Anti-fraud propaganda system and method and electronic equipment

Abstract

The invention relates to the technical field of anti-fraud propaganda, and discloses an anti-fraud propaganda system and method and electronic equipment, and the system comprises a user data collection end which is used for collecting user information data; the database is used for counting historical fraud cases of all jurisdictions; the propaganda information matching unit is used for performing matching analysis on the information data of the user and the historical fraud type of the current area, and matching corresponding propaganda information according to an analysis result; the anti-fraud propaganda execution module is used for executing corresponding propaganda information according to a preset propaganda strategy; and the early warning center is used for carrying out early warning analysis according to the information data of the user and carrying out anti-fraud propaganda according to an early warning analysis result. According to the method and the device, adaptive selection can be performed according to information such as states of the users and occurrence frequencies of different cases, and then anti-fraud propaganda can be performed in a targeted manner, so that the coping ability of the users is improved when the users face fraud risks, and the anti-fraud propaganda effect is improved.

Description

Technical Field

[0001] The present application relates to the technical field of anti-fraud publicity, and in particular to a system, method and electronic equipment for anti-fraud publicity. Background Art

[0002] The rapid development of mobile smart devices and the Internet has greatly facilitated people's daily lives and work. However, at the same time, the Internet has also become a channel for criminals to commit fraud, especially for hotels. Scammers will use payment and credit card fraud, fake transactions, phishing websites, Wi-Fi phishing attacks, and fake delivery services to defraud users inadvertently. Therefore, fraud awareness is needed to raise people's awareness of anti-fraud measures and thus reduce the occurrence of fraud cases.

[0003] In the existing hotel anti-fraud publicity, fraud cases are played in public places to let users know more about fraud cases, thereby achieving a certain anti-fraud effect. Slogans are also set up, notifications are sent to users, etc. to improve consumers' safety awareness, thereby reducing the risk of consumers being defrauded.

[0004] Although the existing publicity methods can play an anti-fraud publicity role, in the specific application process, the amount of information input to consumers is limited, that is, consumers know fewer anti-fraud cases within a limited time, so the publicity effect on consumers is not good. When consumers encounter a type of fraud they are not familiar with, they still cannot quickly determine whether they are facing the risk of fraud. Therefore, how to provide corresponding fraud cases according to different consumers and thereby improve the anti-fraud publicity effect is the fundamental problem to be solved by the present invention. Summary of the Invention

[0005] In order to improve the effectiveness of anti-fraud publicity, the present application provides a system, method and electronic equipment for anti-fraud publicity.

[0006] In a first aspect, the present application provides a system, method, and electronic device for anti-fraud publicity, which employ the following technical solutions:

[0007] An anti-fraud publicity system, comprising:

[0008] User data collection terminal, used to collect user information data;

[0009] A database that counts historical fraud cases in all jurisdictions;

[0010] A promotional information matching unit is used to match and analyze user information data and historical fraud types in the current area, and match corresponding promotional information based on the analysis results;

[0011] The anti-fraud publicity execution module is used to execute corresponding publicity information according to the preset publicity strategy;

[0012] The early warning center is used to conduct early warning analysis based on user information data and carry out anti-fraud publicity based on the early warning analysis results.

[0013] By adopting the above-mentioned technical solution, adaptive selection can be made according to information such as the user's status and the frequency of occurrence of different cases, and targeted anti-fraud publicity can be carried out, so that users can improve their coping capabilities when facing the risk of fraud, thereby improving the anti-fraud publicity effect; in addition, this embodiment also monitors and analyzes the user's network usage risks through the early warning center, and can provide timely reminders when the user is at risk of network fraud, thereby reducing the occurrence of fraud cases.

[0014] Optionally, the process of performing matching analysis includes:

[0015] Classify historical fraud cases in the database by fraud type, obtain a trend chart of the number of fraud types under each category, and determine the risk value of the fraud type based on the trend chart;

[0016] Obtain user information data of victims of corresponding fraud types under each category, perform comparison based on the user information data, and obtain the filtering value;

[0017] Obtain matching fraud types based on the risk value and screening value, and obtain corresponding promotional information based on the matching fraud types.

[0018] By adopting the above technical solution, on the one hand, by obtaining a quantity change trend chart of each type of fraud case after classification, the occurrence risk value can be determined according to the change trend chart, and the occurrence risk value can reflect the probability of occurrence of the current fraud type. Therefore, the occurrence risk value is used as one of the factors for matching the fraud type, thereby improving the adaptability of the fraud type to the user. On the other hand, by obtaining the user information data of the victims of the corresponding fraud type under each category, the user information data is compared to obtain the screening value. Therefore, the screening value can reflect the adaptability of the objects of different fraud types to the user. Therefore, the screening value is used as one of the factors for matching the fraud type, which can make the promotional content better adapted to the user. Then, the matching fraud type is obtained through the occurrence risk value and the screening value, and the corresponding promotional information is obtained according to the matching fraud type. Then, a comprehensive analysis is conducted based on the probability of occurrence of the current fraud type and the user's adaptability to select the most suitable promotional content for the user, thereby improving the anti-fraud promotion effect.

[0019] Optionally, the calculation process of the risk value of each fraud type includes:

[0020] Obtain historical fraud cases within a preset period, and divide the preset period into n periods evenly;

[0021] By formula Calculate the risk value of the jth type of fraud ;

[0022] Among them, n is the number of time periods divided into average periods of historical time, i∈[1,n], is the number of occurrences of the jth fraud type in the i-th period in all jurisdictions, is the influence coefficient of the i-th period, The value increases relative to i, y(x) is the judgment function, when x=0, y(x)=0, otherwise, y(x)=1; is the number of occurrences of the jth type of fraud in the i-th period in the current jurisdiction, K is the adjustment coefficient, and K>1.2;

[0023] The process of obtaining the screening value includes:

[0024] By formula Calculate the filter value of the current user and the jth fraud type ;

[0025] Among them, H is the number of types of user information data, k∈[1,H], is the corresponding value of the kth type of user information data of the current user, is the mean value of the kth user information data in the jth fraud type, is the unit value corresponding to the k-th user information data, is the influence coefficient of the k-th user information data;

[0026] By risk value and filter values Get the matching fraud type.

[0027] By adopting the above technical solution, it is possible to ensure that historical data from all jurisdictions are utilized, improve the diversity of samples, and at the same time increase the weight of the current jurisdiction, ensuring the adaptability of the obtained results to the current jurisdiction. By calculating the risk value obtained, the adaptability of the fraud type to the user can be improved.

[0028] Optionally, the process of obtaining matching fraud types includes:

[0029] By formula Calculate the matching value ;

[0030] Select matching value The fraud type corresponding to the maximum value is obtained as the result.

[0031] By adopting the above technical solution, it is possible to conduct a comprehensive analysis based on the probability of occurrence of the current fraud type and the user's adaptation situation, select the most suitable promotional content for the user, and thus improve the anti-fraud publicity effect.

[0032] Optionally, the early warning analysis process includes:

[0033] Obtain access link data and access software data from collected user information data;

[0034] Extract the access links and the corresponding number and duration in the access link data;

[0035] Extract the access software and the corresponding number and duration from the access software data;

[0036] Conduct early warning analysis based on the number of access links and their corresponding duration, and the number of access software and their corresponding duration.

[0037] By adopting the above technical solution, early warning analysis is performed based on the access links and the corresponding number and duration, and the access software and the corresponding number and duration; by obtaining and analyzing the access link data and access software data in the user information data, the user's network fraud risk can be judged, and then the user can be reminded in time to reduce the risk of fraud.

[0038] Optionally, the early warning analysis process includes:

[0039] Monitor the risk values of obtaining access links and accessing software respectively;

[0040] By formula

[0041]

[0042] Calculate the risk value W;

[0043] Where D1 is the number of access links, v∈[1, D1], D2 is the number of access software, u∈[1, D2], is the warning value of the vth access link, is the risk value of the vth access link, is the number of visits to the vth visit link, is the average access time of the vth access link, is the maximum access duration of the vth access link, is the preset adjustment coefficient, T0 is the unit duration, is the warning value of the u-th access software, is the risk value of the u-th access software, is the number of visits to the u-th access software, is the average access time of the u-th access software, is the maximum access duration of the u-th access software;

[0044] Compare the risk value W with the preset threshold W1. When W≥W1, conduct anti-fraud publicity.

[0045] By adopting the above technical solution, we can conduct an overall comprehensive analysis of multiple parameters such as the user's access content, access duration and number of visits, and then determine whether it is a security risk of network access. Security risks are often accompanied by fraudulent information. Therefore, through the above early warning analysis process, we can assist hotel managers in the anti-fraud process.

[0046] Optionally, the preset publicity strategy includes:

[0047] A promotional voice will automatically play when the user enters the room, an anti-fraud calendar will be displayed when the user scans to enter the mini program, and free mobile phone charging time can be obtained by viewing fraud cases.

[0048] By adopting the above technical solutions, users can be guided to learn more about fraud cases, thereby reducing their risk of being defrauded and improving their anti-fraud risk.

[0049] Secondly, this application provides an anti-fraud publicity method, which adopts the following technical solutions:

[0050] A method for anti-fraud publicity, the method using any one of the anti-fraud publicity systems described above, comprising:

[0051] Step 1: Collect user information data through the user data collection terminal;

[0052] Step 2: Collect historical fraud cases in all jurisdictions through the database;

[0053] Step 3: The promotional information matching unit performs a matching analysis on the user's information data and the historical fraud types in the current area, and matches the corresponding promotional information based on the analysis results;

[0054] Step 4: Execute the corresponding promotional information according to the preset promotional strategy through the anti-fraud promotion execution module;

[0055] Step 5: The early warning center conducts early warning analysis based on the user's information data and conducts anti-fraud publicity based on the results of the early warning analysis.

[0056] In a third aspect, the present application provides an electronic device for anti-fraud propaganda, which adopts the following technical solution:

[0057] An electronic device for anti-fraud publicity, wherein the electronic device stores a program of an anti-fraud publicity system as described above.

[0058] In summary, this application includes at least one of the following beneficial technical effects:

[0059] 1. It can make adaptive selections based on information such as the user's status and the frequency of occurrence of different cases, and then carry out targeted anti-fraud publicity, so that users can improve their coping capabilities when facing the risk of fraud, thereby improving the anti-fraud publicity effect; using the occurrence risk value as one of the factors for matching the fraud type, it can improve the adaptability of the fraud type to the user, and using the screening value as one of the factors for matching the fraud type, it can make the publicity content better adapted to the user, and then obtain the matching fraud type through the occurrence risk value and the screening value, and obtain the corresponding publicity information according to the matching fraud type, thereby improving the anti-fraud publicity effect.

[0060] 2. Through the calculation process of the occurrence risk value, it is possible to ensure that the historical data of all jurisdictions are utilized, improve the diversity of samples, and at the same time increase the weight of the current jurisdiction to ensure the adaptability of the obtained results to the current jurisdiction. The occurrence risk value obtained through calculation can further improve the adaptability of the fraud type to the user; through the calculation process of the screening value, it reflects the adaptability of the objects of different fraud types to the user, and then obtain the matching fraud type through the occurrence risk value and the screening value, obtain the corresponding publicity information according to the matching fraud type, and select the most suitable publicity content for the user, thereby improving the anti-fraud publicity effect.

[0061] 3. The present invention can conduct an overall comprehensive analysis of multiple parameters such as the user's access content, access duration, and number of visits through the risk value calculation process, and then determine whether the user's network access is a security risk. Security risks are often accompanied by fraudulent information. Therefore, through the above-mentioned early warning analysis process, the hotel management personnel can be assisted in the anti-fraud process. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a system logic block diagram of anti-fraud propaganda.

[0063] Figure 2 It is a flow chart of the methods and steps of anti-fraud publicity. DETAILED DESCRIPTION

[0064] Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings.

[0065] Throughout this specification, reference to the terms "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0066] This application embodiment discloses an anti-fraud propaganda system. Figure 1 , including a user data collection terminal, a database, a publicity information matching unit, an anti-fraud publicity execution module and an early warning center, wherein the user data collection terminal is used to collect user information data; the database stores historical fraud cases of all jurisdictions obtained by statistics; the publicity information matching unit is used to match and analyze the user's information data and the historical fraud types of the current area, and match the corresponding publicity information according to the analysis results; the anti-fraud publicity execution module is used to execute the corresponding publicity information according to the preset publicity strategy; the early warning center is used to perform early warning analysis based on the user's information data, and carry out anti-fraud publicity according to the early warning analysis results. Through the above technical solution, this embodiment collects user information data and selects corresponding cases as publicity information in the database through a matching analysis method, and then executes the corresponding publicity information according to the predicted publicity strategy. In this way, adaptive selection can be made according to information such as the user's status and the frequency of occurrence of different cases, and then targeted anti-fraud publicity can be carried out, so that users can improve their coping capabilities when facing the risk of fraud, thereby improving the anti-fraud publicity effect; in addition, this embodiment also monitors and analyzes the user's network usage risks through the early warning center, and can timely remind users when there is a risk of network fraud, thereby reducing the occurrence of fraud cases.

[0067] It should be noted here that the predictive publicity strategy in the above technical solution is a specific means of publicity and is not further limited here; user information data includes two aspects, one is the user's basic information, such as age information, income level information, etc., and the other is the user's relevant access data under the current network; in addition, the early warning center conducts anti-fraud publicity not through the anti-fraud publicity execution module, but directly reminds users manually.

[0068] In addition, this embodiment provides a process for matching analysis, including: classifying historical fraud cases in the database according to fraud types, obtaining a quantity change trend chart of the corresponding fraud type under each category, and determining its occurrence risk value based on the quantity change trend chart; obtaining user information data of victims of the corresponding fraud type under each category, comparing the user information data, and obtaining a screening value; obtaining a matching fraud type based on the occurrence risk value and the screening value, and obtaining corresponding promotional information based on the matching fraud type. Through the above process, on the one hand, by obtaining a quantity change trend chart of each fraud case type after classification, its occurrence risk value can be determined based on its change trend chart, and the occurrence risk value can reflect the probability of occurrence of the current fraud type, so according to the occurrence The risk value is used as one of the factors for matching fraud types, thereby improving the adaptability of fraud types to users. On the other hand, by obtaining user information data of victims of corresponding fraud types under each category, and comparing them according to the user information data, the filtering value is obtained. Therefore, the filtering value can reflect the adaptability of the objects of different fraud types to users. Therefore, using the filtering value as one of the factors for matching fraud types can make the promotional content better adapted to users, and then obtain the matching fraud type through the occurrence of risk value and filtering value, and obtain the corresponding promotional information according to the matching fraud type, and then comprehensively analyze the probability of occurrence of the current fraud type and the user's adaptability to select the most suitable promotional content for the user, thereby improving the anti-fraud promotion effect.

[0069] In one embodiment, a calculation process for the risk value of each fraud type is given, including: first, obtaining historical fraud cases in a preset period, and dividing the preset period into n periods on average; it should be noted that the selection of historical periods and the division of n periods are set by the system backend administrator and are not limited here. The formula Calculate the risk value of the jth type of fraud ; where n is the average number of time periods divided into historical periods, i∈[1,n], is the number of occurrences of the jth fraud type in the i-th period in all jurisdictions, is the influence coefficient of the i-th period, The value increases relative to i. It should be noted that the order of i from small to large is determined according to the time before and after. At the same time, the influence coefficient varies according to the interval between the divided time period and the current time point. The longer the interval, the smaller the corresponding influence coefficient. The specific value selection is set after fitting multiple groups of data in the big data. In addition, y(x) is a judgment function. When x=0, y(x)=0, and the time period is not considered. Otherwise, y(x)=1; is the number of occurrences of the jth type of fraud in the i-th period in the current jurisdiction, K is the adjustment coefficient, and K>1.2. The adjustment coefficient is used to adjust the priority weight of the current jurisdiction relative to the whole. Therefore, through the above calculation process, it can ensure that the historical data of all jurisdictions are utilized, improve the diversity of samples, and at the same time increase the weight of the current jurisdiction, ensure the adaptability of the obtained results to the current jurisdiction, and obtain the risk value through calculation, thereby improving the adaptability of the fraud type to the user.

[0070] In one embodiment, a process for obtaining a screening value is provided, including: Calculate the filter value of the current user and the jth fraud type ; Where H is the number of types of user information data, k∈[1,H], the value of this item is determined according to the type of data that can be obtained. User information data includes but is not limited to the user's age, income, etc. is the corresponding value of the kth type of user information data of the current user, is the mean value of the kth user information data in the jth fraud type, is the unit value corresponding to the kth type of user information data. This value is determined according to the type of user information data. For example, if the type of user information data is age, the unit value can be 1 years old. is the influence coefficient of the kth type of user information data. This influence coefficient is set according to the type of user information data and the corresponding experience data. and filter values Obtain matching fraud types through the above calculation process, and then use the screening value to reflect the adaptability of the targets of different fraud types and users. Therefore, using the screening value as one of the factors for obtaining matching fraud types can make the promotional content better adapted to users, and then obtain matching fraud types through the occurrence risk value and the screening value, obtain corresponding promotional information according to the matching fraud type, and conduct a comprehensive analysis based on the probability of occurrence of the current fraud type and the user's adaptability to select the most suitable promotional content for the user, thereby improving the anti-fraud promotion effect.

[0071] The process of matching fraud types includes: Calculate the matching value ;Select matching value The fraud type corresponding to the maximum value is obtained as the result, and then a comprehensive analysis can be conducted based on the probability of occurrence of the current fraud type and the user's adaptation situation to select the most suitable promotional content for the user, thereby improving the anti-fraud promotion effect.

[0072] In one embodiment, a warning analysis process is provided, including: obtaining access link data and access software data from collected user information data; extracting access links and corresponding times and durations from the access link data; extracting access software and corresponding times and durations from the access software data; performing warning analysis based on the access links and corresponding times and durations and the access software and corresponding times and durations; by obtaining and analyzing the access link data and access software data from the user information data, the user's network fraud risk can be judged, and the user can be reminded in a timely manner to reduce the risk of fraud.

[0073] It should be noted that the acquisition and analysis of access data is completed in the background and is encrypted, so the user's privacy will not be leaked.

[0074] The early warning analysis process includes: monitoring the risk values of obtaining access links and access software respectively;

[0075] By formula Calculate the risk value W;

[0076] Where D1 is the number of access links, v∈[1, D1], D2 is the number of access software, u∈[1, D2], is the warning value of the vth access link, is the risk value of the vth access link. This data is realized based on the link security evaluation technology in the existing technology. The risk value fluctuates in the range of 0-100. is the number of visits to the vth visit link, is the average access time of the vth access link, is the maximum access duration of the vth access link, It is a preset adjustment coefficient. This data is selected and set based on empirical data to adjust the influence weight of the maximum value relative to the mean. T0 is the unit duration. This parameter is a fixed value and is set based on the test data fitting. is the warning value of the u-th access software. The method of obtaining this parameter is the same as the risk value of the access link, which will not be detailed here. is the risk value of the u-th access software, is the number of visits to the u-th access software, is the average access time of the u-th access software, The maximum access time of the u-th access software is used, and the risk value W is compared with the preset threshold W1. When W≥W1, anti-fraud publicity is carried out. Therefore, through the above risk value calculation process, a comprehensive analysis of multiple parameters such as the user's access content, access time and number of visits can be conducted to determine whether it is a security risk of network access. Security risks are often accompanied by fraud information. Therefore, through the above early warning analysis process, the anti-fraud process of hotel managers can be assisted.

[0077] In one embodiment, the preset promotional strategy includes: automatically playing promotional voice after the user enters the room, presenting an anti-fraud calendar when the user scans to enter the mini program, and obtaining free mobile phone charging time by viewing fraud cases. Through the above scheme, users can be guided to learn more about fraud cases, thereby reducing their risk of being defrauded and increasing their risk of anti-fraud.

[0078] The present application also discloses a method for anti-fraud propaganda, which adopts any one of the anti-fraud propaganda systems described above. Figure 2 , including: Step 1, collecting user information data through the user data collection terminal; Step 2, counting historical fraud cases in all jurisdictions through the database; Step 3, matching and analyzing the user's information data and the historical fraud types in the current area through the publicity information matching unit, and matching the corresponding publicity information according to the analysis results; Step 4, executing the corresponding publicity information according to the preset publicity strategy through the anti-fraud publicity execution module; Step 5, conducting early warning analysis based on the user's information data through the early warning center, and conducting anti-fraud publicity based on the early warning analysis results. Through the above technical solution, it is possible to make adaptive choices based on information such as the user's status and the frequency of occurrence of different cases, and then conduct targeted anti-fraud publicity, so that users can improve their coping capabilities when facing the risk of fraud, thereby improving the effectiveness of anti-fraud publicity.

[0079] An embodiment of the present application also discloses an electronic device for anti-fraud publicity, in which a program of an anti-fraud publicity system as described above is stored.

[0080] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. An anti-fraud publicity system, characterized in that: include: User data collection terminal, used to collect user information data; A database that counts historical fraud cases in all jurisdictions; A promotional information matching unit is used to match and analyze user information data and historical fraud types in the current area, and match corresponding promotional information based on the analysis results; The anti-fraud publicity execution module is used to execute corresponding publicity information according to the preset publicity strategy; The early warning center is used to conduct early warning analysis based on user information data and carry out anti-fraud publicity based on the early warning analysis results; The process of performing matching analysis includes: Classify historical fraud cases in the database by fraud type, obtain a trend chart of the number of fraud types under each category, and determine the risk value of the fraud type based on the trend chart; Obtain user information data of victims of corresponding fraud types under each category, perform comparison based on the user information data, and obtain the filtering value; Obtain matching fraud types based on the risk value and screening value, and obtain corresponding promotional information based on the matching fraud types; The calculation process for the risk value of each fraud type includes: Obtain historical fraud cases within a preset period, and divide the preset period into n periods evenly; By formula Calculate the risk value of the jth type of fraud ; Among them, n is the number of time periods divided into average periods of historical time, i∈[1,n], is the number of occurrences of the jth fraud type in the i-th period in all jurisdictions, is the influence coefficient of the i-th period, The value increases relative to i, y(x) is the judgment function, when x=0, y(x)=0, otherwise, y(x)=1; is the number of occurrences of the jth type of fraud in the i-th period in the current jurisdiction, K is the adjustment coefficient, and K>1.2; The process of obtaining the screening value includes: By formula Calculate the filter value of the current user and the jth fraud type ; Among them, H is the number of types of user information data, k∈[1,H], is the corresponding value of the kth type of user information data of the current user, is the mean value of the kth user information data in the jth fraud type, is the unit value corresponding to the k-th user information data, is the influence coefficient of the k-th user information data; By risk value and filter values Get the matching fraud type.

2. The anti-fraud publicity system according to claim 1, characterized in that: The process of matching fraud types includes: By formula Calculate the matching value ; Select matching value The fraud type corresponding to the maximum value is obtained as the result.

3. The anti-fraud publicity system according to claim 1, characterized in that: The process of early warning analysis includes: Obtain access link data and access software data from collected user information data; Extract the access links and the corresponding number and duration in the access link data; Extract the access software and the corresponding number and duration from the access software data; Conduct early warning analysis based on the number of access links and their corresponding duration, and the number of access software and their corresponding duration.

4. The anti-fraud publicity system according to claim 3, characterized in that: The process of early warning analysis includes: Monitor the risk values of obtaining access links and accessing software respectively; By formula Calculate the risk value W; Where D1 is the number of access links, v∈[1, D1], D2 is the number of access software, u∈[1, D2], is the warning value of the vth access link, is the risk value of the vth access link, is the number of visits to the vth visit link, is the average access time of the vth access link, is the maximum access duration of the vth access link, is the preset adjustment coefficient, T0 is the unit duration, is the warning value of the u-th access software, is the risk value of the u-th access software, is the number of visits to the u-th access software, is the average access time of the u-th access software, is the maximum access duration of the u-th access software; Compare the risk value W with the preset threshold W1. When W≥W1, conduct anti-fraud publicity.

5. The anti-fraud publicity system according to claim 4, characterized in that: The preset publicity strategies include: A promotional voice will automatically play when the user enters the room, an anti-fraud calendar will be displayed when the user scans to enter the mini program, and free mobile phone charging time can be obtained by viewing fraud cases.

6. A method for anti-fraud publicity, characterized in that: The method adopts an anti-fraud publicity system according to any one of claims 1 to 5, comprising: Step 1: Collect user information data through the user data collection terminal; Step 2: Collect historical fraud cases in all jurisdictions through the database; Step 3: The promotional information matching unit performs a matching analysis on the user's information data and the historical fraud types in the current area, and matches the corresponding promotional information based on the analysis results; Step 4: Execute the corresponding promotional information according to the preset promotional strategy through the anti-fraud promotion execution module; Step 5: The early warning center conducts early warning analysis based on the user's information data and conducts anti-fraud publicity based on the results of the early warning analysis.

7. An electronic device for anti-fraud propaganda, characterized in that: The electronic device stores a program of an anti-fraud publicity system as described in any one of claims 1 to 5.

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