is numerically compared with the corresponding preset abnormal threat alarm threshold. If the abnormal threat alarm value Pi exceeds the corresponding preset abnormal threat alarm threshold, it indicates that the target type i poses a greater threat to the asset information security of the park during the monitoring period, and the target type i is marked as a non-controllable type; if a non-controllable type exists during the monitoring period, it indicates that the security risk of the asset information database during the monitoring period is relatively large, and a risk alarm signal is generated; if a non-controllable type does not exist during the monitoring period, it indicates that the security risk of the asset information database during the monitoring period is relatively small, and a risk controllable signal is generated.

[0051] Embodiment 3: Figure 2 As shown, the difference between this embodiment and Embodiment 1 and Embodiment 2 is that the information risk assessment module is communicatively connected to the information security testing module, and the information risk assessment module sends a risk controllable signal to the information security testing module. When the information security testing module receives the risk controllable signal, it performs several security tests (including penetration testing, code auditing, and security function testing, etc.) on the asset information library, simulates various attack scenarios, verifies the security performance of the asset information library, and obtains the test evaluation scores of various security tests accordingly. It should be noted that the larger the test evaluation score of the corresponding security test, the better the test result performance for the corresponding security test.

[0052] Further, the information security test module communicates with the test performance comprehensive evaluation module. After completing the test, the information security test module sends the test evaluation scores of each security test to the test performance comprehensive evaluation module. The test performance comprehensive evaluation module performs a comprehensive evaluation and analysis of the test performance based on the test evaluation scores of each security test, and generates a security test pass signal or a security test fail signal through analysis;

[0053] The safety test pass signal or safety test fail signal is sent to the park operation end. When the park operation end receives the safety test fail signal, it issues a corresponding warning to remind the management personnel to conduct cause investigation and analysis, and make targeted and reasonable improvement measures to ensure the security of the asset information database. The specific analysis process of the comprehensive evaluation and analysis of test performance is as follows:

[0054] Collect the test evaluation scores of each security test, compare the test evaluation scores with the corresponding preset test evaluation score thresholds, if the test evaluation scores do not exceed the corresponding preset test evaluation score thresholds, indicating that the test results for the corresponding security test are poor, then the corresponding security test is marked as a vulnerability test; if there is a vulnerability test, a security test failure signal is generated;

[0055] If there is no vulnerability test, the ratio of the test evaluation score of the corresponding security test to the corresponding preset test evaluation score threshold is marked as the test performance value, and each security test is set in advance to correspond to a set of preset weight values, and the product of the test performance value of the corresponding security test and the corresponding preset weight value is marked as the test analysis value, and the test analysis values ​​of all security tests are summed up to obtain the test comprehensive evaluation value;

[0056] The test comprehensive evaluation value is numerically compared with the preset test comprehensive evaluation threshold. If the test comprehensive evaluation value exceeds the preset test comprehensive evaluation threshold, a safety test pass signal is generated; if the test comprehensive evaluation value does not exceed the preset test comprehensive evaluation threshold, a safety test fail signal is generated.

[0057] Embodiment 4: Figure 2 As shown, the difference between this embodiment and the first, second and third embodiments is that the test performance evaluation module is connected to the background supervision and evaluation module in communication, and the test performance evaluation module sends the safety test qualified signal to the background supervision and evaluation module. When the background supervision and evaluation module receives the safety test qualified signal, it analyzes the on-the-job status of the administrator in the area where the park operation end is located during the monitoring period. When there is no administrator in the area where the park operation end is located, it is judged that it is in a management omission state;

[0058] The total duration of the park operation terminal being in a management omission state during the monitoring period is obtained and marked as the total management omission time value, and the number of occurrences of the park operation terminal being in a management omission state for a single duration exceeding the corresponding preset time threshold during the monitoring period is marked as the management omission risk frequency value;

[0059] The total time value of management omission GY and the risk value of management omission WF are numerically calculated by the formula X=e×GY+n×WF to obtain the background supervision evaluation value X; wherein, e and n are preset weight coefficients with values ​​greater than zero, n>e>0; and the larger the value of the background supervision evaluation value X, the worse the overall performance of the administrator at the park operation end during the monitoring period, which is less conducive to ensuring the efficiency of the park asset information risk response;

[0060] The background supervision evaluation value X is numerically compared with the preset background supervision evaluation threshold. If the background supervision evaluation value X exceeds the preset background supervision evaluation threshold, it indicates that the on-the-job performance of the administrator at the park operation end during the monitoring period is generally poor, which is not conducive to ensuring the efficiency of the park asset information risk response. In this way, a background supervision alarm signal is generated and sent to the park operation end. When the park operation end receives the background supervision alarm signal, it issues a corresponding warning and promptly strengthens the supervision of the administrator in the subsequent period to ensure the efficiency of the subsequent response to the park asset information risk and further improve the security of the park asset information.

[0061] The working principle of the present invention is as follows: when in use, the asset information database is monitored in real time through artificial intelligence technology to identify abnormal behaviors and potential security threats. When abnormal behaviors or potential security threats are found, the early warning mechanism is automatically triggered. The security protection module takes corresponding security protection measures according to the early warning information to prevent the occurrence of information security incidents, thereby realizing comprehensive monitoring, early warning, protection and management of the park's asset information, improving the security and management efficiency of the park's asset information, and providing strong technical support for the intelligent development of the park. The information risk assessment module analyzes the information risk level of the asset information database within the monitoring period, performs security testing when generating a risk controllable signal and comprehensively evaluates the test performance, and analyzes the on-the-job status of administrators in the area where the park's operating end is located during the monitoring period when generating a security test qualified signal, which is beneficial to significantly improve the security of the asset information database.

[0062] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An artificial intelligence-based park asset information security management system, characterized in that: It includes a park management platform and a park operation end. The park management platform includes an asset information database, an information security monitoring module, an intelligent early warning module, a security protection module, and a management decision-making module. The asset information database is used to store park asset information. The information security monitoring module is used to build a security monitoring model based on deep learning, automatically classify, label, and identify asset information, and use artificial intelligence technology to monitor the asset information database in real time, analyze changes in asset information, identify abnormal behaviors and potential security threats, and send the analysis results to the intelligent early warning module. Based on the analysis results of the information security monitoring module, the intelligent early warning module automatically triggers the early warning mechanism when abnormal behavior or potential security threats are found, and sends early warning information to the management decision-making module and the security protection module; the security protection module performs security protection on the park's asset information and takes corresponding security protection measures based on the early warning information sent by the intelligent early warning module; the management decision-making module adjusts the security strategy based on the early warning information and the implementation of the security protection measures, and sends the management decision results to the park operation end.

2. According to the artificial intelligence-based park asset information security management system of claim 1, it is characterized in that: The park management platform also includes asset rental and sales management module, property supervision module, intelligent ledger module and enterprise service module.

3. According to the artificial intelligence-based park asset information security management system of claim 2, it is characterized in that: The asset leasing and sales management module is used to realize online and offline contract collaboration, edit contract templates online, and manage contract changes, renewals, and lease terminations; the property supervision module is used to supervise park properties, record the work records, performance, time spent, and customer satisfaction of each property repair person and on-site processing person, and record the material consumption and cost generated by each work order; The intelligent ledger module is used to quickly achieve financial write-off matching, automatically calculate the monthly amortization amount of rights and responsibilities, and check financial statements in real time; the enterprise service module is used to provide highly reliable enterprise value-added services to enterprises in the park, and push the park's corresponding service policy information to the tenant's client.

4. According to the artificial intelligence-based park asset information security management system of claim 1, it is characterized in that: The intelligent early warning module is communicated with the information risk assessment module. The information risk assessment module is used to set a monitoring period of T1 days. When the number of days reaches T1, the information risk level of the asset information database within the monitoring period is analyzed, and a risk alarm signal or a risk controllable signal is generated through the analysis, and the risk alarm signal or the risk controllable signal is sent to the park operation end.

5. The park asset information security management system based on artificial intelligence according to claim 4 is characterized in that: The specific analysis process of the information risk assessment module is as follows: the total number of abnormal behaviors or potential security threats in the asset information database during the monitoring period is collected and marked as the abnormal threat frequency, the number of hidden danger durations during the monitoring period is obtained and marked as the information hidden danger frequency, and if the abnormal threat frequency or the information hidden danger frequency exceeds the corresponding preset threshold, a risk alarm signal is generated.

6. The park asset information security management system based on artificial intelligence according to claim 5 is characterized in that: If the abnormal threat frequency and the information hidden danger frequency do not exceed the corresponding preset thresholds, the abnormal threat alarm value is obtained by numerically calculating the risk matching value, the response abnormal value and the response time table value of the target type i. If the abnormal threat alarm value exceeds the corresponding preset abnormal threat alarm threshold, the target type i is marked as a non-controllable type; if a non-controllable type exists within the monitoring period, a risk alarm signal is generated; if a non-controllable type does not exist within the monitoring period, a risk controllable signal is generated.

7. The park asset information security management system based on artificial intelligence according to claim 4 is characterized in that: The information risk assessment module is communicatively connected to the information security testing module. The information risk assessment module sends a risk controllable signal to the information security testing module. When the information security testing module receives the risk controllable signal, it performs several security tests on the asset information library.

8. The park asset information security management system based on artificial intelligence according to claim 7 is characterized in that: Information security test module communication connection test performance comprehensive evaluation module. After the information security test module completes the test, the test performance comprehensive evaluation module conducts a comprehensive evaluation and analysis of the test performance based on the test evaluation scores of each security test, and generates a security test pass signal or a security test fail signal through analysis, and sends the security test pass signal or the security test fail signal to the park operation end.

9. The artificial intelligence-based park asset information security management system according to claim 8 is characterized in that: The specific analysis process of the comprehensive evaluation and analysis of test performance is as follows: If there is a vulnerability test, a security test failure signal is generated; if there is no vulnerability test, the test comprehensive evaluation value is compared with the preset test comprehensive evaluation threshold, and if the test comprehensive evaluation value exceeds the preset test comprehensive evaluation threshold, a security test pass signal is generated; Otherwise a safety test failure signal is generated.

10. The park asset information security management system based on artificial intelligence according to claim 8 is characterized in that: The test performance evaluation module is communicated with the background supervision and evaluation module. The test performance evaluation module sends the safety test pass signal to the background supervision and evaluation module. When the background supervision and evaluation module receives the safety test pass signal, it analyzes the on-the-job status of the administrators in the area where the park operation end is located during the monitoring period, and sends the background supervision alarm signal to the park operation end when it generates it.

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