E-mail protection method and device

Abstract

The invention provides an email protection method and device, and relates to the technical field of emails, the email data of any email is acquired through a preset data collection system, and the reputation evaluation factor of a sender corresponding to the email is calculated based on the email data; calculating the weight of each reputation evaluation factor according to the contribution degree of each reputation evaluation factor to the junk mail; performing weighted summation on the weight of each reputation evaluation factor through a weighted scoring algorithm to obtain a reputation evaluation score of the sender; and when the reputation evaluation score is greater than or equal to a preset evaluation threshold value, receiving the E-mail of the sender, and filtering junk mails in the E-mail through a preset junk mail filtering method. Therefore, the reputation of the sender is evaluated by comprehensively considering the plurality of reputation evaluation factors calculated by the mail data, the accurate identification rate of the email sender can be improved, the false alarm rate and the missing report rate can be reduced, and the junk mail filtering effect is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of email, and in particular to an email protection method and device. Background Art

[0002] With the widespread use of email, spam has become a serious problem, bringing inconvenience and security risks to users. In the related technology, traditional spam filtering methods usually use rule filtering, blacklist and content analysis technologies, which only filter email content, and have problems such as high false positive rate and high false negative rate. Therefore, a more accurate and reliable spam filtering method is needed. Summary of the invention

[0003] The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

[0004] To this end, the first purpose of the present invention is to propose an email protection method, which evaluates the sender's reputation by comprehensively considering multiple reputation evaluation factors calculated by email data, thereby improving the accurate identification rate of email senders, reducing false alarm rates and missed alarm rates, and improving the effect of spam filtering.

[0005] A second object of the present invention is to provide an email protection device.

[0006] A third objective of the present invention is to provide an electronic device.

[0007] A fourth object of the present invention is to provide a non-transitory computer-readable storage medium storing computer instructions.

[0008] A fifth object of the present invention is to provide a computer program product.

[0009] To achieve the above object, a first embodiment of the present invention provides an email protection method, the method comprising:

[0010] Obtaining email data of any email through a preset data collection system, and calculating multiple reputation evaluation factors of the sender of the email based on the email data, wherein the reputation evaluation factors include the frequency of email sending by the sender within a preset time interval, user feedback data of the recipient reporting or marking spam emails, and the sender's historical behavior data;

[0011] Calculate the weight of each reputation evaluation factor according to the contribution of each reputation evaluation factor of the email to spam;

[0012] The weights of each reputation evaluation factor are weighted and summed by a weighted scoring algorithm to obtain the reputation evaluation score of the sender corresponding to the email;

[0013] When the reputation evaluation score is greater than or equal to a preset evaluation threshold, the email from the sender is received, and spam in the email is filtered out by a preset spam filtering method.

[0014] To achieve the above-mentioned purpose, a second embodiment of the present invention provides an email protection device, the device comprising:

[0015] A first calculation module is used to obtain email data of any email through a preset data collection system, and calculate multiple reputation evaluation factors of the sender of the email based on the email data, wherein the reputation evaluation factors include the frequency of email sending by the sender within a preset time interval, user feedback data of the recipient reporting or marking spam emails, and historical behavior data of the sender;

[0016] The second calculation module is used to calculate the weight of each reputation evaluation factor according to the contribution of each reputation evaluation factor corresponding to the email to the spam;

[0017] A third calculation module is used to perform weighted summation of the weights of each reputation evaluation factor through a weighted scoring algorithm to obtain a reputation evaluation score of the sender corresponding to the email;

[0018] The filtering module is used to receive the email of the sender when the reputation evaluation score is greater than or equal to a preset evaluation threshold, and filter out spam in the email through a preset spam protection device.

[0019] To achieve the above-mentioned purpose, the third aspect of the present invention proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in the first aspect.

[0020] In order to achieve the above-mentioned purpose, the fourth aspect of the present invention proposes a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0021] In order to achieve the above-mentioned purpose, a fifth aspect of the present invention provides a computer program product, and when the computer program is executed by a processor, it implements the method described in the first aspect.

[0022] The email protection method, device, electronic device, storage medium and computer program product provided by the embodiment of the present invention obtains the email data of any email through a preset data collection system, and calculates the reputation evaluation factor of the sender corresponding to the email based on the email data; calculates the weight of each reputation evaluation factor according to the contribution of each reputation evaluation factor to spam; performs weighted summation of the weights of each reputation evaluation factor through a weighted scoring algorithm to obtain the sender's reputation evaluation score; when the reputation evaluation score is greater than or equal to a preset evaluation threshold, receives the sender's email, and filters out spam in the email through a preset spam filtering method. Therefore, by comprehensively considering multiple reputation evaluation factors calculated by email data to evaluate the sender's reputation, the accurate recognition rate of the email sender can be improved, the false alarm rate and the missed alarm rate can be reduced, and the effect of spam filtering can be improved.

[0023] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0025] Figure 1 A flowchart of an email protection method provided by an embodiment of the present invention;

[0026] Figure 2 A schematic diagram of an update process of an email protection method provided by an embodiment of the present invention;

[0027] Figure 3 A schematic diagram of the structure of an email protection device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0029] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in the present invention are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with the relevant laws, regulations and standards of relevant countries and regions.

[0030] The following describes the email protection method and device according to the embodiments of the present invention with reference to the accompanying drawings.

[0031] Figure 1 A flowchart of an email protection method provided by an embodiment of the present invention.

[0032] like Figure 1 As shown, the method comprises the following steps:

[0033] Step 101, obtain the email data of any email through a preset data collection system, and calculate multiple reputation evaluation factors of the sender corresponding to the email based on the email data, wherein the reputation evaluation factors include the frequency of email sending by the sender within a preset time period, user feedback data of the recipient reporting or marking spam, and the sender's historical behavior data.

[0034] Optionally, the email data includes the email address of the sender of the email, the timestamp of sending the email, the recipient list, the email subject and content, spam information marked by the recipient, and recipient feedback information.

[0035] The recipient list may be one or more, the email subject and content may include pictures, texts and links, and the recipient feedback information may be the information filled in by the recipient when reporting the email.

[0036] Optionally, the data collection system is implemented through an email server log or a dedicated data collection module, but is not limited thereto and this embodiment does not specifically limit this.

[0037] In some embodiments, based on the email data, one implementation method for calculating multiple reputation evaluation factors of the sender of the email can be: according to the timestamp of the email, the sending frequency of the email can be calculated; according to the email address, recipient list, email subject and content of the sender of the email, the historical behavior data of the sender of the email can be obtained; according to the spam information marked by the recipient and the recipient feedback information, the user feedback data of the recipient of the email can be obtained. Therefore, a reliable data collection system is designed to collect and process the sender's historical email data. The accuracy and real-time nature of the email data are ensured to improve the accuracy and efficiency of the reputation evaluation.

[0038] Step 102: Calculate the weight of each reputation evaluation factor according to the contribution of each reputation evaluation factor corresponding to the email to spam.

[0039] In some embodiments, with respect to sending frequency: senders who send a large number of emails in a short period of time are more likely to be spammers; with respect to user feedback data: the report or marking information of the recipient (user) on spam can be used as a reference; with respect to historical behavior data: whether the sender information is frequently changed, whether a large number of spam emails have been sent, etc. Thus, the contribution of each reputation evaluation factor to spam can be accurately determined, the weight of each reputation evaluation factor can be calculated, and the weight can be dynamically adjusted according to the actual situation to ensure the accuracy and practicality of the reputation evaluation.

[0040] Step 103: weighted summing the weights of the reputation evaluation factors is performed using a weighted scoring algorithm to obtain a reputation evaluation score of the sender corresponding to the email.

[0041] In some embodiments, the reputation evaluation scores may be divided into value ranges and levels to facilitate subsequent spam filtering and processing.

[0042] Step 104: When the reputation evaluation score is greater than or equal to the preset evaluation threshold, the sender's email is received, and spam in the email is filtered out by a preset spam filtering method.

[0043] In some embodiments, based on the reputation evaluation score, an evaluation threshold is set to distinguish between spam senders and legitimate senders. The evaluation threshold can be dynamically adjusted according to the needs of the recipient and the actual situation.

[0044] Specifically, when a recipient receives a new email, the sender's reputation evaluation score is first checked. If the sender's reputation evaluation score is lower than the set evaluation threshold, the email is marked as spam. For senders whose reputation evaluation scores are higher than the evaluation threshold, other traditional spam filtering methods can be continued. Thus, by considering the false alarm rate and the missed alarm rate, a reasonable evaluation threshold for email filtering is designed to ensure effective spam filtering while minimizing false alarms.

[0045] In some embodiments, the spam filtering method includes a spam rule filtering method, an email blacklist, a spam content analysis method, an email whitelist, anti-spam software, a spam image recognition method, and a spam user feedback mechanism.

[0046] Optionally, the spam rule filtering method uses pre-defined rules to detect spam. These rules may be based on keywords, phrases, email header information, etc. For example, detecting whether an email contains specific words, common formats of spam, etc.

[0047] Optionally, email blacklisting is done by maintaining a blacklist of known spammers' IP addresses, domain names, or email addresses. When an email is received, it can be checked to see if the sender is on the blacklist and, based on that, decide whether to mark the email as spam.

[0048] Optionally, the spam content analysis method is to analyze the content of the email, including text, images, links, etc., to determine whether it is spam.

[0049] Optionally, a mail whitelist is to maintain a whitelist of known trusted senders' IP addresses, domain names or email addresses. When an email is received, it can be checked whether the sender is on the whitelist, and if so, it is allowed to be received.

[0050] Optionally, anti-spam software is used by using specially designed anti-spam software that can detect and filter spam and provide adjustable parameters and configuration options to suit different environments and needs.

[0051] Optionally, the spam image recognition method analyzes and recognizes images in emails to detect embedded spam content or links. The spam image recognition method can prevent spammers from circumventing text analysis through images.

[0052] Optionally, a spam user feedback mechanism is a feedback mechanism provided to recipients, allowing recipients to report spam or misjudged emails. The feedback data can be used to improve the accuracy of the spam filtering system.

[0053] The email protection method of the embodiment of the present invention obtains the email data of any email through a preset data collection system, and calculates the reputation evaluation factor of the sender corresponding to the email based on the email data; calculates the weight of each reputation evaluation factor according to the contribution of each reputation evaluation factor to spam; performs weighted summation of the weights of each reputation evaluation factor through a weighted scoring algorithm to obtain the sender's reputation evaluation score; when the reputation evaluation score is greater than or equal to a preset evaluation threshold, receives the sender's email, and filters out spam in the email through a preset spam filtering method. Therefore, by comprehensively considering multiple reputation evaluation factors calculated by email data to evaluate the sender's reputation, the accurate recognition rate of the email sender can be improved, the false alarm rate and the missed alarm rate can be reduced, and the effect of spam filtering can be improved.

[0054] In order to clearly illustrate the above embodiment, this embodiment also provides a schematic diagram of an update process of an email protection method, such as Figure 2 shown.

[0055] like Figure 2 As shown, the update process of the email protection method may include the following steps:

[0056] Step 201, using a machine learning algorithm to calculate the mapping relationship between each email data and the reputation evaluation score of the corresponding email sender, so as to construct an email sender reputation evaluation model.

[0057] In some embodiments, machine learning algorithms include, but are not limited to, logistic regression, random forest, and other algorithms, but are not limited thereto.

[0058] Furthermore, the machine learning algorithm uses a supervised learning algorithm to learn the mapping relationship between each email data and the reputation evaluation score of the corresponding email sender through training, and then builds an email sender reputation evaluation model. Therefore, based on the email sender reputation evaluation model, it is possible to quickly perform reputation evaluation and filtering while receiving emails, improve email processing efficiency, and avoid email congestion and delay.

[0059] Step 202: predicting the real-time reputation evaluation score of the real-time sender of the email using the email sender reputation evaluation model to determine whether the real-time sender is a receivable sender.

[0060] In some embodiments, when it is determined that the real-time sender is not a receivable sender, real-time feedback information from the recipient is obtained; when it is determined that the real-time sender is a receivable sender, the evaluation threshold of the email sender reputation evaluation model is dynamically adjusted according to the real-time email data and the real-time feedback information from the recipient, so that the email sender reputation evaluation model can adaptively respond to the ever-changing means of spam attacks.

[0061] Step 203: Based on the real-time sender's email data, the weights of the reputation evaluation factors and the parameters of the weighted scoring algorithm are adjusted by an adaptive algorithm.

[0062] In some embodiments, the feedback option integrated in the email client can also be used to collect the recipient's real-time feedback information and the real-time spam information marked by the recipient; based on the recipient's real-time feedback information and the real-time spam information marked by the recipient, the sender's reputation evaluation score can be adjusted in real time. Therefore, if a sender is reported multiple times, its reputation score will decrease, and it can respond to new spam attacks in a timely manner, maintaining the timeliness and flexibility of the protection mechanism.

[0063] The email protection method of the embodiment of the present invention is updated, and the mapping relationship between each email data and the reputation evaluation score of the corresponding sender of the email is calculated through a machine learning algorithm to build an email sender reputation evaluation model; based on the real-time sender's email data, the weight of each reputation evaluation factor and the parameters of the weighted scoring algorithm are adjusted through an adaptive algorithm; based on the real-time sender's email data, the weight of each reputation evaluation factor and the parameters of the weighted scoring algorithm are adjusted through an adaptive algorithm. As a result, the email sender reputation evaluation model can be customized and adjusted according to different email systems and user needs, respond to the recipient's feedback in a timely manner, and update the sender's reputation evaluation score according to the recipient's feedback, with high flexibility.

[0064] In order to implement the above embodiment, the present invention also provides an email protection device.

[0065] Figure 3 A schematic diagram of the structure of an email protection device provided by an embodiment of the present invention.

[0066] like Figure 3 As shown, the email protection device 30 includes: a first calculation module 31 , a second calculation module 32 , a third calculation module 33 and a filtering module 34 .

[0067] The first calculation module 31 is used to obtain the email data of any email through a preset data collection system, and calculate multiple reputation evaluation factors of the sender of the email based on the email data, wherein the reputation evaluation factors include the frequency of sending emails by the sender within a preset time interval, user feedback data of the recipient reporting or marking spam emails, and the sender's historical behavior data;

[0068] The second calculation module 32 is used to calculate the weight of each reputation evaluation factor according to the contribution of each reputation evaluation factor corresponding to the email to the spam;

[0069] A third calculation module 33 is used to perform weighted summation of the weights of each reputation evaluation factor by using a weighted scoring algorithm to obtain a reputation evaluation score of the sender corresponding to the email;

[0070] The filtering module 34 is used to receive the email from the sender and filter out spam in the email through a preset spam protection device when the reputation evaluation score is greater than or equal to a preset evaluation threshold.

[0071] Furthermore, in a possible implementation of an embodiment of the present invention, the email data includes the email address of the sender of the email, the timestamp of sending the email, the recipient list, the email subject and content, spam information marked by the recipient, and the recipient feedback information.

[0072] Furthermore, in a possible implementation of the embodiment of the present invention, the first calculation module 31 is specifically configured to:

[0073] According to the timestamp of sending the email, determine the sending frequency of the email;

[0074] Obtain the historical behavior data of the sender of the email according to the email address, recipient list, email subject and content of the email;

[0075] According to the spam information marked by the recipient and the recipient feedback information, the user feedback data of the recipient corresponding to the email is obtained.

[0076] Furthermore, in a possible implementation of the embodiment of the present invention, the device further includes:

[0077] A construction module is used to calculate the mapping relationship between each email data and the reputation evaluation score of the corresponding email sender through a machine learning algorithm to build an email sender reputation evaluation model;

[0078] The judgment module is used to predict the real-time reputation evaluation score of the real-time sender of the email through the email sender reputation evaluation model to judge whether the real-time sender is a receivable sender.

[0079] Furthermore, in a possible implementation of the embodiment of the present invention, the device further includes:

[0080] The first adjustment module is used to adjust the weights of the reputation evaluation factors and the parameters of the weighted scoring algorithm through an adaptive algorithm based on the real-time sender's email data.

[0081] Furthermore, in a possible implementation of the embodiment of the present invention, the device further includes:

[0082] A collection module, for collecting recipients' real-time feedback information and real-time spam information marked by recipients through a feedback option integrated in an email client;

[0083] The second adjustment module is used to adjust the sender's reputation evaluation score in real time based on the recipient's real-time feedback information and the real-time spam information marked by the recipient.

[0084] Furthermore, in a possible implementation of an embodiment of the present invention, the spam filtering method includes: a spam rule filtering device, an email blacklist, a spam content analysis device, an email whitelist, anti-spam software, a spam image recognition device, and a spam user feedback mechanism.

[0085] The email protection device of the embodiment of the present invention obtains the email data of any email through a preset data collection system, and calculates the reputation evaluation factor of the sender corresponding to the email based on the email data; calculates the weight of each reputation evaluation factor according to the contribution of each reputation evaluation factor to spam; performs weighted summation of the weights of each reputation evaluation factor through a weighted scoring algorithm to obtain the sender's reputation evaluation score; when the reputation evaluation score is greater than or equal to a preset evaluation threshold, receives the sender's email, and filters out spam in the email through a preset spam filtering method. Therefore, by comprehensively considering multiple reputation evaluation factors calculated by email data to evaluate the sender's reputation, the accurate recognition rate of the email sender can be improved, the false alarm rate and the missed alarm rate can be reduced, and the effect of spam filtering can be improved.

[0086] In order to implement the above embodiment, the present invention further provides an electronic device, including:

[0087] at least one processor; and

[0088] a memory communicatively connected to the at least one processor; wherein,

[0089] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the aforementioned method.

[0090] In order to implement the above embodiment, the present invention further proposes a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to enable the computer to execute the above method.

[0091] In order to implement the above embodiments, the present invention further provides a computer program product, including a computer program, wherein the computer program implements the above method when executed by a processor.

[0092] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0093] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0094] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0095] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0096] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0097] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0098] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0099] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. An email protection method, characterized in that: The method comprises: Obtaining email data of any email through a preset data collection system, and calculating multiple reputation evaluation factors of the sender of the email based on the email data, wherein the reputation evaluation factors include the frequency of email sending by the sender within a preset time interval, user feedback data of the recipient reporting or marking spam emails, and the sender's historical behavior data; The weight of each reputation evaluation factor is calculated according to the contribution of each reputation evaluation factor of the email to spam; The weights of each reputation evaluation factor are weighted and summed by a weighted scoring algorithm to obtain the reputation evaluation score of the sender corresponding to the email; When the reputation evaluation score is greater than or equal to a preset evaluation threshold, the email from the sender is received, and spam in the email is filtered out by a preset spam filtering method.

2. The method according to claim 1, characterized in that The email data includes the email address of the sender of the email, the timestamp of sending the email, the recipient list, the email subject and content, the spam information marked by the recipient, and the recipient feedback information.

3. The method according to claim 2, characterized in that The multiple reputation evaluation factors of the sender of the email corresponding to the email are calculated based on the email data, including: According to the timestamp of sending the email, calculate the sending frequency of the email; Obtain the historical behavior data of the sender of the email according to the email address, recipient list, email subject and content of the email; According to the spam information marked by the recipient and the recipient feedback information, the user feedback data of the recipient corresponding to the email is obtained.

4. The method according to claim 1, characterized in that The method further comprises: The mapping relationship between each email data and the reputation evaluation score of the corresponding email sender is calculated through a machine learning algorithm to build an email sender reputation evaluation model; The real-time reputation evaluation score of the real-time sender of the email is predicted by the email sender reputation evaluation model to determine whether the real-time sender is a receivable sender.

5. The method according to claim 1, characterized in that The method further comprises: Based on the real-time sender's email data, the weights of the reputation evaluation factors and the parameters of the weighted scoring algorithm are adjusted through an adaptive algorithm.

6. The method according to claim 1, characterized in that The method further comprises: Collect real-time feedback from recipients and real-time spam information marked by recipients through feedback options integrated into email clients; Based on the real-time feedback information from the recipient and the real-time spam information marked by the recipient, the reputation evaluation score of the sender is adjusted in real time.

7. The method according to claim 1, characterized in that The spam filtering method includes: a spam rule filtering method, a mail blacklist, a spam content analysis method, a mail whitelist, anti-spam software, a spam image recognition method, and a spam user feedback mechanism.

8. An email protection device, characterized in that: The device comprises: A first calculation module is used to obtain email data of any email through a preset data collection system, and calculate multiple reputation evaluation factors of the sender of the email based on the email data, wherein the reputation evaluation factors include the frequency of email sending by the sender within a preset time interval, user feedback data of the recipient reporting or marking spam emails, and historical behavior data of the sender; The second calculation module is used to calculate the weight of each reputation evaluation factor according to the contribution of each reputation evaluation factor corresponding to the email to the spam; A third calculation module is used to perform weighted summation of the weights of each reputation evaluation factor through a weighted scoring algorithm to obtain a reputation evaluation score of the sender corresponding to the email; The filtering module is used to receive the email of the sender when the reputation evaluation score is greater than or equal to a preset evaluation threshold, and filter out spam in the email through a preset spam protection device.

9. The device according to claim 8, characterized in that The email data includes the email address of the sender of the email, the timestamp of sending the email, the recipient list, the email subject and content, the spam information marked by the recipient, and the recipient feedback information.

10. The device according to claim 9, characterized in that The first calculation module is specifically used for: According to the timestamp of sending the email, determine the sending frequency of the email; Obtain the historical behavior data of the sender of the email according to the email address, recipient list, email subject and content of the email; According to the spam information marked by the recipient and the recipient feedback information, the user feedback data of the recipient corresponding to the email is obtained.

11. The device according to claim 8, characterized in that The device also includes: A construction module is used to calculate the mapping relationship between each email data and the reputation evaluation score of the corresponding email sender through a machine learning algorithm to build an email sender reputation evaluation model; The judgment module is used to predict the real-time reputation evaluation score of the real-time sender of the email through the email sender reputation evaluation model to judge whether the real-time sender is a receivable sender.

12. The device according to claim 8, characterized in that The device also includes: The first adjustment module is used to adjust the weights of the reputation evaluation factors and the parameters of the weighted scoring algorithm through an adaptive algorithm based on the real-time sender's email data.

13. The device according to claim 8, characterized in that The device also includes: A collection module, for collecting recipients' real-time feedback information and real-time spam information marked by recipients through a feedback option integrated in an email client; The second adjustment module is used to adjust the sender's reputation evaluation score in real time based on the recipient's real-time feedback information and the real-time spam information marked by the recipient.

14. The device according to claim 8, characterized in that The spam filtering method comprises: a spam rule filtering device, a mail blacklist, a spam content analyzing device, a mail whitelist, anti-spam software, a spam image recognition device, and a spam user feedback mechanism.

15. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

16. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

17. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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