Student safety assessment method and electronic equipment

Abstract

The invention discloses a student safety assessment method and electronic equipment, and the method comprises the steps: obtaining the behavior data of a target student in a time period according to the specified time period in a safety event corresponding to various types of behavior data; the behavior data comprises at least one of consumption data, academic data, social data, internet surfing data and access data of each place in a school; for each type of behavior data, if the first data content of the behavior data of the type is matched with the second data content specified in the security event corresponding to the type, determining to trigger the security event; and determining a safety assessment result of the target student according to the times of triggering each safety event by each type of behavior data of the target student in a historical time period. Accurate safety assessment management is carried out on each student.

Description

Technical Field

[0001] The present application relates to the technical field of smart campus management, and in particular to a student safety assessment method and electronic equipment. Background Art

[0002] With the rapid development of information technology, smart campus has gradually become a new trend in modern education. As an important part of this trend, smart campus safety warning provides a solid guarantee for campus safety. However, with the expansion of campus scale and the increase in the number of students, faculty and visitors, as well as the richness and diversity of various teaching activities, campus safety issues have increasingly highlighted the importance and urgency of safety warning. With the continuous advancement of educational informatization and the rapid development of big data technology, campus safety management faces unprecedented challenges and opportunities.

[0003] The existing technology generally relies on management personnel inspections, experience judgment, monitoring and other methods to manage student safety. On the one hand, the existing technology solutions are affected by the subjective judgment of management personnel. On the other hand, it is difficult for monitoring to cover every corner of the campus. The existing technology cannot achieve accurate safety management of each student. Summary of the invention

[0004] The present application provides a student safety assessment method and electronic equipment to solve the problem that the existing technology cannot accurately manage the safety of each student.

[0005] In a first aspect, the present application provides a student safety assessment method, the method comprising:

[0006] According to the time period specified in the security incident corresponding to each type of behavior data, the behavior data of the target student within the time period is obtained; the behavior data includes at least one of consumption data, academic data, social data, Internet access data, and entry and exit data of various places in the school;

[0007] For each type of behavior data, if the first data content of the behavior data of the category matches the second data content specified in the security event corresponding to the category, it is determined that the security event is triggered;

[0008] The security assessment result of the target student is determined according to the number of times each security event is triggered by various behavioral data of the target student in a historical time period.

[0009] The above technical solution has the following advantages or beneficial effects:

[0010] Because in this application, corresponding security events are pre-set for various types of behavioral data. Various types of behavioral data include at least one of consumption data, academic data, social data, Internet data, and entry and exit data of various places in the school. A time period is specified in the security event. For each type of behavioral data, the behavior data of the target student in the time period specified in the corresponding security event is obtained. Then it is determined whether the first data content of the target student's behavioral data matches the second data content specified in the corresponding security event. If it matches, it is determined that the security event is triggered, otherwise the security event is not triggered. According to the number of times each security event is triggered by various types of behavioral data of the target student in the historical time period, the security assessment result of the target student is determined. This application combines the consumption data, academic data, social data, Internet data, and entry and exit data of various places in the school of the target student to conduct a student safety assessment on the target student. Compared with the solution of student safety management relying on management personnel inspections, experience judgment, monitoring, etc., accurate security assessment management can be achieved for each student.

[0011] In an optional implementation manner, if the various types of behavior data include consumption data, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0012] The total consumption amount in the first time period is less than the preset consumption threshold;

[0013] The number of consumptions in the second time period is less than the preset first number threshold;

[0014] The average consumption amount in the third time period increases by a ratio greater than a preset first ratio threshold value compared with the average consumption amount in the previous third time period;

[0015] The average consumption amount in the fourth time period decreases by a ratio greater than a preset second ratio threshold value compared with the average consumption amount in the previous fourth time period.

[0016] In an optional implementation, if the various types of behavior data include academic data, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0017] The number of failed courses in the courses taken during the fifth time period is greater than a preset first quantity threshold;

[0018] The number of failed courses after reexamination in the sixth time period is greater than a preset second quantity threshold;

[0019] The credits earned in the seventh time period are less than the preset credit threshold;

[0020] The number of absences during the eighth time period is greater than a preset second number threshold;

[0021] During the ninth time period, the performance ranking declines to a level greater than the preset ranking threshold.

[0022] In an optional implementation, if the various types of behavior data include social data, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0023] Not joining a club during the tenth time period;

[0024] Joining a community during the eleventh time period, and the ratio of the number of activities participated in the community to the total number of activities organized by the community is less than the preset third ratio threshold;

[0025] In the twelfth time period, the number of the target student's stable friends is less than a preset third number threshold.

[0026] In an optional implementation manner, the process of determining the stable friends of the target student includes:

[0027] For each consumption of the target student in the twelfth time period, determine the time window corresponding to the consumption, determine each candidate student who consumes in the time window, and set the number of occurrences of each candidate student to 1;

[0028] For each candidate student that appears in the twelfth time period, the number of appearances of the candidate student is accumulated to obtain a total number of appearances; if the total number of appearances is greater than a preset third number threshold, the candidate student is determined as a stable friend of the target student.

[0029] The above technical solution has the following advantages or beneficial effects:

[0030] In this application, the target student's stable friends are determined based on the target student's consumption data. Specifically, the time window corresponding to each consumption of the target student is determined, and then each candidate student who consumes within the time window is determined, and the number of occurrences of each candidate student is set to 1. Then the total number of occurrences of each candidate student is counted, and the candidate students whose total number of occurrences is greater than the preset third number threshold are determined as stable friends, thereby improving the accuracy of determining stable friends.

[0031] In an optional implementation, if the various types of behavior data include Internet access data, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0032] The online time during the thirteenth time period exceeds the preset online time period;

[0033] Visiting a preset blacklist website within the fourteenth time period;

[0034] The online comments published during the fifteenth time period contain preset blacklist words.

[0035] In an optional implementation, if the various types of behavior data include entry and exit data of various places in the school, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0036] There is no attendance record of entering or leaving any place during the sixteenth time period; the places include at least one of a library, dormitory, restaurant and classroom;

[0037] Entering a preset danger zone during the seventeenth sub-time period.

[0038] In an optional implementation, the process of determining the safety assessment result of the target student includes:

[0039] For each of the security events, determine a security assessment score for the security event according to the number of times the security event is triggered;

[0040] Determine the total security assessment score based on the security assessment scores of each security incident and the corresponding weight values; determine the security assessment result of the target student based on the total security assessment score; the security assessment result includes one of the following: major security assessment risk, potential security assessment risk, general security assessment risk and no security assessment risk.

[0041] The above technical solution has the following advantages or beneficial effects:

[0042] In this application, for each security event, the security assessment score of the security event is determined according to the number of times the security event is triggered. Then, a corresponding weight value is configured for each security event. Different weight values ​​can be set according to the importance of each security event. The weight value corresponding to a security event with a greater degree of importance is larger, and the weight value corresponding to a security event with a smaller degree of importance is smaller. Then, based on the security assessment score and the corresponding weight value of each security event, the total security assessment score is determined; and the security assessment result of the target student is determined based on the total security assessment score. Thereby, the accuracy of determining the security assessment result of the target student is improved.

[0043] In an optional implementation, if the various types of behavior data include online data, the second data content specified in the security event corresponding to the category includes a preset blacklist word included in the online speech within the fifteenth time period, and according to the number of times the security event is triggered, determining the security assessment score of the security event includes:

[0044] Determine a first ratio of the number of speeches containing blacklist words to the total number of speeches made by the target student in the fifteenth time period; determine a second ratio of the number of blacklist words contained in online speeches to the total number of words in a preset blacklist vocabulary list; determine a third ratio of the time length of speeches containing blacklist words to the time length of the fifteenth time period; and determine a security assessment score for the security incident based on the sum of the first ratio, the second ratio and the third ratio.

[0045] The above technical solution has the following advantages or beneficial effects:

[0046] In this application, it is considered that the number of speeches containing blacklist words, the number of blacklist words contained in online speeches, and the length of time of speeches containing blacklist words by the target students will all reflect the safety level of the target students. Therefore, this application determines the first ratio of the number of speeches containing blacklist words to the total number of speeches, the second ratio of the number of blacklist words contained in online speeches to the total number of words in the preset blacklist vocabulary list; and the third ratio of the length of time of speeches containing blacklist words to the length of time of the fifteenth time period. Then, based on the sum of the first ratio, the second ratio, and the third ratio, the security assessment score of the security incident of containing preset blacklist words in online speeches is determined. Thereby, the accuracy of determining the security assessment score of the security incident can be improved.

[0047] In a second aspect, the present application provides a student safety assessment device, the device comprising:

[0048] An acquisition module, for acquiring the target student's behavior data within the time period specified in the security event corresponding to each type of behavior data; the behavior data includes at least one of consumption data, academic data, social data, Internet access data, and entry and exit data of various places in the school;

[0049] A determination module, for determining, for each type of behavior data, that the security event is triggered if the first data content of the behavior data of the category matches the second data content specified in the security event corresponding to the category;

[0050] The evaluation module is used to determine the security evaluation result of the target student according to the number of times each security event is triggered by various behavioral data of the target student in a historical time period.

[0051] The evaluation module is specifically used to determine the security evaluation score of each security event according to the number of times the security event is triggered;

[0052] Determine the total security assessment score based on the security assessment scores of each security incident and the corresponding weight values; determine the security assessment result of the target student based on the total security assessment score; the security assessment result includes one of the following: major security assessment risk, potential security assessment risk, general security assessment risk and no security assessment risk.

[0053] The evaluation module is specifically used to determine a first ratio of the number of speeches containing blacklist words to the total number of speeches made by the target student within the fifteenth time period; determine a second ratio of the number of blacklist words contained in online speeches to the total number of words in a preset blacklist vocabulary list; determine a third ratio of the time length of speeches containing blacklist words to the time length of the fifteenth time period; and determine the security assessment score of the security incident based on the sum of the first ratio, the second ratio and the third ratio.

[0054] In a third aspect, the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0055] Memory, used to store computer programs;

[0056] The processor is used to implement the method when executing the program stored in the memory.

[0057] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the described method is implemented.

[0058] In a fifth aspect, the present application provides a computer program product, wherein the computer program product comprises an executable program, and the executable program is executed by a processor to implement the described method. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0060] Figure 1 A schematic diagram of the student safety assessment process provided for this application;

[0061] Figure 2 A schematic diagram of the process of identifying stable friends of target students provided for this application;

[0062] Figure 3Schematic diagram of the process for determining the safety assessment results of target students for this application;

[0063] Figure 4 A schematic diagram of the process of determining the security assessment score of a security event based on the number of times a security event is triggered provided by this application;

[0064] Figure 5 A detailed flowchart of the student safety assessment provided for this application;

[0065] Figure 6 Another detailed flow chart of the student safety assessment provided for this application;

[0066] Figure 7 A schematic diagram of the display interface for the security assessment results provided in this application;

[0067] Figure 8 The student safety assessment system architecture diagram provided for this application;

[0068] Fig. 9 A schematic diagram of the structure of the student safety assessment device provided for this application;

[0069] Fig.10 This is a schematic diagram of the electronic device structure provided in this application. DETAILED DESCRIPTION

[0070] In order to make the purpose and implementation method of the present application clearer, the exemplary implementation method of the present application will be clearly and completely described below in conjunction with the drawings in the exemplary embodiments of the present application. Obviously, the described exemplary embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0071] It should be noted that the brief description of terms in this application is only for the convenience of understanding the embodiments described below, and is not intended to limit the embodiments of this application. Unless otherwise specified, these terms should be understood according to their common and usual meanings.

[0072] The terms "first", "second", "third", etc. in the specification and claims of this application and the above drawings are used to distinguish similar or similar objects or entities, and do not necessarily mean to limit a specific order or sequence, unless otherwise noted. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances.

[0073] The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover but not exclude inclusion, for example, a product or device comprising a list of components is not necessarily limited to all the components expressly listed but may include other components not expressly listed or inherent to such product or device.

[0074] The term "module" refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic, or combination of hardware and / or software code that is capable of performing the functions associated with that element.

[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0076] For the convenience of explanation, the above description has been made in conjunction with specific embodiments. However, the above exemplary discussion is not intended to be exhaustive or limit the embodiments to the specific forms disclosed above. Based on the above teachings, various modifications and variations can be obtained. The selection and description of the above embodiments are to better explain the principles and practical applications, so that those skilled in the art can better use the embodiments and various different variations of the embodiments suitable for specific use considerations.

[0077] Figure 1 A diagram of the student safety assessment process provided for this application, which includes the following steps:

[0078] S101: According to the time period specified in the security event corresponding to each type of behavior data, the behavior data of the target student within the time period is obtained; the behavior data includes at least one of consumption data, academic data, social data, Internet access data, and entry and exit data of various places in the school;

[0079] S102: For each type of behavior data, if the first data content of the behavior data of the category matches the second data content specified in the security event corresponding to the category, determining that the security event is triggered;

[0080] S103: Determine a security assessment result of the target student according to the number of times each security event is triggered by each type of behavior data of the target student in a historical time period.

[0081] The student safety assessment method provided in this application is applied to electronic devices, which may be PCs, computers, servers and other devices.

[0082] For each student in the school, the student is taken as the target student, and various types of behavior data of the target student are obtained. Among them, various types of behavior data include at least one of consumption data, academic data, social data, Internet data and entry and exit data of various places in the school. Preferably, various types of behavior data include consumption data, academic data, social data, Internet data and entry and exit data of various places in the school at the same time, so as to improve the accuracy of student safety assessment. Consumption data includes consumption time, consumption amount, etc. Academic data includes test scores, failed course data, make-up test data, ranking data, credits data, etc. Social data includes participation in clubs, friendship data between students, etc. Internet data includes Internet time, visited websites, speech content, etc. The entry and exit data of various places in the school include entry and exit data of libraries, dormitories, restaurants, classrooms, pre-set dangerous areas, etc.

[0083] The students’ consumption data can be obtained through the school’s one-card system, their academic data can be obtained through the school’s academic affairs system, their social data can be obtained through the school’s one-card system and club records, their Internet access data can be obtained through the school’s network management system, and their entry and exit data of various places in the school can be obtained through the school’s access control system, library system, dormitory management system, and cameras deployed in the school.

[0084] At least one corresponding security event is set for each type of behavior data, and a time period and data content are specified in the security event. Among them, the data content specified in the security event is used as the second data content. For each type of behavior data, according to the time period specified in the security event corresponding to the type of behavior data, the behavior data of the target student in the time period is obtained. Then the first data content of the behavior data of the target student is determined. It is judged whether the first data content matches the second data content specified in the security event corresponding to the category. Optionally, the second data content specified in the security event can be a rule, such as the total amount of consumption in the time period is less than the set consumption value. If the total amount of consumption in the time period of the target student is less than the set consumption value, it is determined that the first data content matches the second data content, otherwise it is determined that the first data content does not match the second data content. For each type of behavior data, if the first data content of the behavior data of the category matches the second data content specified in the security event corresponding to the category, it is determined that the security event is triggered, otherwise it is determined that the security event is not triggered.

[0085] Then obtain the number of times each security incident is triggered by various types of behavioral data of the target students in the historical time period, and determine the security assessment result of the target students. The historical time period is, for example, a semester, a year, or a time period from the student's enrollment to the present, and the historical time period is not less than the time period specified in each security incident. Optionally, the total number of times each security incident is triggered can be determined. The greater the total number, the greater the security risk. For example, the security assessment result of a student whose total number is greater than the first threshold is a major security assessment risk, the security assessment result of a student whose total number is not greater than the first threshold and greater than the second threshold is a potential security assessment risk, the security assessment result of a student whose total number is not greater than the second threshold and greater than the third threshold is a general security assessment risk, and the security assessment result of a student whose total number is not greater than the third threshold is a no-risk security assessment.

[0086] Because in this application, corresponding security events are pre-set for various types of behavioral data. Various types of behavioral data include at least one of consumption data, academic data, social data, Internet data, and entry and exit data of various places in the school. A time period is specified in the security event. For each type of behavioral data, the behavior data of the target student in the time period specified in the corresponding security event is obtained. Then it is determined whether the first data content of the target student's behavioral data matches the second data content specified in the corresponding security event. If it matches, it is determined that the security event is triggered, otherwise the security event is not triggered. According to the number of times each security event is triggered by various types of behavioral data of the target student in the historical time period, the security assessment result of the target student is determined. This application combines the consumption data, academic data, social data, Internet data, and entry and exit data of various places in the school of the target student to conduct a student safety assessment on the target student. Compared with the solution of student safety management relying on management personnel inspections, experience judgment, monitoring, etc., accurate security assessment management can be achieved for each student.

[0087] The following is an explanation of the second data content specified in the security events corresponding to each type of behavior data.

[0088] In an optional implementation manner, if the various types of behavior data include consumption data, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0089] The total consumption amount in the first time period is less than the preset consumption threshold;

[0090] The number of consumptions in the second time period is less than the preset first number threshold;

[0091] The average consumption amount in the third time period increases by a ratio greater than a preset first ratio threshold value compared with the average consumption amount in the previous third time period;

[0092] The average consumption amount in the fourth time period decreases by a ratio greater than a preset second ratio threshold value compared with the average consumption amount in the previous fourth time period.

[0093] The first time period is, for example, a week, a month, etc. The total amount of consumption in the first time period is less than a preset consumption threshold, and the preset consumption threshold is, for example, 300 yuan, 400 yuan, etc. Optionally, the average amount of consumption in the first time period may be less than a preset average consumption threshold. The selection of the preset consumption threshold is related to the length of the first time period. The selection of the preset average consumption threshold is related to the length of the first time period.

[0094] The number of consumptions in the second time period is less than the preset first number threshold. The second time period is, for example, one week, two weeks, one month, etc. The preset first number threshold is, for example, 15 times, 18 times, etc. The selection of the preset first number threshold is related to the actual length of the second time period.

[0095] The average consumption amount in the third time period increases by a ratio greater than the average consumption amount in the previous third time period that is greater than a preset first ratio threshold. The third time period is, for example, one week, two weeks, etc. The preset first ratio threshold is, for example, 50%, 60%, etc.

[0096] The average consumption amount in the fourth time period decreases by a ratio greater than the average consumption amount in the previous fourth time period by a ratio greater than a preset second ratio threshold. The fourth time period is, for example, one week, two weeks, etc. The preset second ratio threshold is, for example, 50%, 60%, etc.

[0097] Each of the above rules is a security event corresponding to the consumption data. That is, the second data content specified in security event 1 is that the total consumption amount in the first time period is less than the preset consumption threshold; the second data content specified in security event 2 is that the number of consumption times in the second time period is less than the preset first number threshold; the second data content specified in security event 3 is that the average consumption amount in the third time period is greater than the average consumption amount in the previous third time period, and the ratio of the increase is greater than the preset first ratio threshold; the second data content specified in security event 4 is that the average consumption amount in the fourth time period is greater than the average consumption amount in the previous fourth time period, and the ratio of the decrease is greater than the preset second ratio threshold.

[0098] Preferably, the consumption data includes the above four security events at the same time, and the number of times the consumption data triggers each of the above four security events in the historical time period is subsequently counted, thereby improving the accuracy of student safety assessment.

[0099] In an optional implementation, if the various types of behavior data include academic data, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0100] The number of failed courses in the courses taken during the fifth time period is greater than a preset first quantity threshold;

[0101] The number of failed courses after reexamination in the sixth time period is greater than a preset second quantity threshold;

[0102] The credits earned in the seventh time period are less than the preset credit threshold;

[0103] The number of absences during the eighth time period is greater than a preset second number threshold;

[0104] During the ninth time period, the performance ranking declines to a level greater than the preset ranking threshold.

[0105] The number of failed courses in the courses taken in the fifth time period is greater than the preset first quantity threshold. The fifth time period is, for example, a semester, a school year, etc. The preset first quantity threshold is, for example, 6, 7, etc. The selection of the preset first quantity threshold is related to the length of the fifth time period.

[0106] The number of failed courses after the make-up exam in the sixth time period is greater than the preset second quantity threshold. The sixth time period is, for example, a semester, a school year, etc. The preset second quantity threshold is, for example, 4, 5, etc. The selection of the preset second quantity threshold is related to the length of the sixth time period.

[0107] The credits earned in the seventh time period are less than the preset credit threshold. The seventh time period is, for example, a semester, a school year, etc. The preset credit threshold is, for example, 10 points, 15 points, etc. The selection of the preset credit threshold is related to the length of the seventh time period. Optionally, the ratio of the credits earned by the target student in the seventh time period to the theoretical credits stipulated by the school can also be calculated. If the ratio is less than the set ratio threshold, the security event is triggered. The set ratio threshold is, for example, 0.4, 0.5, etc.

[0108] The number of absences in the eighth time period is greater than the preset second number threshold. The eighth time period is, for example, one week, one month, two months, etc. The preset second number threshold is, for example, 10, 15, etc. The selection of the preset second number threshold is related to the length of the eighth time period.

[0109] The ranking of the grade declines during the ninth time period is greater than the preset ranking threshold. The ninth time period is, for example, a semester, a school year, etc. The ranking of the grade decline may be the ranking of the grade decline within the class, and the preset ranking threshold is, for example, 10, 12, etc. The ranking of the grade decline may also be the ranking of the grade decline within the school's major, and the preset ranking threshold is, for example, 50, 60, etc.

[0110] Each of the above rules is used as a security event corresponding to academic data. That is, the second data content specified in security event 5 is that the number of failed courses in the fifth time period is greater than the preset first quantity threshold; the second data content specified in security event 6 is that the number of failed courses after the make-up exam in the sixth time period is greater than the preset second quantity threshold; the second data content specified in security event 7 is that the credits earned in the seventh time period are less than the preset credit threshold; the second data content specified in security event 8 is that the number of absences in the eighth time period is greater than the preset second number threshold; the second data content specified in security event 9 is that the grade decline in the ninth time period is greater than the preset ranking threshold.

[0111] Preferably, the academic data includes the above five security events at the same time, and the number of times the academic data triggers each of the above five security events within a historical time period is subsequently counted, thereby improving the accuracy of student safety assessment.

[0112] In an optional implementation, if the various types of behavior data include social data, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0113] Not joining a club during the tenth time period;

[0114] Joining a community during the eleventh time period, and the ratio of the number of activities participated in the community to the total number of activities organized by the community is less than the preset third ratio threshold;

[0115] In the twelfth time period, the number of the target student's stable friends is less than a preset third number threshold.

[0116] The student did not join any club within a tenth time period, wherein the tenth time period is, for example, a semester or a school year.

[0117] Join the club in the eleventh time period, and the ratio of the number of activities participated in the club to the total number of activities organized by the club is less than a preset third ratio threshold. The eleventh time period is, for example, a semester, a school year, etc. The preset third ratio threshold is, for example, 0.3, 0.4, etc.

[0118] In the twelfth time period, the number of the target student's stable friends is less than the preset third number threshold. The twelfth time period is, for example, one month, two months, etc. The preset third number threshold is, for example, 10, 20, etc.

[0119] The above rules are respectively used as security events corresponding to social data. That is, the second data content specified in security event 10 is that the student has not joined a club in the tenth time period; the second data content specified in security event 11 is that the student has joined a club in the eleventh time period, and the ratio of the number of activities participated in the club to the total number of activities organized by the club is less than the preset third ratio threshold; the second data content specified in security event 12 is that the number of stable friends of the target student in the twelfth time period is less than the preset third number threshold.

[0120] Preferably, the social data includes the above three security events at the same time, and the number of times the social data triggers each of the above three security events in a historical time period is subsequently counted, thereby improving the accuracy of student safety assessment.

[0121] Figure 2 The schematic diagram of the process of determining the stable friends of the target student provided for this application includes the following steps:

[0122] S201: for each consumption of the target student in the twelfth time period, determining a time window corresponding to the consumption, determining each candidate student who consumes in the time window, and setting the number of occurrences of each candidate student to 1;

[0123] S202: For each candidate student that appears in the twelfth time period, the number of appearances of the candidate student is accumulated to obtain a total number of appearances; if the total number of appearances is greater than a preset third number threshold, the candidate student is determined as a stable friend of the target student.

[0124] In this application, the target student's stable friends are determined based on the target student's consumption data. Specifically, the time window corresponding to each consumption of the target student is determined, and then each candidate student who consumes within the time window is determined, and the number of occurrences of each candidate student is set to 1. Then the total number of occurrences of each candidate student is counted, and the candidate students whose total number of occurrences is greater than the preset third number threshold are determined as stable friends, thereby improving the accuracy of determining stable friends.

[0125] In an optional implementation, if the various types of behavior data include Internet access data, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0126] The online time during the thirteenth time period exceeds the preset online time period;

[0127] Visiting a preset blacklist website within the fourteenth time period;

[0128] The online comments published during the fifteenth time period contain preset blacklist words.

[0129] The online time in the thirteenth time period exceeds the preset online time period. The thirteenth time period is, for example, one week, two weeks, one month, etc. The preset online time period is, for example, 50 hours, 80 hours, etc. The selection of the preset online time period is related to the length of the thirteenth time period.

[0130] The preset blacklist website is accessed within a fourteenth time period, where the fourteenth time period is, for example, one day, one week, two weeks, etc. The preset blacklist website is, for example, a website that has security problems after security detection.

[0131] The online speech published in the fifteenth time period includes preset blacklist words. The fifteenth time period is, for example, one day, one week, two weeks, etc. The preset blacklist words are, for example, illegal words, uncivilized words, etc.

[0132] The above rules are respectively used as security events corresponding to online data. That is, the second data content specified in security event 13 is that the online time in the thirteenth time period exceeds the preset online time period; the second data content specified in security event 14 is that the preset blacklist website is visited in the fourteenth time period; the second data content specified in security event 15 is that the online speech in the fifteenth time period contains the preset blacklist words.

[0133] Preferably, the Internet access data includes the above three security events at the same time, and the number of times the Internet access data triggers each of the above three security events within a historical time period is subsequently counted, thereby improving the accuracy of student safety assessment.

[0134] In an optional implementation, if the various types of behavior data include entry and exit data of various places in the school, the second data content specified in the security event corresponding to the category includes at least one of the following:

[0135] There is no attendance record of entering or leaving any place during the sixteenth time period; the places include at least one of a library, dormitory, restaurant and classroom;

[0136] Entering a preset danger zone during the seventeenth sub-time period.

[0137] There is no attendance record of entering and leaving each place in the sixteenth time period. The sixteenth time period is, for example, one day, two days, one week, etc.

[0138] Entering a preset danger zone within a seventeenth sub-time period. The seventeenth sub-time period may be, for example, one day, two days, or one week.

[0139] Figure 3 The schematic diagram of the process for determining the safety assessment results of the target students provided for this application includes the following steps:

[0140] S301: For each security event, determine a security assessment score of the security event according to the number of times the security event is triggered;

[0141] S302: Determine a total security assessment score based on the security assessment scores and corresponding weight values ​​of each security event; determine a security assessment result of the target student based on the total security assessment score; the security assessment result includes one of a major security assessment risk, a potential security assessment risk, a general security assessment risk, and no security assessment risk.

[0142] In this application, for each security event, the security assessment score of the security event is determined according to the number of times the security event is triggered. Then, a corresponding weight value is configured for each security event. Different weight values ​​can be set according to the importance of each security event. The weight value corresponding to a security event with a greater degree of importance is larger, and the weight value corresponding to a security event with a smaller degree of importance is smaller. Then, based on the security assessment score and the corresponding weight value of each security event, the total security assessment score is determined; and the security assessment result of the target student is determined based on the total security assessment score. Thereby, the accuracy of determining the security assessment result of the target student is improved.

[0143] In an optional implementation, if the various types of behavior data include online data, the second data content specified in the security event corresponding to the category includes the presence of preset blacklist words in online speeches published within the fifteenth time period, Figure 4 A schematic diagram of a process for determining a security assessment score of a security event according to the number of times a security event is triggered provided in this application, the process comprising the following steps:

[0144] S401: Determine a first ratio of the number of speeches containing blacklist words to the total number of speeches made by the target student in the fifteenth time period;

[0145] S402: Determine a second ratio of the number of blacklist words contained in the online speech to the total number of words in the preset blacklist word list;

[0146] S403: Determine a third ratio of the duration of the speech containing the blacklist vocabulary to the duration of the fifteenth time period;

[0147] S404: Determine a security assessment score of the security event according to the sum of the first ratio, the second ratio and the third ratio.

[0148] In this application, it is considered that the number of speeches containing blacklist words, the number of blacklist words contained in online speeches, and the length of time of speeches containing blacklist words by the target students will all reflect the safety level of the target students. Therefore, this application determines the first ratio of the number of speeches containing blacklist words to the total number of speeches, the second ratio of the number of blacklist words contained in online speeches to the total number of words in the preset blacklist vocabulary list; and the third ratio of the length of time of speeches containing blacklist words to the length of time of the fifteenth time period. Then, based on the sum of the first ratio, the second ratio, and the third ratio, the security assessment score of the security incident of containing preset blacklist words in online speeches is determined. Thereby, the accuracy of determining the security assessment score of the security incident can be improved.

[0149] Figure 5 A detailed flow chart of the student safety assessment provided for this application includes the following steps:

[0150] S501: According to the time period specified in the security event corresponding to each type of behavior data, the behavior data of the target student within the time period is obtained; the behavior data includes at least one of consumption data, academic data, social data, Internet access data, and entry and exit data of various places in the school;

[0151] S502: For each type of behavior data, if the first data content of the behavior data of the category matches the second data content specified in the security event corresponding to the category, determining that the security event is triggered;

[0152] S503: For each of the security events, determine a security assessment score of the security event according to the number of times the security event is triggered;

[0153] S504: Determine a total security assessment score based on the security assessment scores and corresponding weight values ​​of each security event; determine a security assessment result of the target student based on the total security assessment score; the security assessment result includes one of a major security assessment risk, a potential security assessment risk, a general security assessment risk, and no security assessment risk.

[0154] In addition, the electronic device performs a student safety assessment on each student, and after determining the safety assessment result, it can generate display content of the safety assessment result, and display the display content of the safety assessment result in the student management system.

[0155] Figure 6 Another detailed flow chart of the student safety assessment provided for this application includes the following steps:

[0156] S601: According to the time period specified in the security event corresponding to each type of behavior data, the behavior data of the target student within the time period is obtained; the behavior data includes at least one of consumption data, academic data, social data, Internet access data, and entry and exit data of various places in the school;

[0157] S602: For each type of behavior data, if the first data content of the behavior data of the category matches the second data content specified in the security event corresponding to the category, determine that the security event is triggered;

[0158] S603: Determine a security assessment result of the target student according to the number of times each security event is triggered by each type of behavior data of the target student in a historical time period;

[0159] S604: Generate display content of the security assessment result, and display the display content of the security assessment result in the student management system.

[0160] The security assessment results displayed include information such as student name, student class, student phone number, and student security assessment results.

[0161] Figure 7 A schematic diagram of the display interface for the security assessment results provided in this application, such as Figure 7 As shown, the display interface displays a list of students, and each student displays information such as student name, class, phone number, student security assessment result, and number of triggered security events. For example, student 31, class is International Economics and Trade, International Trade Class 2, phone number is 13000000000, security assessment result is potential risk, and there are 8 security prediction analyses. That is, the number of triggered security events is 8. Different security assessment results can be displayed in different colors, such as major risks are displayed in dark red, potential risks are displayed in blue, and general risks are displayed in yellow.

[0162] The present invention relates to the field of big data technology. By integrating and analyzing multi-dimensional data such as students' entry and exit of various places, consumption, academics, social interaction, and Internet access, a student safety warning level model is formed to help faculty and staff understand the safety of students. Compared with the traditional single-dimensional safety assessment method, this application integrates multi-dimensional data such as students' entry and exit of various places on campus, consumption, academics, social interaction, and Internet access, and can automatically learn and adapt to changes in students' data in various dimensions, thereby improving the accuracy and real-time performance of the student safety warning level algorithm. The student's safety warning level can be calculated through more comprehensive dimensions, making the result more accurate.

[0163] The student safety assessment process provided by this application mainly consists of the following modules:

[0164] 1. Data collection module: Through the relevant technologies of big data, collect data of various dimensions of students in colleges and universities, and convert the data into standard data for calculating the student safety warning level.

[0165] 2. Data analysis module: Combine standard data such as entry and exit of various places, consumption, academics, social interaction, and Internet access with relevant machine learning algorithms to form a student safety warning level model, and classify students who generate warnings into major risk students, general risk students, and potential risk students.

[0166] 3. Message notification module: Push the predicted student information with safety warning level to the counselor for follow-up processing.

[0167] This application uses big data related technologies to connect students' entry and exit, consumption, academic, social, and Internet data to the big data platform, and manage them in the data warehouse to provide a data basis for subsequent data analysis.

[0168] The entry and exit data of various places include the access control data of entrances and exits, libraries, dormitories, restaurants, etc. Consumption data includes the consumption data of the restaurant's one-card pass, etc. Academic data includes students' credits, GPA, target credits, failed courses, make-up exams, etc. Social data includes participation in club activities, friendships, etc., relying on one-card pass data, access control data, etc. Internet data includes Internet time, visited websites, speech content, etc.

[0169] We conduct a detailed analysis of the five security warning dimensions of entry and exit, consumption, study, social interaction, and Internet access, and define corresponding warning indicators. The details are as follows:

[0170] 1. Early warning of entry and exit data of each venue.

[0171] Late return: Failure to return to the dormitory within the time specified by the school.

[0172] Staying out overnight: No attendance record during the time period specified by the school.

[0173] No leaving / no returning: No attendance record of entering or leaving the dormitory within 24 hours.

[0174] High frequency of occurrence in dangerous areas: The number of occurrences in the dangerous areas defined by the school is greater than the threshold set by the school.

[0175] Suspected of loss of contact: Within 48 hours, there was no data on the student's entrance, exit, library, dormitory, restaurant, Internet access, etc.

[0176] Based on the total number of times each warning indicator appears during this semester, the data is normalized for the number of times each warning indicator appears for each student, and the total behavioral warning score for each student is calculated.

[0177] Student A’s total score = a(A)+b(A)+c(A)+d(A)+e(A).

[0178] a(A) is the late return warning score, b(A) is the overnight stay-out warning score, c(A) is the no-go / no-return warning score, d(A) is the high-frequency appearance warning score in dangerous areas, and e(A) is the suspected loss of contact warning score.

[0179] The top 20% of the students are given 8 points, the 20%-40% are given 4 points, the 40%-80% are given 2 points, and the bottom 20% are given 1 point. The behavior warning score of student A is recorded as Behavior_score(A)

[0180] 2. Consumption data warning.

[0181] Low consumption: Based on the distribution of the average monthly consumption amount of students, determine one or more thresholds to distinguish low consumption amounts. For example, the lower limit (close to 300 yuan) in the range of 300-800 yuan can be used as the initial judgment standard for low consumption.

[0182] Calculate the difference between the average consumption amount of low-consumption student A and 300, normalize the calculation result, record it as ce(A), calculate the ratio of the number of low consumption times of student A to the total number of consumption times as the frequency factor, record it as cs(A).

[0183] Student A’s low consumption score f(A)=ce(A)*cs(A).

[0184] Low-frequency consumption: Students whose monthly consumption records are less than the set number of times (for example, set to 15 times), or who had breakfast less than the set number of times last week (for example, set to 3 times). The normalized low-frequency consumption times of student A are recorded as dpxf(A).

[0185] Three consecutive days without consumption: There is no consumption record for 3 consecutive days on the card, excluding weekends and holidays. The normalized number of consecutive days without consumption for student A is recorded as lxstwxf(A).

[0186] A sudden increase in consumption: The average consumption amount of students in the past 7 days has increased by a percentage compared to the average consumption amount in the past 7 days. For example, the consumption amount has increased by more than 50% compared with the previous time period.

[0187] Calculate the proportion of each student's consumption surge, normalize the calculation result, record it as zzbl(A), calculate the ratio of the number of consumption surges of student A to the total number of consumption as the frequency factor, record it as zzcs(A).

[0188] The consumption surge score of student A g(A)=zzbl(A)*zzcs(A).

[0189] A sudden drop in consumption: The student's average consumption amount in the past 7 days has dropped by a percentage compared to the average consumption amount in the past 7 days. For example, the consumption amount has dropped by more than 50% compared with the previous time period.

[0190] Calculate the proportion of each student's consumption reduction, normalize the calculation result, record it as zjbl(A), calculate the ratio of the number of consumption reductions of student A to the total number of consumption as the frequency factor, record it as zjcs(A).

[0191] The consumption reduction score of student A h(A)=zjbl(A)*zjcs(A).

[0192] Student A’s total score = f(A)+dpxf(A)+lxstwxf(A)+g(A)+h(A).

[0193] The top 20% are given 8 points, the 20%-40% are given 4 points, the 40%-80% are given 2 points, and the bottom 20% are given 1 point. The consumption warning score of student A is recorded as Consume_score(A).

[0194] 3. Academic data warning.

[0195] Red academic warning: The number of failed courses in all courses taken in a semester (excluding public elective courses) is ≥5 after re-examination; or the credits taken in the academic year do not reach 1 / 3 of the required credits; or the cumulative number of failed courses since admission is ≥6.

[0196] Orange academic warning: The cumulative number of failed courses since enrollment is ≥6; or the credits earned in the academic year do not reach 1 / 2 of the required credits; or the cumulative number of failed courses since enrollment is ≥5.

[0197] Yellow academic warning: After retaking the supplementary examinations for all courses taken in a semester (excluding public elective courses), the student still has ≥3 failed courses; or the credits taken in the academic year do not reach 2 / 3 of the required credits; or the cumulative number of failed courses since admission is ≥4.

[0198] General academic warning: Students who have significantly declined have dropped more than 10 places in the class ranking; or have missed more than 4 classes in the past week.

[0199] A red warning is recorded as 8 points, an orange warning is recorded as 4 points, a yellow warning is recorded as 2 points, and a general academic warning is recorded as 1 point. The academic warning score of student A is recorded as Study_score(A).

[0200] 4. Social data warning.

[0201] Club participation warning: The student has not participated in any clubs this semester, or among the clubs he has joined, the number of activities he has participated in is less than the set value of the total number of activities organized by the club, such as 1 / 3. For example, student A has participated in 2 clubs this semester. The club participation factor is recorded as stcys(A) = the number of clubs participated in>0?0:1. One club organized 3 activities, and the student participated in 2 times. Another club organized 5 activities, and the student participated in 1 time. The inactive factor bhyyz(A) = the number of clubs whose participation activities do not meet the threshold / the total number of club activities.

[0202] The club participation warning score of student A is stcy(A)=stcys(A)+bhyyz(A).

[0203] Social travel warning: In places where students often go, such as libraries, dormitories, and restaurants, excluding classrooms, access control data is used to calculate whether the student has a stable group of friends, and a stable friend score is formed. For example, after collecting card swiping records and excluding card swiping records during class time, the time window is set to 1 minute, and all students who swipe their cards in the time window before and after student A swipes their cards are identified. The number of students who appear repeatedly before and after student A swipes their cards this semester is counted, and the number of students whose repeated appearances exceed 1 / 3 of the total number of student A swipes. The more repeated students there are, the more stable friends there are, and the lower the warning score is. Therefore, the inverse is taken, recorded as wdhy(A). After calculating the stable friend scores of all students, the data is normalized to obtain the social appearance score of student A, recorded as sjcx(A).

[0204] The total score of student A = stcy(A)+sjcx(A).

[0205] The top 20% are given 8 points, the 20%-40% are given 4 points, the 40%-80% are given 2 points, and the bottom 20% are given 1 point. The social warning score of student A is recorded as Social_score(A).

[0206] 5. Online data warning.

[0207] Abnormal Internet time: The daily Internet time exceeds 8 hours for 7 consecutive days or the Internet time in the early morning (after 0:00) exceeds 4 hours for 7 consecutive days. This semester, the number of times student A has this warning is normalized and the result is recorded as swsjyc(A).

[0208] Unsafe website visits: Visits to the list of unsafe websites defined by the school. This semester, the number of times student A received this warning is normalized and recorded as baqwzfw(A).

[0209] Online speech blacklist: Students’ online speeches cover words on the school’s blacklist. The warning score is calculated based on the number of speeches and the number of speeches with blacklist words. For example, student A has 200 speeches this semester, recorded as zfy(A), covering 20 words on the blacklist, the number of coverage is recorded as fg(A), the total number of words on the blacklist is recorded as total, 50 speeches involve blacklist words, recorded as fy(A), the total number of speech days is recorded as zts(A), and the number of days containing blacklist words is recorded as ts(A).

[0210] Student A’s online speech blacklist score = (fy(A) / zfy(A))*(fg(A) / total)*(ts(A) / zts(A)).

[0211] After calculating the online speech blacklist scores of all students involved, the data is normalized and the online speech blacklist score of student A is recorded as wsfyhmd(A).

[0212] Student A’s total score = swsjyc(A)+baqwzfw(A)+wsfyhmd(A).

[0213] The top 20% of the students get 8 points, the 20%-40% get 4 points, the 40%-80% get 2 points, and the bottom 20% get 1 point. The consumption warning score of student A is recorded as Network_score(A).

[0214] 6. Calculate the student safety warning level.

[0215] After obtaining the warning scores of each student in each warning dimension, students with scores of 0 are first eliminated as risk-free students.

[0216] The overall score of student A is:

[0217] Score(A)=α1*Behavior_score(A)+α2*Consume_score(A)+α3*Study_score(A)+α4*Social_score(A)+α5*Network_score(A).

[0218] Among them, α1, α2, α3, α4, and α5 are the weights of different warning dimensions.

[0219] Students whose total scores are in the top 20% are at significant risk, those in the bottom 20% are at potential risk, and the remaining students are at average risk.

[0220] 7. Push the results to the counselor.

[0221] The students at each safety warning level predicted above will be pushed to the counselors, who will follow up, verify, and handle them, and intervene in advance. At the same time, according to the counselors' confirmation or adjustment of the safety warning level results, our prediction algorithm will be optimized to make the calculation results more accurate.

[0222] Figure 8 The student safety assessment system architecture diagram provided for this application is as follows: Figure 8 As shown in the figure, data is collected through the academic affairs system, one-card system, access control system, library system, dormitory management system, etc. Student warning indicators include entry and exit warning indicators, consumption warning indicators, academic warning indicators, social warning indicators, and Internet warning indicators. Entry and exit warning indicators include late return, overnight stay, no exit / no return, high frequency of dangerous areas, and suspected loss of contact. Consumption warning indicators include low consumption, low frequency consumption, no consumption for three consecutive days, sudden increase in consumption, and sudden decrease in consumption. Academic warning indicators include red academic warning, orange academic warning, yellow academic warning, and general academic warning. Social warning indicators include warning of club participation and social travel warning. Internet warning indicators include abnormal Internet time, unsafe website access, and online speech blacklist. Then determine the warning level of student safety assessment, including major risk students, general risk students, and potential risk students.

[0223] Fig. 9 This is a schematic diagram of the structure of the student safety assessment device provided in this application, and the device includes:

[0224] The acquisition module 91 is used to acquire the behavior data of the target student within the time period specified in the security event corresponding to each type of behavior data; the behavior data includes at least one of consumption data, academic data, social data, Internet access data, and entry and exit data of various places in the school;

[0225] A determination module 92, for determining, for each type of behavior data, that the security event is triggered if the first data content of the behavior data of the category matches the second data content specified in the security event corresponding to the category;

[0226] The evaluation module 93 is used to determine the security evaluation result of the target student according to the number of times each security event is triggered by each type of behavior data of the target student in a historical time period.

[0227] The evaluation module 93 is specifically used to determine the security evaluation score of each security event according to the number of times the security event is triggered;

[0228] Determine the total security assessment score based on the security assessment scores of each security incident and the corresponding weight values; determine the security assessment result of the target student based on the total security assessment score; the security assessment result includes one of the following: major security assessment risk, potential security assessment risk, general security assessment risk and no security assessment risk.

[0229] The evaluation module 93 is specifically used to determine a first ratio of the number of speeches containing blacklist words to the total number of speeches made by the target student within the fifteenth time period; determine a second ratio of the number of blacklist words contained in online speeches to the total number of words in a preset blacklist vocabulary list; determine a third ratio of the time length of speeches containing blacklist words to the time length of the fifteenth time period; and determine the security assessment score of the security incident based on the sum of the first ratio, the second ratio and the third ratio.

[0230] The present application also provides an electronic device, such as Fig.10 As shown, it includes: a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114;

[0231] The memory 113 stores a computer program, and when the program is executed by the processor 111, the processor 111 executes any one of the above method steps.

[0232] The communication bus mentioned in the above electronic device can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0233] The communication interface 112 is used for communication between the above electronic device and other devices.

[0234] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0235] The above-mentioned processor can be a general-purpose processor, including a central processing unit, a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc.

[0236] The present application also provides a computer storage readable storage medium, wherein the computer readable storage medium stores a computer program executable by an electronic device, and when the program runs on the electronic device, the electronic device implements any of the above method steps when executing.

[0237] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0238] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A student safety assessment method, characterized in that: The method comprises: According to the time period specified in the security incident corresponding to each type of behavior data, the behavior data of the target student within the time period is obtained; the behavior data includes at least one of consumption data, academic data, social data, Internet access data, and entry and exit data of various places in the school; For each type of behavior data, if the first data content of the behavior data of the category matches the second data content specified in the security event corresponding to the category, it is determined that the security event is triggered; The security assessment result of the target student is determined according to the number of times each security event is triggered by various behavioral data of the target student in a historical time period.

2. The method according to claim 1, characterized in that If the various types of behavior data include consumption data, the second data content specified in the security event corresponding to the category includes at least one of the following: The total consumption amount in the first time period is less than the preset consumption threshold; The number of consumptions in the second time period is less than the preset first number threshold; The average consumption amount in the third time period increases by a ratio greater than a preset first ratio threshold value compared with the average consumption amount in the previous third time period; The average consumption amount in the fourth time period decreases by a ratio greater than a preset second ratio threshold value compared with the average consumption amount in the previous fourth time period.

3. The method according to claim 1, characterized in that If the various types of behavior data include academic data, the second data content specified in the security event corresponding to the category includes at least one of the following: The number of failed courses in the courses taken during the fifth time period is greater than a preset first quantity threshold; The number of failed courses after reexamination in the sixth time period is greater than a preset second quantity threshold; The credits earned in the seventh time period are less than the preset credit threshold; The number of absences during the eighth time period is greater than a preset second number threshold; During the ninth time period, the performance ranking declines to a level greater than the preset ranking threshold.

4. The method according to claim 1, characterized in that If the various types of behavior data include social data, the second data content specified in the security event corresponding to the category includes at least one of the following: Not joining a club during the tenth time period; Joining a community during the eleventh time period, and the ratio of the number of activities participated in the community to the total number of activities organized by the community is less than the preset third ratio threshold; In the twelfth time period, the number of the target student's stable friends is less than a preset third number threshold.

5. The method according to claim 4, characterized in that The process of determining the stable friends of the target student includes: For each consumption of the target student in the twelfth time period, determine the time window corresponding to the consumption, determine each candidate student who consumes in the time window, and set the number of occurrences of each candidate student to 1; For each candidate student that appears in the twelfth time period, the number of appearances of the candidate student is accumulated to obtain a total number of appearances; if the total number of appearances is greater than a preset third number threshold, the candidate student is determined as a stable friend of the target student.

6. The method according to claim 1, characterized in that If the various types of behavior data include online data, the second data content specified in the security event corresponding to the category includes at least one of the following: The online time during the thirteenth time period exceeds the preset online time period; Visiting a preset blacklist website within the fourteenth time period; The online comments published during the fifteenth time period contain preset blacklist words.

7. The method according to claim 1, characterized in that If the various types of behavior data include entry and exit data of various places in the school, the second data content specified in the security event corresponding to the category includes at least one of the following: There is no attendance record of entering or leaving any place during the sixteenth time period; the places include at least one of a library, dormitory, restaurant and classroom; Entering a preset danger zone during the seventeenth sub-time period.

8. The method according to claim 1, characterized in that The process for determining the safety assessment results for the target students includes: For each of the security events, determine a security assessment score for the security event according to the number of times the security event is triggered; Determine the total security assessment score based on the security assessment scores of each security incident and the corresponding weight values; determine the security assessment result of the target student based on the total security assessment score; the security assessment result includes one of the following: major security assessment risk, potential security assessment risk, general security assessment risk and no security assessment risk.

9. The method according to claim 8, characterized in that If the various types of behavior data include online data, the second data content specified in the security event corresponding to the category includes a preset blacklist word included in the online speech published within the fifteenth time period, and the security assessment score of the security event is determined according to the number of times the security event is triggered, including: Determine a first ratio of the number of speeches containing blacklist words to the total number of speeches made by the target student in the fifteenth time period; determine a second ratio of the number of blacklist words contained in online speeches to the total number of words in a preset blacklist vocabulary list; determine a third ratio of the time length of speeches containing blacklist words to the time length of the fifteenth time period; and determine a security assessment score for the security incident based on the sum of the first ratio, the second ratio and the third ratio.

10. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, for implementing the method according to any one of claims 1 to 9 when executing a program stored in a memory.

Images