Number status identification method, number status identification device and electronic equipment

Abstract

This application discloses a number status identification method, a number status identification device, and an electronic device. The method includes: obtaining the message sending volume and message receiving volume of a calling number corresponding to each unit time period within a first time period, wherein the message sending volume is the number of messages sent to the called number, and the message receiving volume is the number of messages received from the called number; determining a message sending frequency threshold corresponding to the calling number within each unit time period based on the message sending volume and message receiving volume corresponding to each unit time period, using a quartile method; determining a message sending / receiving ratio threshold corresponding to the calling number within each unit time period based on the message sending volume and message receiving volume corresponding to each unit time period, using a quartile method; and performing status identification on the calling number based on the message sending frequency threshold and the message sending / receiving ratio threshold.

Description

Technical Field

[0001] This application belongs to the field of computer technology, and specifically relates to a number status recognition method, a number status recognition device, and an electronic device. Background Technology

[0002] SMS bombing typically refers to a sender sending a large number of text messages to a specific mobile phone number within a short period of time, causing the recipient to be unable to use their phone or other services normally. Currently, security controls for SMS bombing primarily employ methods such as identifying SMS bombing when the number of messages sent by the sender to the recipient within a certain time frame reaches a certain threshold, and then intercepting the messages sent by the sender to the recipient.

[0003] However, different users have vastly different usage scenarios and behavioral habits. For example, some users may frequently send text messages, which is not necessarily malicious but rather a normal communication need. A fixed threshold might incorrectly flag these normal messaging behaviors as spamming, leading to abnormal processing of the sender's number. Alternatively, in certain scenarios, such as security verification or account security alerts, a large number of messages might be sent to users in a short period. Using a fixed threshold could also easily misjudge these normal messages as spamming, disrupting normal business processes. Therefore, judging based on a fixed threshold will result in a high false positive rate. Summary of the Invention

[0004] This application provides a number status recognition method, a number status recognition device, and an electronic device, which can solve the problem of high false judgment rate.

[0005] In a first aspect, embodiments of this application provide a number status identification method, the method comprising: obtaining the message sending volume and message receiving volume of a calling number corresponding to each unit time period within a first time period, wherein the message sending volume is the number of messages sent to a called number, and the message receiving volume is the number of messages received from the called number; determining a message sending frequency threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period using an quartile method; determining a message sending / receiving ratio threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period using an quartile method; and performing status identification on the calling number based on the message sending frequency threshold and the message sending / receiving ratio threshold.

[0006] Secondly, embodiments of this application provide a number status identification device, which includes: an acquisition module, configured to acquire the message sending volume and message receiving volume of a calling number corresponding to each unit time period within a first time period, wherein the message sending volume is the number of messages sent to the called number, and the message receiving volume is the number of messages received from the called number; a first determination module, configured to determine a message sending frequency threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period, using a quartile method; a second determination module, configured to determine a message sending / receiving ratio threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period, using the quartile method; and an identification module, configured to allow a user to perform status identification on the calling number based on the message sending frequency threshold and the message sending / receiving ratio threshold.

[0007] Thirdly, embodiments of this application provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0008] Fourthly, embodiments of this application provide a computer-readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0009] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0010] In a sixth aspect, embodiments of this application provide a computer program product comprising at least one computer program that, when loaded and executed by a processor, implements the method described in the first aspect.

[0011] In this embodiment, the message sending and receiving volumes of the calling number are obtained for each unit time period within a first time period. The message sending volume is the number of messages sent to the called number, and the message receiving volume is the number of messages received from the called number. Then, based on the message sending and receiving volumes for each unit time period, a message sending frequency threshold corresponding to the calling number is determined using the quartile method. Next, based on the message sending and receiving volumes for each unit time period, a message transmission / reception ratio threshold corresponding to the calling number is determined using the quartile method. Finally, based on the message sending frequency threshold... By using message sending and receiving ratio thresholds to identify the status of calling numbers, the message sending frequency threshold and message sending and receiving ratio threshold can be dynamically set according to different users' message sending and receiving behaviors. This provides more accurate and flexible thresholds, reducing the probability of misjudging normal behavior as message bombing. At the same time, determining the message sending frequency threshold and message sending and receiving ratio threshold based on the quartile method improves the accuracy of the message sending frequency threshold and message sending and receiving ratio threshold, further reducing the false judgment rate. In addition, by combining the message sending frequency threshold and message sending and receiving ratio threshold to identify the status of calling numbers, the accuracy of identification is improved, which also reduces the false judgment rate. Attached Figure Description

[0012] Figure 1 This is a flowchart illustrating a number status identification method provided in an embodiment of this application;

[0013] Figure 2 This is a schematic diagram of the structure of a number status recognition device provided in an embodiment of this application;

[0014] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0015] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0016] The following description, in conjunction with the accompanying drawings, details a number status identification method, a number status identification device, and an electronic device provided in this application through specific embodiments and application scenarios.

[0017] Figure 1This application illustrates a method for identifying a number status, provided by an embodiment. This method can be executed by an electronic device, which may include a server and / or a terminal device. In other words, the method can be executed by software or hardware installed on the electronic device, and includes the following steps:

[0018] S110: Get the number of messages sent and received for the calling number in each time unit within the first time period.

[0019] The message sending volume refers to the number of messages sent to the called number, and the message receiving volume refers to the number of messages received from the called number.

[0020] It is understandable that different users have different SMS sending needs and usage frequencies. Therefore, it is necessary to dynamically set thresholds based on sending and receiving behaviors for different numbers. In this embodiment, the sending and receiving behaviors of the calling number are analyzed by obtaining the message sending and receiving volumes corresponding to each unit time period within the first time period.

[0021] In one exemplary embodiment, S110 may include the following steps:

[0022] S112: Obtain the communication history of the calling number and the called number within the first time period.

[0023] S114: Based on the communication history, determine the message sending volume of the calling number in each unit time period within the first time period, and determine the message receiving volume of the calling number in each unit time period within the first time period.

[0024] S120: Based on the message sending volume and message receiving volume corresponding to each of the unit time periods, determine the message sending frequency threshold within the unit time period corresponding to the calling number using the quartile method.

[0025] It is understandable that if a calling number sends a large number of text messages to a called number within a unit of time, it indicates that the calling number's sending frequency is high. Therefore, the message sending frequency can be determined based on the message sending volume corresponding to each unit of time. One method for determining the message sending frequency is based on the quartile method. The quartile method identifies and removes outliers by calculating the interquartile range of the data, thus reducing the impact of outliers on the analysis and calculation results and improving the accuracy of the analysis. Therefore, in this embodiment, the message sending frequency is determined based on the quartile method, resulting in high accuracy of the determined message sending frequency.

[0026] S130: Based on the message sending volume and message receiving volume corresponding to each of the unit time periods, determine the message sending / receiving ratio threshold within the unit time period corresponding to the calling number using the quartile method.

[0027] As we can understand, the message send / receive ratio (SRR) refers to the ratio of the number of messages sent by the calling number to the number of messages received by the calling number per unit of time; in other words, the ratio of message sent to message received. A higher SRR indicates that the number of messages sent by the calling number is significantly greater than the number of messages replied to. Therefore, by determining the SRR threshold based on the message sent and received volumes for each time period, we can determine whether the calling number's behavior constitutes message bombing.

[0028] The message sending / receiving ratio threshold is also determined based on the quartile method, which ensures high accuracy in determining the threshold.

[0029] S140: Based on the message sending frequency threshold and the message sending-receiving ratio threshold, perform status identification on the calling number.

[0030] Understandably, after determining the message sending frequency threshold and the message sending-to-receive ratio threshold, the calling number can be identified based on these thresholds.

[0031] In this step, based on the message sending frequency threshold and message send-receive ratio threshold, the calling number's status is identified. This allows for timely determination and filtering of whether the messages sent by the calling number are spam, effectively reducing interference and disturbance to users. Secondly, it can also prevent calling numbers from sending large amounts of spam, reducing the probability of user personal information leakage, thereby enhancing user satisfaction and loyalty.

[0032] In this embodiment, the message sending and receiving volumes of the calling number are obtained for each unit time period within a first time period. The message sending volume is the number of messages sent to the called number, and the message receiving volume is the number of messages received from the called number. Then, based on the message sending and receiving volumes for each unit time period, a message sending frequency threshold corresponding to the calling number is determined using the quartile method. Next, based on the message sending and receiving volumes for each unit time period, a message transmission / reception ratio threshold corresponding to the calling number is determined using the quartile method. Finally, based on the message sending frequency threshold... By using message sending and receiving ratio thresholds to identify the status of calling numbers, the message sending frequency threshold and message sending and receiving ratio threshold can be dynamically set according to different users' message sending and receiving behaviors. This provides more accurate and flexible thresholds, reducing the probability of misjudging normal behavior as message bombing. At the same time, determining the message sending frequency threshold and message sending and receiving ratio threshold based on the quartile method improves the accuracy of the message sending frequency threshold and message sending and receiving ratio threshold, further reducing the false judgment rate. In addition, by combining the message sending frequency threshold and message sending and receiving ratio threshold to identify the status of calling numbers, the accuracy of identification is improved, which also reduces the false judgment rate.

[0033] The following sections provide illustrative explanations of how to determine the message sending frequency threshold corresponding to the calling number and how to determine the message sending / receiving ratio threshold corresponding to the calling number.

[0034] (1) In an exemplary embodiment, determining the message sending frequency threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period, using the quartile method, may include the following steps:

[0035] S122: Determine the first weighted cumulative distribution value corresponding to each unit time period based on the message sending volume corresponding to each unit time period.

[0036] As can be understood, the first weighted cumulative distribution value refers to the result of summing up each data point after weighting it according to the importance or weight of the message sending volume corresponding to each unit time period. This data point refers to a unit time period. The first weighted cumulative distribution value is used to represent the importance of each data point. When data points have different importance or frequency, weighted accumulation can better reflect the overall trend of the original data or the impact of important data points.

[0037] In an exemplary embodiment, determining the first weighted cumulative distribution value corresponding to each unit time period based on the message sending volume and the message receiving volume corresponding to each unit time period may include the following steps:

[0038] Step 1: Determine the message sending weight for each unit time period based on the message sending volume for each unit time period.

[0039] Understandably, when performing cumulative calculations, directly adding data points without considering their importance might result in the first weighted cumulative distribution value failing to reflect the essential differences between the data points. By introducing weights, the first weighted cumulative distribution value for each unit of time period can be accurately calculated based on the actual importance of each data point.

[0040] Step 2: Sort the message sending weights corresponding to each time unit in descending order.

[0041] Step 3: Calculate the first weighted cumulative distribution value corresponding to each of the sorted unit time periods.

[0042] Regarding steps 2 and 3 above, it can be understood that the first weighted cumulative distribution value corresponding to each unit time period is the sum of the message sending weights corresponding to all unit time periods preceding that unit time period. In calculating the first weighted cumulative distribution value, sorting by message sending weight allows for direct accumulation from the minimum to the maximum value, simplifying the accumulation process and reducing errors. Without sorting, the message sending weights of some important data might be overlooked or incorrectly accumulated to inappropriate positions, resulting in an inaccurate first weighted cumulative distribution value for a given unit time period.

[0043] In one exemplary embodiment, before S112, the method further includes: cleaning the message sending volume, i.e. removing outliers, which may include values ​​where the message sending volume is 0, values ​​where the message sending volume deviates significantly from the normal value, etc.

[0044] S124: Based on the first weighted cumulative distribution value corresponding to each unit time period, determine the first upper quartile and the first lower quartile of the first weighted cumulative distribution value using the quartile method.

[0045] It is understandable that the first upper quartile is the frequency of data points whose first weighted cumulative distribution value reaches 25% of the total weight, and the first lower quartile is the frequency of data points whose first weighted cumulative distribution value reaches 75% of the total weight.

[0046] It should be noted that if a certain quartile is located exactly between two data points, that is, between the first weighted cumulative distribution values ​​of the two data points, then the quartile is taken as the weighted average of the first weighted cumulative distribution values ​​of the two data points.

[0047] S126: Determine the minimum threshold and the maximum threshold of the first weighted cumulative distribution value based on the first upper quartile and the first lower quartile.

[0048] In an exemplary embodiment, determining the minimum and maximum threshold values ​​of the first weighted cumulative distribution value based on the first upper quartile and the first lower quartile includes: determining a first interquartile range based on the first upper quartile and the first lower quartile; and determining the minimum and maximum threshold values ​​of the first weighted cumulative distribution value based on the first upper quartile, the first lower quartile, and the first interquartile range.

[0049] The interquartile range (IQR) effectively distinguishes extreme values ​​from fluctuations in a normal distribution of data. The first interquartile range is determined based on the first upper quartile (Q1) and the first lower quartile (Q3). The first interquartile range is the difference between the first lower quartile (Q3) and the first upper quartile (Q1), i.e., IQR = Q3 - Q1. In other words, the first interquartile range represents the fluctuation range of the middle 50% of the data and is unaffected by extreme values.

[0050] Furthermore, in another exemplary embodiment, determining the minimum and maximum thresholds of the first weighted cumulative distribution value based on the first upper quartile, the first lower quartile, and the first interquartile range includes: determining that the minimum threshold of the first weighted cumulative distribution value is the difference between the first upper quartile and K times the first interquartile range, where K is a real number greater than 0; and determining that the maximum threshold of the first weighted cumulative distribution value is the sum of the first lower quartile and K times the first interquartile range.

[0051] In other words, the lowest threshold of the first weighted cumulative distribution value is L1 = Q1 - K * IQR, and the highest threshold of the first weighted cumulative distribution value is H1 = Q3 + K * IQR. Here, K can be 1.5.

[0052] S128: Based on the message sending volume corresponding to the unit time period corresponding to the first weighted cumulative distribution value within the first range, determine the message sending frequency threshold, wherein the first range is from the first weighted cumulative distribution value corresponding to the lowest threshold to the first weighted cumulative distribution value corresponding to the highest threshold.

[0053] In other words, any value below the minimum threshold or above the maximum threshold is considered an outlier and is not used when determining the frequency threshold. This is because the first range typically includes normally distributed data points, and excluding outliers effectively avoids abnormal effects caused by individual extreme values, making the determined frequency threshold more accurate.

[0054] In one exemplary embodiment, determining the message sending frequency threshold based on the message sending volume corresponding to the unit time period corresponding to the first weighted cumulative distribution value within a first range may include the following steps:

[0055] Step 1: Based on the message sending volume corresponding to each unit time period corresponding to the first range, determine the average value of the first message sending frequency corresponding to the unit time period.

[0056] In other words, the average frequency of the first message is the ratio of the sum of the message sending frequencies for each time period to the total number of time periods.

[0057] Step 2: Based on the message sending volume corresponding to each of the aforementioned time periods and the average frequency of the first message sending, determine the average frequency of the second message sending using the standard deviation formula.

[0058] For example, the average frequency of the second message sending can be represented by the following standard deviation formula:

[0059]

[0060] Where S represents the average frequency of sending the second message, and N is the total number of time intervals within the first range. Let i be the message sending frequency in the i-th time unit. This represents the average frequency of the first message being sent.

[0061] Step 3: Determine the message sending frequency threshold based on the average value of the first message sending frequency and the average value of the second message sending frequency.

[0062] In an exemplary embodiment, the message sending frequency threshold can be expressed by the following formula:

[0063]

[0064] Where X is the message sending frequency threshold, and S is the average second message sending frequency. This represents the average frequency of the first message being sent.

[0065] In another exemplary embodiment, the message sending frequency threshold can be expressed by the following formula:

[0066]

[0067] Where X is the message sending frequency threshold, and S is the average second message sending frequency. This represents the average frequency of the first message being sent.

[0068] In (1) above, the method for determining the message sending frequency threshold is based on a combination of quartile analysis and standard deviation, which realizes fully automated dynamic configuration of the threshold.

[0069] (2) In an exemplary embodiment, determining the message transmission / reception ratio threshold within the unit time period corresponding to the calling number based on the quartile method according to the message transmission volume and message reception volume corresponding to each unit time period includes:

[0070] S132: Determine the message sending / receiving ratio for each unit time period based on the message sending volume and message receiving volume corresponding to each unit time period.

[0071] S134: Determine the second weighted cumulative distribution value corresponding to each unit time period based on the message sending and receiving ratio value corresponding to each unit time period.

[0072] In one exemplary embodiment, determining the second weighted cumulative distribution value for each unit time period based on the message sending volume and message receiving volume for each unit time period includes: determining the message sending and receiving weight for each unit time period based on the message sending and receiving ratio for each unit time period; sorting the message sending and receiving weights for each unit time period in descending order; and calculating the second weighted cumulative distribution value for each unit time period after sorting.

[0073] The message sending / receiving ratio is the ratio of the number of messages sent to the number of messages received.

[0074] For details regarding the specific content of S134, please refer to the description in the aforementioned S122 regarding determining the message sending frequency threshold, which will not be repeated here.

[0075] S136: Based on the second weighted cumulative distribution value corresponding to each unit time period, determine the second upper quartile and the second lower quartile of the second weighted cumulative distribution value using the quartile method.

[0076] For details regarding S136, please refer to the description in S124 above regarding determining the message sending frequency threshold, which will not be repeated here.

[0077] S137: Determine the minimum and maximum threshold values ​​of the second weighted cumulative distribution value based on the second upper quartile and the second lower quartile.

[0078] In one exemplary embodiment, determining the minimum and maximum threshold values ​​of the second weighted cumulative distribution value based on the second upper quartile and the second lower quartile includes: determining the second interquartile range based on the second upper quartile and the second lower quartile; and determining the minimum and maximum threshold values ​​of the second weighted cumulative distribution value based on the second upper quartile, the second lower quartile, and the second interquartile range.

[0079] Further, in another exemplary embodiment, determining the minimum and maximum thresholds of the second weighted cumulative distribution value based on the second upper quartile, the second lower quartile, and the second interquartile range includes: determining the minimum threshold of the second weighted cumulative distribution value as the difference between the second upper quartile and M times the second interquartile range, where M is a real number greater than 0; and determining the maximum threshold of the second weighted cumulative distribution value as the sum of the second lower quartile and M times the second interquartile range. Wherein, M can be 1.5.

[0080] For details regarding S137, please refer to the description in S126 concerning determining the message sending frequency threshold, which will not be repeated here.

[0081] S138: Based on the message sending / receiving ratio value corresponding to the unit time period corresponding to the second weighted cumulative distribution value within the second range, determine the message sending / receiving ratio threshold, wherein the second range is from the second weighted cumulative distribution value corresponding to the lowest threshold to the second weighted cumulative distribution value corresponding to the highest threshold.

[0082] In one exemplary embodiment, determining the message transmission / reception ratio threshold based on the message transmission / reception ratio corresponding to the unit time period within the second range of the second weighted cumulative distribution value includes: determining a first average message transmission / reception ratio corresponding to each unit time period based on the message transmission / reception ratio corresponding to each unit time period within the second range; determining a second average message transmission / reception ratio using the standard deviation formula based on the message transmission / reception ratio corresponding to each unit time period and the first average message transmission / reception ratio; and determining the message transmission / reception ratio threshold based on the first average message transmission / reception ratio and the second average message transmission / reception ratio.

[0083] For details regarding the specific content of S138, please refer to the description in the aforementioned S128 regarding determining the message sending frequency threshold, which will not be repeated here.

[0084] In (2) above, the method for determining the message sending and receiving ratio threshold is based on a combination of quartile analysis and standard deviation, which realizes fully automated dynamic configuration of the threshold.

[0085] In an exemplary embodiment, the step of identifying the status of the calling number based on the message sending frequency threshold and the message sending-to-receive ratio threshold includes the following steps:

[0086] Step 1: Obtain the target message sending volume and target message receiving volume of the calling number within the target unit time period in the second time period.

[0087] The target time unit can be any time unit.

[0088] Step 2: Based on the target message sending volume and the target message receiving volume, determine the target message sending frequency and target message sending / receiving ratio of the calling number within the target unit time period.

[0089] Optionally, assuming the target message sending volume is N1 and the target message receiving volume is N2, if N2 is 0, then N2 is set to 1, and the target message sending-receiving ratio is N1 / N2.

[0090] Step 3: Based on the target message sending frequency, the target message sending-to-receive ratio, the message sending frequency threshold, and the message sending-to-receive ratio threshold, perform status identification on the calling number.

[0091] In one exemplary embodiment, the step of identifying the status of the calling number based on the target message sending frequency, the target message sending-to-receive ratio, the message sending frequency threshold, and the message sending-to-receive ratio threshold includes one of the following:

[0092] (1) If the target message sending frequency is less than the message sending frequency threshold and the target message sending-receive ratio is less than the message sending-receive ratio threshold, the status of the calling number is determined to be normal.

[0093] In other words, if the frequency of target message sending and the target message sending-to-receive ratio do not reach the corresponding thresholds, it indicates that the calling number is in a normal state.

[0094] (2) If the target message sending frequency is greater than or equal to the message sending frequency threshold and the target message sending-to-receive ratio is less than the message sending-to-receive ratio threshold, the status of the calling number is determined to be suspected abnormal.

[0095] In other words, if the frequency of sending target messages reaches the corresponding threshold, but the sending and receiving ratio of target messages does not reach the corresponding threshold, it indicates that the calling number is suspected to be normal and further judgment is needed on the number.

[0096] (3) If the frequency of sending the target message is less than the message sending frequency threshold and the target message sending-to-receive ratio is greater than or equal to the message sending-to-receive ratio threshold, the status of the calling number is determined to be the suspected abnormality.

[0097] In other words, if the frequency of sending the target message does not reach the corresponding threshold, but the sending and receiving ratio of the target message both reach the corresponding threshold, it also indicates that the status of the calling number is suspected to be normal, and further judgment is needed on the number.

[0098] In another exemplary embodiment, if the target message sending-to-receive ratio is larger, it means that the target message sending volume of the bishop number is greater than the target message receiving volume, that is, the target message sending-to-receive ratio must be greater than 1. Then, if the target message sending volume of the bishop number is much greater than the target message receiving volume, that is, the difference between the target message sending volume and the target message receiving volume is greater than a preset threshold, it can also be determined that the status of the calling number is suspected to be abnormal.

[0099] (4) If the target message sending frequency is greater than or equal to the message sending frequency threshold and the target message sending-to-receive ratio is greater than or equal to the message sending-to-receive ratio threshold, the status of the calling number is determined to be abnormal.

[0100] In other words, if both the frequency of sending the target message and the target message sending-to-receive ratio reach the corresponding thresholds, it indicates that the calling number is in an abnormal state.

[0101] In this embodiment, there is no need for manual review or keyword configuration to identify spam messages. The status of the calling number is identified by the message sending frequency threshold and the message sending-to-receive ratio threshold, thereby determining whether the message sent by the calling number is a spam message.

[0102] In an exemplary embodiment, after performing status identification on the calling number based on the target message sending frequency, the target message sending-to-receive ratio, the message sending frequency threshold, and the message sending-to-receive ratio threshold, the method further includes one of the following:

[0103] (1) When the status of the calling number is suspected to be abnormal, perform in-depth review of the messages sent by the calling number within the target time period.

[0104] Understandably, this in-depth review refers to the manual review and keyword review of messages sent by the calling number to determine whether the messages sent by the calling number are spam. If they are spam, the calling number is determined to be in an abnormal state.

[0105] (2) If the status of the calling number is abnormal, intercept the message sent by the calling number to the called number.

[0106] Understandably, if the calling number exhibits abnormal behavior that constitutes spam, messages sent from that calling number to the called number will be blocked.

[0107] Figure 2 This specification shows a schematic diagram of the structure of a number status identification device provided in an embodiment, as shown below. Figure 3 As shown, the number status identification device 200 may include: an acquisition module 210, a first determination module 220, a second determination module 230, and an identification module 240.

[0108] In this embodiment, the acquisition module 210 is used to acquire the message sending volume and message receiving volume corresponding to each unit time period of the calling number within a first time period, wherein the message sending volume is the number of messages sent to the called number, and the message receiving volume is the number of messages received from the called number; the first determination module 220 is used to determine the message sending frequency threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period using the quartile method; the second determination module 230 is used to determine the message sending / receiving ratio threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period using the quartile method; and the identification module 240 allows the user to perform status identification on the calling number based on the message sending frequency threshold and the message sending / receiving ratio threshold.

[0109] In an exemplary embodiment, the first determining module 220 is specifically configured to: determine a first weighted cumulative distribution value corresponding to each unit time period based on the message sending volume corresponding to each unit time period; determine a first upper quartile and a first lower quartile of the first weighted cumulative distribution value based on the quartile method based on the first weighted cumulative distribution value corresponding to each unit time period; determine a minimum threshold and a maximum threshold of the first weighted cumulative distribution value based on the first upper quartile and the first lower quartile; and determine a message sending frequency threshold based on the message sending volume corresponding to the unit time period corresponding to the first weighted cumulative distribution value within a first range, wherein the first range is from the first weighted cumulative distribution value corresponding to the minimum threshold to the first weighted cumulative distribution value corresponding to the maximum threshold.

[0110] In an exemplary embodiment, the first determining module 220 is specifically configured to: determine the message sending weight corresponding to each unit time period based on the message sending volume corresponding to each unit time period; sort the message sending weights corresponding to each unit time period in descending order; and calculate the first weighted cumulative distribution value corresponding to each unit time period after sorting.

[0111] In an exemplary embodiment, the first determining module 220 is specifically configured to: determine a first interquartile range based on the first upper quartile and the first lower quartile; and determine the minimum threshold and the maximum threshold of the first weighted cumulative distribution value based on the first upper quartile, the first lower quartile, and the first interquartile range.

[0112] In an exemplary embodiment, the first determining module 220 is specifically configured to: determine that the lowest threshold of the first weighted cumulative distribution value is the difference between the first upper quartile and K times the first interquartile range, where K is a real number greater than 0; and determine that the highest threshold of the first weighted cumulative distribution value is the sum of the first lower quartile and K times the first interquartile range.

[0113] In an exemplary embodiment, the first determining module 220 is specifically configured to: determine a first message sending frequency average value corresponding to each unit time period based on the message sending volume corresponding to each unit time period corresponding to the first range; determine a second message sending frequency average value using a standard deviation formula based on the message sending volume corresponding to each unit time period and the first message sending frequency average value; and determine the message sending frequency threshold based on the first message sending frequency average value and the second message sending frequency average value.

[0114] In an exemplary embodiment, the second determining module 230 is specifically configured to: determine a message transmission / reception ratio for each unit time period based on the message transmission volume and message reception volume corresponding to each unit time period; determine a second weighted cumulative distribution value for each unit time period based on the message transmission / reception ratio for each unit time period; determine a second upper quartile and a second lower quartile of the second weighted cumulative distribution value based on the quartile method, according to the second weighted cumulative distribution value for each unit time period; determine a minimum threshold and a maximum threshold of the second weighted cumulative distribution value based on the second upper quartile and the second lower quartile; and determine the message transmission / reception ratio threshold based on the message transmission / reception ratio for each unit time period corresponding to the second weighted cumulative distribution value within a second range, wherein the second range is from the second weighted cumulative distribution value corresponding to the minimum threshold to the second weighted cumulative distribution value corresponding to the maximum threshold.

[0115] In an exemplary embodiment, the second determining module 230 is specifically configured to: determine the message sending and receiving weight corresponding to each unit time period based on the message sending and receiving ratio corresponding to each unit time period; sort the message sending and receiving weights corresponding to each unit time period in descending order; and calculate the second weighted cumulative distribution value corresponding to each unit time period after sorting.

[0116] In one exemplary embodiment, the second determining module 230 is specifically configured to: determine a second interquartile range based on the second upper quartile and the second lower quartile; and determine a minimum threshold and a maximum threshold of the second weighted cumulative distribution value based on the second upper quartile, the second lower quartile, and the second interquartile range.

[0117] In an exemplary embodiment, the second determining module 230 is specifically configured to: determine the lowest threshold of the second weighted cumulative distribution value as the difference between the second upper quartile and M times the second interquartile range, where M is a real number greater than 0; and determine the highest threshold of the second weighted cumulative distribution value as the sum of the second lower quartile and M times the second interquartile range.

[0118] In an exemplary embodiment, the second determining module 230 is specifically configured to: determine a first average message sending / receiving ratio corresponding to each unit time period based on the message sending / receiving ratio value corresponding to each unit time period corresponding to the second range; determine a second average message sending / receiving ratio using the standard deviation formula based on the message sending / receiving ratio value corresponding to each unit time period and the first average message sending / receiving ratio; and determine the message sending / receiving ratio threshold based on the first average message sending / receiving ratio and the second average message sending / receiving ratio.

[0119] In an exemplary embodiment, the identification module 240 is specifically configured to: obtain the target message sending volume and target message receiving volume of the calling number within a target unit time period in a second time period; determine the target message sending frequency and target message sending-receiving ratio of the calling number within the target unit time period based on the target message sending volume and the target message receiving volume; and perform status identification on the calling number based on the target message sending frequency, the target message sending-receiving ratio, the message sending frequency threshold, and the message sending-receiving ratio threshold.

[0120] In an exemplary embodiment, the identification module 240 is specifically configured to: determine that the calling number is in a normal state when the target message sending frequency is less than the message sending frequency threshold and the target message sending-to-receive ratio is less than the message sending-to-receive ratio threshold; determine that the calling number is in a suspected abnormal state when the target message sending frequency is greater than or equal to the message sending frequency threshold and the target message sending-to-receive ratio is less than the message sending-to-receive ratio threshold; determine that the calling number is in a suspected abnormal state when the target message sending frequency is less than the message sending frequency threshold and the target message sending-to-receive ratio is greater than or equal to the message sending-to-receive ratio threshold; and determine that the calling number is in an abnormal state when the target message sending frequency is greater than or equal to the message sending frequency threshold and the target message sending-to-receive ratio is greater than or equal to the message sending-to-receive ratio threshold.

[0121] In one exemplary embodiment, the identification module 240 is specifically used for one of the following: when the status of the calling number is the suspected abnormality, performing in-depth review of the messages sent by the calling number within a target time period; when the status of the calling number is the abnormality, intercepting the messages sent by the calling number to the called number.

[0122] The number status recognition device provided in this application embodiment can achieve... Figure 1 The various processes implemented in the method embodiments shown will not be described again here to avoid repetition.

[0123] The number status identification device in this application embodiment can be a device, or it can be a component, integrated circuit, or chip in an electronic device. This application embodiment does not impose specific limitations.

[0124] One of the number status identification devices in this application embodiment can be a device with an operating system. The operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system.

[0125] Optional, such as Figure 3 As shown, this application embodiment also provides an electronic device 300, including a processor 310, a memory 320, and a program or instructions stored in the memory 320 and executable on the processor 310. When the program or instructions are executed by the processor 310, they implement the various processes of the above-described number status identification method embodiment and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0126] This application also provides a computer-readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described number status identification method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0127] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0128] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described number status recognition method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0129] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0130] This application also provides a computer program product, which includes at least one computer program. When the computer program is loaded and executed by a processor, it implements the various processes of the above-described number status recognition method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0131] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0132] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0133] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for identifying the status of a phone number, characterized in that, include: The message sending volume and message receiving volume of the calling number are obtained for each unit time period within the first time period, wherein the message sending volume is the number of messages sent to the called number, and the message receiving volume is the number of messages received from the called number; Based on the message sending volume and message receiving volume corresponding to each of the unit time periods, the message sending frequency threshold within the unit time period corresponding to the calling number is determined using the quartile method. Based on the message sending volume and message receiving volume corresponding to each of the unit time periods, the message sending and receiving ratio threshold within the unit time period corresponding to the calling number is determined based on the quartile method. The caller ID number is identified based on the message sending frequency threshold and the message sending-receive ratio threshold. The step of determining the message sending frequency threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period, using the quartile method, includes: Based on the message sending volume corresponding to each of the said time periods, determine the first weighted cumulative distribution value corresponding to each of the said time periods; The minimum and maximum threshold values ​​of the first weighted cumulative distribution are determined using the quartile method. Based on the message sending volume corresponding to each unit time period corresponding to the first range, the average message sending frequency corresponding to the unit time period is determined, wherein the first range is from the first weighted cumulative distribution value corresponding to the lowest threshold to the first weighted cumulative distribution value corresponding to the highest threshold; Based on the message sending volume corresponding to each of the aforementioned unit time periods and the average frequency of the first message sending, the average frequency of the second message sending is determined using the standard deviation formula; The message sending frequency threshold is determined based on the average value of the first message sending frequency and the average value of the second message sending frequency. The step of determining the message transmission / reception ratio threshold within the unit time period corresponding to the calling number based on the message transmission volume and message reception volume corresponding to each unit time period, using the quartile method, includes: Based on the message sending volume and message receiving volume corresponding to each of the aforementioned time periods, determine the message sending / receiving ratio for each of the aforementioned time periods; A second weighted cumulative distribution value is determined for each unit time period based on the message sending / receiving ratio value corresponding to each unit time period; The minimum and maximum threshold values ​​of the second weighted cumulative distribution are determined using the quartile method. Based on the message sending and receiving ratio values ​​corresponding to each unit time period corresponding to the second range, the average value of the first message sending and receiving ratio corresponding to the unit time period is determined, and the second range is from the second weighted cumulative distribution value corresponding to the lowest threshold to the second weighted cumulative distribution value corresponding to the highest threshold; Based on the message sending and receiving ratio corresponding to each of the unit time periods and the average value of the first message sending and receiving ratio, the average value of the second message sending and receiving ratio is determined using the standard deviation formula. The message sending / receiving ratio threshold is determined based on the average value of the first message sending / receiving ratio and the average value of the second message sending / receiving ratio.

2. The method according to claim 1, characterized in that, The determination of the minimum and maximum thresholds of the first weighted cumulative distribution value using the quartile method includes: Based on the first weighted cumulative distribution value corresponding to each unit time period, the first upper quartile and the first lower quartile of the first weighted cumulative distribution value are determined using the quartile method. The minimum and maximum threshold values ​​of the first weighted cumulative distribution value are determined based on the first upper quartile and the first lower quartile.

3. The method according to claim 1, characterized in that, The step of determining the first weighted cumulative distribution value corresponding to each unit time period based on the message sending volume corresponding to each unit time period includes: Based on the message sending volume corresponding to each of the aforementioned time periods, determine the message sending weight corresponding to each of the aforementioned time periods; The message sending weights corresponding to each time unit are sorted in descending order; Calculate the first weighted cumulative distribution value corresponding to each of the sorted unit time periods.

4. The method according to claim 2, characterized in that, The determination of the minimum and maximum thresholds of the first weighted cumulative distribution value based on the first upper quartile and the first lower quartile includes: The first interquartile range is determined based on the first upper quartile and the first lower quartile. Based on the first upper quartile, the first lower quartile, and the first interquartile range, the minimum and maximum thresholds of the first weighted cumulative distribution value are determined.

5. The method according to claim 4, characterized in that, The determination of the minimum and maximum thresholds of the first weighted cumulative distribution value based on the first upper quartile, the first lower quartile, and the first interquartile range includes: The minimum threshold for the first weighted cumulative distribution value is determined to be the difference between the first upper quartile and K times the distance between the first quartiles, where K is a real number greater than 0. The highest threshold of the first weighted cumulative distribution value is determined to be the sum of the first lower quartile and K times the first quartile distance.

6. The method according to claim 1, characterized in that, The determination of the minimum and maximum thresholds of the second weighted cumulative distribution value using the quartile method includes: Based on the second weighted cumulative distribution value corresponding to each unit time period, the second upper quartile and the second lower quartile of the second weighted cumulative distribution value are determined using the quartile method. The minimum and maximum threshold values ​​of the second weighted cumulative distribution are determined based on the second upper quartile and the second lower quartile.

7. The method according to claim 1, characterized in that, The step of determining the second weighted cumulative distribution value corresponding to each unit time period based on the message sending / receiving ratio corresponding to each unit time period includes: Based on the message sending and receiving ratio corresponding to each of the unit time periods, the message sending and receiving weight corresponding to each of the unit time periods is determined. The message sending and receiving weights corresponding to each of the aforementioned time units are sorted in descending order; Calculate the second weighted cumulative distribution value corresponding to each of the sorted unit time periods.

8. The method according to claim 6, characterized in that, The determination of the minimum and maximum thresholds of the second weighted cumulative distribution value based on the second upper quartile and the second lower quartile includes: The second interquartile range is determined based on the second upper quartile and the second lower quartile; Based on the second upper quartile, the second lower quartile, and the second interquartile range, the minimum and maximum thresholds of the second weighted cumulative distribution value are determined.

9. The method according to claim 8, characterized in that, The determination of the minimum and maximum thresholds of the second weighted cumulative distribution value based on the second upper quartile, the second lower quartile, and the second interquartile range includes: The minimum threshold for the second weighted cumulative distribution value is determined to be the difference between the second upper quartile and M times the second quartile distance, where M is a real number greater than 0. The highest threshold of the second weighted cumulative distribution value is determined to be the sum of the second lower quartile and M times the second interquartile range.

10. The method according to claim 1, characterized in that, The step of identifying the status of the calling number based on the message sending frequency threshold and the message sending-to-receive ratio threshold includes: Obtain the target message sending volume and target message receiving volume corresponding to the target unit time period within the second time period for the calling number; Based on the target message sending volume and the target message receiving volume, determine the target message sending frequency and target message sending / receiving ratio of the calling number within the target unit time period; The calling number is identified based on the target message sending frequency, the target message sending-to-receive ratio, the message sending frequency threshold, and the message sending-to-receive ratio threshold.

11. The method according to claim 10, characterized in that, The step of identifying the status of the calling number based on the target message sending frequency, the target message sending-to-receive ratio, the message sending frequency threshold, and the message sending-to-receive ratio threshold includes one of the following: If the target message sending frequency is less than the message sending frequency threshold and the target message sending-to-receive ratio is less than the message sending-to-receive ratio threshold, the calling number is determined to be in a normal state. If the target message sending frequency is greater than or equal to the message sending frequency threshold, and the target message sending-to-receive ratio is less than the message sending-to-receive ratio threshold, the calling number is determined to be in a suspected abnormal state. If the target message sending frequency is less than the message sending frequency threshold and the target message sending-to-receive ratio is greater than or equal to the message sending-to-receive ratio threshold, the status of the calling number is determined to be the suspected abnormality. If the target message sending frequency is greater than or equal to the message sending frequency threshold, and the target message sending-to-receive ratio is greater than or equal to the message sending-to-receive ratio threshold, the calling number is determined to be in an abnormal state.

12. The method according to claim 11, characterized in that, After performing status identification on the calling number based on the target message sending frequency, the target message sending-to-receive ratio, the message sending frequency threshold, and the message sending-to-receive ratio threshold, the method further includes one of the following: If the status of the calling number is suspected of being abnormal, the messages sent by the calling number within the target time period will be subject to in-depth review. If the calling number is in an abnormal state, intercept the message sent by the calling number to the called number.

13. A number status recognition device, characterized in that, include: The acquisition module is used to acquire the message sending volume and message receiving volume of the calling number for each unit time period within the first time period, wherein the message sending volume is the number of messages sent to the called number, and the message receiving volume is the number of messages received from the called number; The first determining module is used to determine the message sending frequency threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period, using the quartile method. The second determining module is used to determine the message sending and receiving ratio threshold within the unit time period corresponding to the calling number based on the message sending volume and message receiving volume corresponding to each unit time period and the quartile method. The identification module allows the user to identify the status of the calling number based on the message sending frequency threshold and the message sending-receiving ratio threshold. Specifically, the first determining module is used for: Based on the message sending volume corresponding to each of the said time periods, determine the first weighted cumulative distribution value corresponding to each of the said time periods; The minimum and maximum threshold values ​​of the first weighted cumulative distribution are determined using the quartile method. Based on the message sending volume corresponding to each unit time period corresponding to the first range, the average message sending frequency corresponding to the unit time period is determined, wherein the first range is from the first weighted cumulative distribution value corresponding to the lowest threshold to the first weighted cumulative distribution value corresponding to the highest threshold; Based on the message sending volume corresponding to each of the aforementioned unit time periods and the average frequency of the first message sending, the average frequency of the second message sending is determined using the standard deviation formula; The message sending frequency threshold is determined based on the average value of the first message sending frequency and the average value of the second message sending frequency. Specifically, the second determining module is used for: Based on the message sending volume and message receiving volume corresponding to each of the aforementioned time periods, determine the message sending / receiving ratio for each of the aforementioned time periods; A second weighted cumulative distribution value is determined for each unit time period based on the message sending / receiving ratio value corresponding to each unit time period; The minimum and maximum threshold values ​​of the second weighted cumulative distribution are determined using the quartile method. Based on the message sending and receiving ratio values ​​corresponding to each unit time period corresponding to the second range, the average value of the first message sending and receiving ratio corresponding to the unit time period is determined, and the second range is from the second weighted cumulative distribution value corresponding to the lowest threshold to the second weighted cumulative distribution value corresponding to the highest threshold; Based on the message sending and receiving ratio corresponding to each of the unit time periods and the average value of the first message sending and receiving ratio, the average value of the second message sending and receiving ratio is determined using the standard deviation formula. The message sending / receiving ratio threshold is determined based on the average value of the first message sending / receiving ratio and the average value of the second message sending / receiving ratio.

14. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the number status identification method as described in any one of claims 1-12.

15. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the number status identification method as described in any one of claims 1-12.

16. A computer program product, characterized in that, The computer program product includes program instructions that, when executed by a computer, cause the computer to perform the steps of the number status identification method as described in any one of claims 1-12.

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