CN108009844B - Method and device for determining advertisement cheating behaviors and cloud server - Google Patents

Method and device for determining advertisement cheating behaviors and cloud server Download PDF

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CN108009844B
CN108009844B CN201711160918.2A CN201711160918A CN108009844B CN 108009844 B CN108009844 B CN 108009844B CN 201711160918 A CN201711160918 A CN 201711160918A CN 108009844 B CN108009844 B CN 108009844B
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CN108009844A (en
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穆音凯
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Suzhou Lifeng Zhilian Technology Co.,Ltd.
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Beijing Zhiyue Technology Co ltd
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    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
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    • G06Q30/0261—Targeted advertisements based on user location

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Abstract

The invention discloses a method and a device for determining advertisement cheating behaviors and a cloud server, relates to the technical field of advertisements, and can be used for analyzing telecom operator data corresponding to the advertisement behaviors to judge whether the advertisement cheating behaviors exist or not and improve the accuracy of advertisement cheating behavior analysis. The method comprises the following steps: acquiring telecom operator data corresponding to the advertisement behaviors; extracting characteristic data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule; and determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules. The invention is suitable for advertisement activity analysis.

Description

Method and device for determining advertisement cheating behaviors and cloud server
Technical Field
The invention relates to the technical field of advertisements, in particular to a method and a device for determining advertisement cheating behaviors and a cloud server.
Background
With the development of Information Technology (IT) and intelligent terminals, and the combination of the advertising industry and the Information Technology, the market scale of the internet online advertising industry is getting larger and larger, and in addition to displaying advertisements, other behaviors such as consumption recommendation and commercial behavior guidance for different audiences according to user characteristic analysis also belong to online advertising behaviors. The online advertisement is popular with advertisers due to the advantages of various forms, accurate matching, payment according to quantity and the like, but the online advertisement system has more and more involved links, and the advertisers are difficult to objectively and accurately evaluate the advertisement effect, so that a large amount of advertisement cheating phenomena occur. The method of flow counterfeiting, program virtual operation and the like pretends to be normal manual operation and cheats the advertising cost, the percentage of counterfeit data in some advertising services reaches more than 80%, and great loss is caused to advertisers.
In order to prevent cheating and reduce loss, at present, an advertiser can analyze and judge advertisement activities by using advertisement data and behaviors collected by an advertisement platform to evaluate whether the advertisement activities are false advertisement activities simulating normal people operation. Specifically, whether the advertisement cheating behavior exists can be judged based on the collected terminal data of the advertisement behavior user. However, the control right of the terminal is not on the side of the advertiser, the terminal information can be forged at will after the control right of the terminal is obtained, and meanwhile, more and more safety software is provided at present, so that the permission of the advertisement platform for reading the terminal information is limited, the situation of misjudgment is easy to occur, and the accuracy of the analysis of the cheating behaviors of the advertisement is influenced.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, and a cloud server for determining an advertisement cheating behavior, and mainly aims to solve the problems that the control right of a terminal is not on the side of an advertiser at present, terminal information can be forged at will after the control right of the terminal is obtained, and meanwhile, more and more security software is provided at present, and the permission of an advertisement platform for reading the terminal information is limited, so that misjudgment is easily caused, and the accuracy of analysis of the advertisement cheating behavior is affected.
According to an aspect of the present invention, there is provided a method of determining advertisement cheating behavior, the method including:
acquiring telecom operator data corresponding to the advertisement behaviors;
extracting characteristic data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule;
and determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules.
Preferably, the extracting the feature data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule specifically includes:
extracting terminal access position information and corresponding access time information when the user terminal of the advertising behavior accesses the telecom operator service equipment from the telecom operator data;
detecting whether a user mobile terminal with a moving range smaller than a preset range threshold exists in a preset time according to the terminal access position information and the access time information, wherein the user mobile terminal has a plurality of different advertisement access behaviors; and/or
Detecting whether a plurality of user mobile terminals with the same position change tracks exist or not;
and if a plurality of user mobile terminals with the same position change tracks exist and/or the user mobile terminals exist within a preset time, determining that the advertisement activity abnormal behaviors exist.
Preferably, the extracting the feature data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule specifically includes:
extracting user terminal internet access record list information of the advertisement behavior from the telecom operator data;
according to the online record list information, counting the ratio of the access advertisement flow of the user terminal of the advertisement behavior in all flows within a preset time period and/or unit time;
detecting whether the ratio of the access advertisement flow in all flows is larger than a preset ratio threshold value or not;
if yes, determining that the advertisement activity abnormal behavior exists.
Preferably, the extracting the feature data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule specifically includes:
extracting user terminal internet flow detailed record information of the advertisement behavior from the telecom operator data;
detecting whether the flow information of websites or applications related to the advertisement page exists before and after the access record of the advertisement page according to the internet surfing flow detailed record information;
if not, determining that the abnormal behavior of the advertising activity exists.
Preferably, the extracting the feature data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule specifically includes:
extracting terminal identification information of a user terminal of an advertising behavior from the telecom operator data;
inquiring terminal information of a user terminal of the advertising behavior according to the terminal identification information, wherein the terminal information comprises but is not limited to model information, factory time information, place of production information and factory batch information;
detecting whether a plurality of cheating terminals with the same or similar terminal information exist or not, wherein the number of the cheating terminals is larger than a preset number threshold value;
and if so, determining that the abnormal behavior of the advertising activity exists.
Preferably, before determining that there is an ad campaign exception if any, the method further comprises:
extracting terminal access position information and corresponding access time information of a user terminal of an advertising behavior when accessing telecommunication operator service equipment from the telecommunication operator data;
if yes, determining that the abnormal behavior of the advertisement activity exists, specifically comprising:
and if a plurality of cheating terminals exist, comprehensively determining whether the advertisement activity abnormal behavior exists or not by combining the terminal access position information and the access time information.
Preferably, if there are a plurality of the cheating terminals, comprehensively determining whether there is an advertisement activity abnormal behavior by combining the terminal access location information and the access time information, specifically including:
if a plurality of cheating terminals with the same or similar terminal information exist in the terminals of the same advertising campaign, the terminal access position information of the cheating terminals is in the same position range, and the access time information of the cheating terminals is in the same time range, the advertising campaign abnormal behavior is determined to exist.
Preferably, the extracting the feature data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule specifically includes:
extracting international mobile equipment identification code IMEI code or MAC address of the user terminal of the advertising behavior and service number information from the telecom operator data;
detecting whether the IMEI code or the MAC address and the service number information are registered uniquely on the network; and/or
Detecting whether the corresponding service number conversion number of the IMEI code or the MAC address in a preset time period is greater than a preset threshold value or not; and/or
Detecting whether the IMEI code or MAC address conversion number of the service number corresponding to the IMEI code or MAC address in a preset time period is greater than a preset threshold value; and/or
Detecting whether the IMEI code or the MAC address is consistent with the IMEI code or the MAC address of the advertising behavior terminal collected from terminal data;
if the inconsistency is detected, and/or the equipment unique identification information and the service number information are registered on the network to be not unique, and/or the service number conversion quantity is larger than a preset threshold value, and/or the IMEI code or MAC address conversion quantity is larger than a preset threshold value, determining that the abnormal behavior of the advertisement activity exists.
Preferably, the extracting the feature data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule specifically includes:
extracting user profile information of the advertising behavior from the telecom operator data;
detecting whether the advertisement behavior user with the advertisement activity times larger than a preset threshold is a server user or not according to the user data information; and/or
If the times of carrying out the same advertisement activities by the advertisement behavior users with the same IP address or the similar IP addresses are larger than a preset time threshold value, detecting whether the advertisement behavior users with the same IP address or the similar IP addresses are collective internet surfing users or not according to the user information; and/or
Detecting whether the advertisement behavior users accessing the same advertisement are the same user or the user with the account opening time interval smaller than the preset interval threshold value according to the user data information; and/or
Detecting whether the advertisement behavior users accessing the same advertisement are users with registered network access user names close to each other or users with network access addresses close to each other or not according to the user information;
when the advertising behavior user with the advertising activity times larger than the preset threshold is detected to be a server user, and/or the advertising behavior user with the same IP address or the similar IP address is not a collective internet user, and/or the advertising behavior user accessing the same advertisement is the same user or the user with the account opening time interval smaller than the preset interval threshold, and/or the advertising behavior user accessing the same advertisement is a user with the name similar to that of the registered internet user or the internet address similar to that of the registered internet user, determining that the advertising activity abnormal behavior exists.
Preferably, the extracting the feature data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule specifically includes:
extracting communication activity information of advertisement behaviors from the telecom operator data, wherein the communication activity information comprises but is not limited to average network access duration information, average call duration information and average communication service consumption information;
detecting whether the communication activity of the advertising behavior is abnormal or not according to the communication activity information;
if yes, determining that the advertisement activity abnormal behavior exists.
Preferably, the determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules specifically includes:
respectively configuring respective corresponding weights for the verification analysis results under different preset verification rules;
calculating scores respectively corresponding to the verification analysis results under different preset verification rules;
multiplying each item score by the corresponding weight, and adding to obtain an average value;
comparing the average value with a preset standard value;
and if the difference between the average value and a preset standard value is larger than a preset threshold value, determining that the advertising cheating behavior exists.
Preferably, the determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules specifically includes:
acquiring the proportion of the verification analysis results of the abnormal behaviors of the advertisement activities according to the verification analysis results under different preset verification rules;
detecting whether the ratio is larger than a preset ratio threshold value or not;
if yes, determining that the advertisement cheating behavior exists.
Preferably, after determining that the advertising cheating action exists, the method further includes:
acquiring advertisement information with advertisement cheating behaviors and corresponding cheating user and/or cheating terminal information;
storing the cheating user and/or cheating terminal information in a blacklist; and
and generating analysis report information of the advertisement cheating activities according to the advertisement information with the advertisement cheating behaviors, the cheating users and the cheating terminal information.
Preferably, the method further comprises:
counting position information corresponding to the cheating user and/or the cheating terminal information and historical movement track information;
generating analysis report information of the advertisement cheating activities according to the advertisement information with the advertisement cheating behaviors, the cheating users and the cheating terminal information, and specifically comprising the following steps:
and generating analysis report information of the advertisement cheating activities according to the advertisement information with the advertisement cheating behaviors, the cheating users and the cheating terminal information and by combining the position information and the historical movement track information.
According to another aspect of the present invention, there is provided an apparatus for determining advertising cheating behavior, the apparatus comprising:
the acquisition unit is used for acquiring telecommunication operator data corresponding to the advertisement behaviors;
the analysis unit is used for extracting characteristic data corresponding to a preset check rule from the telecom operator data and carrying out check analysis by combining the preset check rule;
and the determining unit is used for determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules.
Preferably, the analysis unit is specifically configured to extract, from the telecommunications carrier data, terminal access location information and corresponding access time information when the user terminal of the advertisement behavior accesses the telecommunications carrier service device;
detecting whether a user mobile terminal with a moving range smaller than a preset range threshold exists in a preset time according to the terminal access position information and the access time information, wherein the user mobile terminal has a plurality of different advertisement access behaviors; and/or
Detecting whether a plurality of user mobile terminals with the same position change tracks exist or not;
and if a plurality of user mobile terminals with the same position change tracks exist and/or the user mobile terminals exist within a preset time, determining that the advertisement activity abnormal behaviors exist.
Preferably, the analysis unit is specifically configured to extract internet access record list information of the user terminal of the advertisement behavior from the data of the telecommunications carrier;
according to the online record list information, counting the ratio of the access advertisement flow of the user terminal of the advertisement behavior in all flows within a preset time period and/or unit time;
detecting whether the ratio of the access advertisement flow in all flows is larger than a preset ratio threshold value or not;
if yes, determining that the advertisement activity abnormal behavior exists.
Preferably, the analysis unit is specifically configured to extract detailed record information of internet traffic of the user terminal of the advertisement behavior from the data of the telecommunications carrier;
detecting whether the flow information of websites or applications related to the advertisement page exists before and after the access record of the advertisement page according to the internet surfing flow detailed record information;
if not, determining that the abnormal behavior of the advertising activity exists.
Preferably, the analysis unit is specifically configured to extract terminal identification information of a user terminal of an advertisement behavior from the telecommunications carrier data;
inquiring terminal information of a user terminal of the advertising behavior according to the terminal identification information, wherein the terminal information comprises but is not limited to model information, factory time information, place of production information and factory batch information;
detecting whether a plurality of cheating terminals with the same or similar terminal information exist or not, wherein the number of the cheating terminals is larger than a preset number threshold value;
and if so, determining that the abnormal behavior of the advertising activity exists.
Preferably, the analysis unit is further configured to extract, from the telecommunications carrier data, terminal access location information when the user terminal of the advertising behavior accesses the telecommunications carrier service device, and corresponding access time information;
and if a plurality of cheating terminals exist, comprehensively determining whether the advertisement activity abnormal behavior exists or not by combining the terminal access position information and the access time information.
Preferably, the analysis unit is further specifically configured to determine that an advertisement campaign abnormal behavior exists if a plurality of cheating terminals having the same or similar terminal information exist in the terminals of the same advertisement campaign, the terminal access location information of the plurality of cheating terminals is within the same location range, and the access time information of the plurality of cheating terminals is within the same time range.
Preferably, the analysis unit is further specifically configured to extract an international mobile equipment identity IMEI code or a MAC address of the user terminal of the advertising behavior and service number information from the telecommunications carrier data;
detecting whether the IMEI code or the MAC address and the service number information are registered uniquely on the network; and/or
Detecting whether the corresponding service number conversion number of the IMEI code or the MAC address in a preset time period is greater than a preset threshold value or not; and/or
Detecting whether the IMEI code or MAC address conversion number of the service number corresponding to the IMEI code or MAC address in a preset time period is greater than a preset threshold value; and/or
Detecting whether the IMEI code or the MAC address is consistent with the IMEI code or the MAC address of the advertising behavior terminal collected from terminal data;
and if the inconsistency is detected, and/or the IMEI code or the MAC address is not unique registered on the network, and/or the service number conversion quantity is greater than a preset threshold value, and/or the IMEI code or the MAC address conversion quantity is greater than a preset threshold value, determining that the abnormal behavior of the advertising activity exists.
Preferably, the analysis unit is further configured to extract user profile information of the advertisement behavior from the telecom operator data;
detecting whether the advertisement behavior user with the advertisement activity times larger than a preset threshold is a server user or not according to the user data information; and/or
If the times of carrying out the same advertisement activities by the advertisement behavior users with the same IP address or the similar IP addresses are larger than a preset time threshold value, detecting whether the advertisement behavior users with the same IP address or the similar IP addresses are collective internet surfing users or not according to the user information; and/or
Detecting whether the advertisement behavior users accessing the same advertisement are the same user or the user with the account opening time interval smaller than the preset interval threshold value according to the user data information; and/or
Detecting whether the advertisement behavior users accessing the same advertisement are users with registered network access user names close to each other or users with network access addresses close to each other or not according to the user information;
when the advertising behavior user with the advertising activity times larger than the preset threshold is detected to be a server user, and/or the advertising behavior user with the same IP address or the similar IP address is not a collective internet user, and/or the advertising behavior user accessing the same advertisement is the same user or the user with the account opening time interval smaller than the preset interval threshold, and/or the advertising behavior user accessing the same advertisement is a user with the name similar to that of the registered internet user or the internet address similar to that of the registered internet user, determining that the advertising activity abnormal behavior exists.
Preferably, the analysis unit is further specifically configured to extract communication activity information of the advertisement behavior from the telecommunications carrier data, where the communication activity information includes, but is not limited to, average network access duration information, average call duration information, and average communication service consumption information;
detecting whether the communication activity of the advertising behavior is abnormal or not according to the communication activity information;
if yes, determining that the advertisement activity abnormal behavior exists.
Preferably, the determining unit is specifically configured to configure respective corresponding weights for the verification analysis results under different preset verification rules;
calculating scores respectively corresponding to the verification analysis results under different preset verification rules;
multiplying each item score by the corresponding weight, and adding to obtain an average value;
comparing the average value with a preset standard value;
and if the difference between the average value and a preset standard value is larger than a preset threshold value, determining that the advertising cheating behavior exists.
Preferably, the determining unit is specifically configured to obtain a ratio of the verification analysis results of the abnormal behavior of the advertisement campaign according to the verification analysis results under different preset verification rules;
detecting whether the ratio is larger than a preset ratio threshold value or not;
if yes, determining that the advertisement cheating behavior exists.
Preferably, the apparatus further comprises: a saving unit and a generating unit;
the acquisition unit is also used for acquiring advertisement information with advertisement cheating behaviors and corresponding cheating user and/or cheating terminal information;
the storage unit is used for storing the cheating user and/or the cheating terminal information in a blacklist;
and the generating unit is used for generating analysis report information of the advertising cheating activities according to the advertising information with the advertising cheating behaviors, the cheating users and the cheating terminal information.
Preferably, the apparatus further comprises: a counting unit;
the statistical unit is used for counting the position information corresponding to the cheating user and/or the cheating terminal information and the historical movement track information;
and the generating unit is specifically used for generating analysis report information of the advertising cheating activities according to the advertising information with the advertising cheating behaviors, the cheating users and the cheating terminal information and by combining the position information and the historical movement track information.
According to yet another aspect of the present invention, there is provided a storage device having stored thereon a computer program that, when executed by a processor, implements the above-described method of determining advertising cheating behavior.
According to still another aspect of the present invention, there is provided a cloud server, including a storage device, a processor, and a computer program stored on the storage device and executable on the processor, where the processor implements the method for determining advertisement cheating behaviors.
By means of the technical scheme, compared with the mode of judging whether the advertising cheating behavior exists or not based on the collected data of the clicking advertising user terminal, the method, the device and the cloud server for determining the advertising cheating behavior can judge whether the advertising cheating behavior exists or not based on the analysis of the telecommunication operator data corresponding to the advertising behavior.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart illustrating a method for determining advertisement cheating behavior according to an embodiment of the present invention;
fig. 2 is a schematic virtual structure diagram of an apparatus for determining advertisement cheating behaviors, according to an embodiment of the present invention;
fig. 3 is a schematic virtual structure diagram of another apparatus for determining advertisement cheating behaviors, according to an embodiment of the present invention;
fig. 4 shows an entity structural diagram of a cloud server provided by an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the invention provides a method for determining advertisement cheating behaviors, which can realize that whether the advertisement cheating behaviors exist or not can be judged by analyzing telecom operator data corresponding to the advertisement behaviors and the accuracy of advertisement cheating behavior analysis can be improved, and as shown in figure 1, the method comprises the following steps:
101. and acquiring telecommunication operator data corresponding to the advertisement behaviors.
The telecom operator may refer to an enterprise providing telecom services such as telephony and internet access for users, such as small campus network operators, Wireless-Fidelity (WIFI) network service providers, virtual operators, and the like. The telecom operator data may include terminal access position information, access time information, user call information, internet access record information, network registration record information, used terminal information, and the like when the user terminal accesses the telecom operator service device.
The execution subject of the embodiment of the invention can be a device for analyzing the advertising activity, can provide services for advertisers, and can accurately analyze whether the advertising cheating behaviors exist or not. When the advertisement activity analysis is needed, the telecommunication operator data corresponding to the recorded advertisement behavior can be obtained from the server of the telecommunication operator for analysis.
102. And extracting characteristic data corresponding to a preset check rule from the obtained telecom operator data, and performing check analysis by combining the preset check rule.
The preset check rules can be preset by technicians according to actual service conditions of the false advertisement behaviors, the number of the preset check rules can be multiple, and it needs to be explained that the more comprehensive the check rules are, the more accurate the analysis result is obtained.
In this embodiment, which feature data to extract from the telecom operator data may be determined according to the content of the preset check rule, for example, if the preset check rule is to detect whether an International Mobile Equipment Identity (IMEI) of a terminal used by a user for an advertisement activity really exists, if the preset check rule is a false IMEI code, it is determined that an advertisement activity abnormal behavior exists, and correspondingly, the IMEI code of the user terminal for the advertisement behavior may be extracted from the telecom operator data as the feature data.
103. And determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules.
In this embodiment, after the verification analysis results under different preset verification rules are obtained, comprehensive analysis may be performed, and a specific comprehensive analysis manner may be determined according to actual requirements, for example, analysis and judgment are performed by using a preconfigured comprehensive analysis formula; analyzing the possibility of the existence of the advertisement cheating behaviors, and if the possibility is more than a certain percentage, indicating that the advertisement cheating behaviors exist; if the probability of the existence of the advertisement cheating behaviors is analyzed to be very small through comprehensive analysis, the advertisement cheating behaviors can be ignored.
Compared with the mode of judging whether the advertising cheating action exists or not based on the collected click advertising user terminal data, the method for determining the advertising cheating action can judge whether the advertising cheating action exists or not based on the analysis of the telecommunication operator data corresponding to the advertising action, can improve the accuracy of the analysis of the advertising cheating action, and meanwhile, based on the reasons of charging safety and the like, communication, internet access records, network registration records, position information, terminal information and the like need to be stored.
Further, as refinement and expansion of the specific implementation of the above embodiment, taking different preset check rules as examples, the implementation process of step 102 is specifically described in different angles, where in an optional embodiment of the present invention, step 102 may specifically include: extracting terminal access position information and corresponding access time information when a user terminal of an advertising behavior is accessed to telecommunication operator service equipment from the obtained telecommunication operator data; detecting whether a user mobile terminal with a moving range smaller than a preset range threshold exists in a preset time period or not according to the extracted terminal access position information and access time information, wherein the user mobile terminal has a plurality of different advertisement access behaviors; and/or detecting whether a plurality of user mobile terminals with the same position change track exist or not; and if a plurality of user mobile terminals with the same position change tracks exist and/or the user mobile terminals exist within a preset time, determining that the advertisement activity abnormal behaviors exist.
The terminal access position information can be obtained by determining the physical position of a user according to the access device information (such as a common mobile phone) after the terminal is accessed to the service device (such as an access device such as a base station, a wireless access point, a signal transmitting device, a fixed cross-connecting box and the like) of an operator, and calculating the position of the mobile phone through the position of the terminal registered in the base station network; for example, a Wireless Access Point (AP) of WIFI, the location range may also be analyzed according to the signal coverage of the AP and the information of the terminal logging in the AP. The access time information may be time information when the user terminal of the advertisement action accesses the telecom operator service device. The preset time and the preset range threshold value can be preset according to actual requirements.
For example, for a mobile phone terminal, normally, the mobile phone terminal needs to move frequently because a person using the mobile phone will move frequently, if the mobile phone terminal is frequently involved in an advertisement-clicking campaign within two months, but the mobile phone terminal is only used under the same base station within the two months, the position is not changed, which is very abnormal, and is likely to be a machine specially used for brushing advertisements, because it is determined that there is an abnormal behavior of the advertisement campaign.
For another example, some cheaters may move the mobile phone terminals to simulate real users, but only move a plurality of mobile phone terminals at the same time due to cost saving and easy management, so that the position change tracks of the mobile phone terminals are the same, and through the verification and analysis process, if a plurality of mobile phone terminals with the same position change track exist and all the mobile phone terminals frequently participate in advertisement clicking activities, the mobile phone terminals are likely to be machines specially used for brushing advertisements, and because a plurality of people using the mobile phone terminals cannot be together all day long, the situation is also easy to judge that abnormal behaviors of the advertisement activities exist; on the contrary, one mobile phone terminal is moved and used at ordinary times, and only occasionally generates an advertising behavior, and then can be judged as a normal behavior.
In another optional embodiment of the present invention, step 102 may specifically include: extracting Internet surfing record list information of the advertising behavior terminal from the obtained telecom operator data; according to the extracted internet record list information, counting the ratio of the access advertisement flow of the user terminal of the advertisement behavior in all the flows within a preset time period and/or unit time; then detecting whether the ratio of the access advertisement flow in all the flows is larger than a preset ratio threshold value or not; if yes, determining that the advertisement activity abnormal behavior exists.
Wherein, the internet record list information may include: access key information and network Protocol (IP) address information, etc.; the preset time period, the unit time and the preset ratio threshold value can be configured in advance according to actual requirements. For example, according to the information such as keywords and network IP, daily accumulation can be used to distinguish that the advertisement content in the user traffic is approximately occupied, a certain period of time is taken, for example, the user has 10KB traffic in a certain hour, where 8K is the advertisement traffic, which is obviously too high, indicating that the user does not do other things, only opens the advertisement page, and is likely to perform the operation of brushing the advertisement click rate, thus determining that there is an abnormal behavior of the advertisement activity.
For another example, through statistical analysis, if the advertisement traffic ratio is too high, or the traffic ratio is too high in a unit time, it may be determined that the advertisement traffic ratio is abnormal, and if the owner intentionally cheats the advertisement traffic ratio, the advertisement traffic ratio should be malicious traffic generated by a virus, so that it is determined that there is an abnormal behavior of the advertisement campaign.
In yet another optional embodiment of the present invention, step 102 may specifically include: extracting user terminal internet access flow detailed record information of advertisement behaviors from the acquired telecom operator data; detecting whether the flow information of websites or applications related to the advertisement page exists before and after the access record of the advertisement page according to the extracted internet surfing flow detailed record; if not, determining that the abnormal behavior of the advertising activity exists.
For example, if the advertisement is a web advertisement, a user generally needs to browse a web page to open a related advertisement, and generally continues to open other links, if the advertisement is a built-in advertisement such as an Application (APP), data traffic to a specific IP address before and after the advertisement should occur, and in any case, unless the advertisement is pushed by an operator, most of the advertisements have leading and following operations, and if the characteristics of a terminal of an advertisement behavior are obvious, the advertisement behavior is very suspicious, and it can be determined that there is an advertisement activity abnormal behavior.
In yet another optional embodiment of the present invention, step 102 may specifically include: extracting terminal identification information of a user terminal of an advertising behavior from the acquired telecom operator data; inquiring the terminal information of the user terminal of the advertisement behavior according to the extracted terminal identification information; detecting whether a plurality of cheating terminals with the same or similar terminal information exist or not, wherein the number of the cheating terminals is larger than a preset number threshold value; and if so, determining that the abnormal behavior of the advertising activity exists.
The terminal information includes, but is not limited to, model information, factory time information, place of production information, factory batch information, and the like; the terminal identification information may include information such as an IMEI number, a MAC address, etc. of the terminal.
For example, by analyzing the information such as IMEI and MAC address of the user terminal of the advertisement activity collected in the database of the telecom operator, the information such as the model, the factory time, and the production place of the device can be analyzed, and if the device information is very consistent with the terminal of a certain batch of advertisement activities, the device may be a cheating terminal dedicated to the brushing amount purchased in batch.
According to the content of the above optional embodiment, in order to make the analysis result more accurate, the integrated judgment of the network access time, the location information, and the like of the user terminal of the advertisement behavior may be combined, so before determining that there is an abnormal behavior of the advertisement activity, the method may further include: extracting terminal access position information and corresponding access time information of a user terminal of an advertising behavior when the user terminal is accessed to telecommunication operator service equipment from the obtained telecommunication operator data; correspondingly, if a plurality of cheating terminals exist, whether the abnormal behavior of the advertising activity exists or not is comprehensively determined by combining the terminal access position information and the access time information. And further, whether the abnormal behaviors of the advertising activities exist can be more accurately analyzed through the multi-aspect comprehensive analysis mode.
Specifically, the above comprehensively determining whether there is an abnormal behavior of the advertisement campaign may specifically include: if a plurality of cheating terminals with the same or similar terminal information exist in the terminals of the same advertising campaign, the terminal access position information of the cheating terminals is in the same position range, and the access time information of the cheating terminals is in the same time range, it is determined that an advertising campaign abnormal behavior exists.
For example, a large number of terminals in a certain advertisement activity are found to be devices of the same model and the same delivery time, the positions are very fixed, and the network access time and the customer information are relatively concentrated, so that the possibility of cheating is very high, and the existence of abnormal behaviors of the advertisement activity can be determined; or the IMEI number and the MAC address are found to be very strong in regularity, and as before, the sequence of only one or two bits behind is not normal.
In yet another optional embodiment of the present invention, step 102 may specifically include: extracting IMEI codes or MAC addresses of the advertising behavior terminals and service number information from the acquired telecom operator data; detecting whether the extracted IMEI code or MAC address and service number information is unique registered on the network; and/or detecting whether the corresponding service number conversion number of the IMEI code or the MAC address in a preset time period is greater than a preset threshold value; and/or detecting whether the IMEI code or MAC address conversion number of the service number corresponding to the IMEI code or MAC address information in a preset time period is greater than a preset threshold value; and/or detecting whether the IMEI code or the MAC address is consistent with the IMEI code or the MAC address of the advertising behavior terminal collected from the terminal data; if the inconsistency is detected, and/or the IMEI code or the MAC address and the service number information are not registered uniquely on the network, and/or the service number conversion quantity is greater than a preset threshold, and/or the IMEI code or the MAC address conversion quantity is greater than a preset threshold, determining that the advertisement activity abnormal behavior exists.
The service number may be a mobile phone number, an internet access terminal number, or the like. For example, the IMEI number of the terminal has uniqueness, and the IMEI number obtained by collecting user information through the terminal side in the past is controlled by the terminal authority, sometimes cannot be obtained, sometimes may be modified, but is very accurate when collected through the communication network side, and the terminal side cannot be controlled; the IMEI number of the user terminal of the advertisement behavior collected by the communication network side is taken as a reference, if the IMEI number is not registered uniquely on the network, the IMEI number is illegal, the fact that the user terminal is possibly a false hypothesis standby for refreshing the advertisement click volume is shown, and the fact that the advertisement activity abnormal behavior exists can be determined.
For another example, the IMEI number and the mobile phone number determine a corresponding relationship, and if it is found that the IMEI number is frequently changed for a certain mobile phone number or the mobile phone number is frequently changed for a certain IMEI number, it indicates that the mobile phone number is abnormal, it may be determined that there is an abnormal behavior of the advertisement campaign.
For another example, if the IMEI number of the advertising campaign terminal collected by the communication network side is not consistent with the IMEI number of the advertising campaign terminal collected by the terminal side, it also indicates that there is a false problem, and it can be determined that there is an abnormal behavior of the advertising campaign.
In yet another optional embodiment of the present invention, step 102 may specifically include: extracting user data information of advertisement behavior users from the obtained telecom operator data; detecting whether the advertisement behavior user with the advertisement activity times larger than a preset threshold is a server user or not according to the extracted user data information; and/or if the times of the same advertisement activities performed by the advertisement behavior users with the same IP address or the similar IP addresses are larger than a preset time threshold value, detecting whether the advertisement behavior users with the same IP address or the similar IP addresses are collective internet access users or not according to the user information; and/or detecting whether the advertisement behavior users accessing the same advertisement are the same user or the user with the account opening time interval smaller than the preset interval threshold value according to the user profile information; and/or detecting whether the advertisement behavior users accessing the same advertisement are users with the same registered network access user names or the network access addresses according to the user information; when it is detected that the advertising behavior users who perform the advertising activities for a number of times greater than a preset threshold are server users, and/or the advertising behavior users of the same IP address or similar IP addresses are not collective internet users, and/or the advertising behavior users who visit the same advertisement are the same users or users whose account opening time interval is less than a preset interval threshold, and/or the advertising behavior users who visit the same advertisement are users whose registered internet users are similar in name or internet addresses, it is determined that an advertising activity abnormal behavior exists.
The user profile information may include related data of the user, such as user property, user name, identification document number, and the like. At the telecommunication operator at the communication network side, user data can be input when the user accesses the network, and particularly after a real-name system is adopted, the user data is more accurate, so that the judgment of whether the abnormal behavior of the advertising activity exists or not based on the user data information is more accurate.
At present, whether the advertisement activity is a false advertisement activity can be analyzed by accessing an IP address, under the normal condition, the number of terminals under the same IP address is limited, and if the number of times of performing the same advertisement activity on the same IP or similar IP sections is too large and the terminals are too concentrated, the advertisement activity is suspicious. However, in this case, there may be some visiting advertisement users of a large enterprise or a large event venue, and therefore it is not accurate to determine whether the visiting advertisement users are false advertisement activities in this way. For example, if the number of times of performing the same advertisement campaign in the same IP or similar IP segment is too large and too concentrated, it may be detected whether the user in the same IP or similar IP segment is a collective internet user (such as a large enterprise, a shopping mall, an internet cafe, etc.) according to the user profile information in the same IP or similar IP segment, if not, it indicates that there is an abnormality, and if so, it indicates that the user belongs to a normal situation.
For another example, if the user is determined to be a large data room according to the user profile information, if the number of times of the advertisement access activity of the user is greater than a certain number threshold, it indicates that there is an abnormality because the advertisement is rarely accessed on the server.
For another example, according to the user profile information, if the advertisement behavior users accessing the same advertisement are the same person or users with close account opening time, which indicates that the user may intentionally refresh the advertisement behavior, it may be determined that there is an advertisement activity abnormal behavior; or the network access registration names of the users accessing the same advertisement are very close, or the network access addresses are very close, the system can be understood as a batch-open card used for swiping the advertisement click volume.
In yet another optional embodiment of the present invention, step 102 may specifically include: extracting communication activity information of the advertisement behavior from the obtained telecom operator data; then detecting whether the communication activity of the advertising behavior is abnormal or not according to the extracted communication activity information; if yes, determining that the advertisement activity abnormal behavior exists.
The communication activity information includes, but is not limited to, average network access duration information, average call duration information, average communication service consumption information, and the like. Whether the user is a normal user can be analyzed through the communication activity information.
For example, there are some characteristics that it can basically determine that the user of the advertising behavior is a real user, for example, the network access time is long, there are other fees besides the internet traffic in each month, such as call fee, short message fee, etc., and the consumption amount in each month is very large, which indicates that the user of the advertising behavior is a real user, and the activities of the user belong to normal behaviors; on the contrary, if the behaviors such as telephone calls, short messages and the like do not occur all the time after the network is accessed, or the network charge with a certain flow is generated every month, the abnormality is determined, the advertisement behavior is possibly a false user and is used for swiping the click volume of the advertisement, and then the abnormal behavior of the advertisement activity can be determined.
The above optional embodiments may be considered to perform verification analysis by using different preset verification rules according to data of a telecommunication operator, and it should be noted that the preset verification rules may not be limited thereto, and may also be set in advance according to requirements on other services, and the more comprehensive verification rules are used for verification analysis, so that the final analysis result of the obtained advertisement activity is more accurate.
Further, in order to illustrate the specific implementation process of step 103, an optional implementation manner of step 103 is to configure respective corresponding weights for the verification analysis results under different preset verification rules; calculating scores respectively corresponding to the verification analysis results under different preset verification rules; multiplying each item score by the corresponding weight, and adding to obtain an average value; finally, comparing the calculated average value with a preset standard value; and if the difference between the average value and the preset standard value is larger than a preset threshold value, determining that the advertising cheating behavior exists. It should be noted that, the larger the difference between the average value and the preset standard value, the more problematic the problem is, and the specific weight and score can be set according to the situation.
For example, according to the importance of the verification analysis result under each preset verification rule to the final advertisement activity analysis result, respectively configuring respective corresponding weights for the verification analysis results under the preset verification rules, then calculating respective corresponding scores of the verification analysis results under the preset verification rules, specifically, which score interval the result is in, and then determining the corresponding score; and then multiplying each item score by the corresponding weight, adding the weights to obtain an average value, finally comparing the calculated average value with a preset standard value, and determining that the advertising cheating behavior exists if the difference between the average value and the preset standard value is greater than a certain threshold value.
Another optional implementation manner of step 103 is to obtain a ratio of the verification analysis results of the abnormal behavior of the advertisement campaign according to the verification analysis results under different preset verification rules; then detecting whether the ratio is larger than a preset ratio threshold value; if yes, determining that the advertisement cheating behavior exists.
For example, the preset proportion threshold is 75%, the verification analysis obtains the verification analysis results according to 10 different preset verification rules, if 8 verification analysis results indicate that the advertisement activity abnormal behavior exists, the proportion of the verification analysis results of the advertisement activity abnormal behavior is determined to be 80%, and the proportion is larger than the preset proportion threshold, so that the advertisement cheating behavior can be determined.
Further, in order to help the user know which advertisement cheating behaviors appear and which users and terminals participate in the cheating behaviors, so as to be used as a reference for the subsequent settlement of advertisement fees, in yet another optional embodiment of the present invention, after determining that the advertisement cheating behaviors exist, the method may further include: acquiring advertisement information with advertisement cheating behaviors and corresponding cheating user and/or cheating terminal information; storing the information of the cheating users and/or the cheating terminals in a blacklist, and further effectively shielding the cheating users and the cheating terminals by using the blacklist when the advertisement click volume is subsequently counted next time; and generating analysis report information of the advertisement cheating activities according to the advertisement information with the advertisement cheating behaviors, the cheating users and the cheating terminal information.
The analysis report information may be in the form of a graph or a table. For example, after it is determined that there is an advertising cheating action, the data of the advertising activity abnormal action can be deeply analyzed to find out the advertising information of the advertising cheating action and the corresponding information of the cheating user and/or the cheating terminal, and then the analysis report information of the advertising cheating action is generated based on the information, wherein the analysis report information can also include the advertising information aiming at the advertising cheating action, the cheating times of the cheating user and the cheating terminal, and the like.
Further, in order to facilitate subsequent tracking of the cheating users and the cheating terminals, the foregoing optional embodiment may further include: counting position information corresponding to the cheating user and/or the cheating terminal information and historical movement track information; correspondingly, the step of generating the analysis report information of the advertisement cheating activities according to the advertisement information, the cheating users and the cheating terminal information with the advertisement cheating behaviors specifically comprises the following steps: and generating analysis report information of the advertisement cheating activities according to the advertisement information with the advertisement cheating behaviors, the cheating users and the cheating terminal information and by combining the position information and the historical movement track information.
For example, according to the current position and the historical movement track of the cheating user or the cheating terminal, which area the cheating user is going to move to can be judged and tracked, so that the subsequent cheating user or the cheating terminal can be conveniently and quickly distinguished when performing the false advertising activity again in the area.
Further, as a specific implementation of the method shown in fig. 1, an embodiment of the present invention provides an apparatus for determining advertisement cheating behavior, where as shown in fig. 2, the apparatus includes: an acquisition unit 21, an analysis unit 22, a determination unit 23.
An obtaining unit 21, configured to obtain telecommunications carrier data corresponding to an advertisement behavior;
the analysis unit 22 may be configured to extract feature data corresponding to a preset check rule from the telecom operator data, and perform check analysis in combination with the preset check rule;
the determining unit 23 may be configured to determine whether an advertisement cheating action exists according to verification analysis results under different preset verification rules.
In a specific application scenario, the analysis unit 22 may be specifically configured to extract, from the telecommunications carrier data, terminal access location information when a user terminal of an advertisement behavior accesses a telecommunications carrier service device, and corresponding access time information; detecting whether a user mobile terminal with a moving range smaller than a preset range threshold exists in a preset time according to the terminal access position information and the access time information, wherein the user mobile terminal has a plurality of different advertisement access behaviors; and/or detecting whether a plurality of user mobile terminals with the same position change track exist or not; and if a plurality of user mobile terminals with the same position change tracks exist and/or the user mobile terminals exist within a preset time, determining that the advertisement activity abnormal behaviors exist.
In a specific application scenario, the analysis unit 22 may be further configured to extract internet access record list information accessed by the user terminal of the advertisement behavior from the data of the telecommunications carrier; according to the online record list information, counting the ratio of the access advertisement flow of the user terminal of the advertisement behavior in all flows within a preset time period and/or unit time; detecting whether the ratio of the access advertisement flow in all flows is larger than a preset ratio threshold value or not; if yes, determining that the advertisement activity abnormal behavior exists.
In a specific application scenario, the analysis unit 22 may be further configured to extract detailed recording information of user terminal internet traffic of an advertisement behavior from the data of the telecommunications carrier; detecting whether the flow information of websites or applications related to the advertisement page exists before and after the access record of the advertisement page according to the internet surfing flow detailed record information; if not, determining that the abnormal behavior of the advertising activity exists.
In a specific application scenario, the analysis unit 22 may be further configured to extract terminal identification information of a user terminal of an advertisement behavior from the telecom operator data; inquiring terminal information of a user terminal of the advertising behavior according to the terminal identification information, wherein the terminal information comprises but is not limited to model information, factory time information, place of production information and factory batch information; detecting whether a plurality of cheating terminals with the same or similar terminal information exist or not, wherein the number of the cheating terminals is larger than a preset number threshold value; and if so, determining that the abnormal behavior of the advertising activity exists.
In a specific application scenario, the analysis unit 22 may be further configured to extract, from the telecommunications carrier data, terminal access location information when the user terminal of the advertisement behavior accesses the telecommunications carrier service device, and corresponding access time information; and if a plurality of cheating terminals exist, comprehensively determining whether the advertisement activity abnormal behavior exists or not by combining the terminal access position information and the access time information.
In a specific application scenario, the analysis unit 22 may be further configured to determine that an advertisement campaign abnormal behavior exists if a plurality of cheating terminals with the same or similar terminal information exist in the same terminal of the same advertisement campaign, and the terminal access location information of the plurality of cheating terminals is in the same location range, and the access time information of the plurality of cheating terminals is in the same time range.
In a specific application scenario, the analyzing unit 22 may be further configured to extract an IMEI code or a MAC address of the user terminal of the advertisement behavior and service number information from the data of the telecommunications carrier; detecting whether the IMEI code or the MAC address and the service number information are registered uniquely on the network; and/or detecting whether the corresponding service number conversion number of the IMEI code or the MAC address in a preset time period is greater than a preset threshold value; and/or detecting whether the IMEI code or MAC address conversion number of the service number corresponding to the IMEI code or MAC address information in a preset time period is greater than a preset threshold value; and/or detecting whether the IMEI code or the MAC address is consistent with the IMEI code or the MAC address of the advertising behavior terminal collected from terminal data; and if the inconsistency is detected, and/or the IMEI code or the MAC address is not unique registered on the network, and/or the service number conversion quantity is greater than a preset threshold value, and/or the IMEI code or the MAC address conversion quantity is greater than a preset threshold value, determining that the abnormal behavior of the advertising activity exists.
In a specific application scenario, the analysis unit 22 may be further configured to extract user profile information of the advertisement behavior from the telecom operator data; detecting whether the advertisement behavior user with the advertisement activity times larger than a preset threshold is a server user or not according to the user data information; and/or if the times of carrying out the same advertisement activities by the users with the same IP address or the similar IP addresses are larger than a preset time threshold value, detecting whether the users with the same IP address or the similar IP addresses are collective internet users or not according to the user information; and/or detecting whether the advertisement behavior users accessing the same advertisement are the same user or the user with the account opening time interval smaller than the preset interval threshold value according to the user profile information; and/or detecting whether the advertisement behavior users accessing the same advertisement are users with the same registered network access user names or the network access addresses according to the user data information; when the advertising behavior user with the advertising activity times larger than the preset threshold is detected to be a server user, and/or the advertising behavior user with the same IP address or the similar IP address is not a collective internet user, and/or the advertising behavior user accessing the same advertisement is the same user or the user with the account opening time interval smaller than the preset interval threshold, and/or the advertising behavior user accessing the same advertisement is a user with the name similar to that of the registered internet user or the internet address similar to that of the registered internet user, determining that the advertising activity abnormal behavior exists.
In a specific application scenario, the analysis unit 22 may be further configured to extract communication activity information of an advertisement behavior from the telecom operator data, where the communication activity information includes, but is not limited to, average network access duration information, average call duration information, and average communication service consumption information; detecting whether the communication activity of the advertising behavior is abnormal or not according to the communication activity information; if yes, determining that the advertisement activity abnormal behavior exists.
In a specific application scenario, the determining unit 23 may be specifically configured to configure respective corresponding weights for the verification analysis results under different preset verification rules; calculating scores respectively corresponding to the verification analysis results under different preset verification rules; multiplying each item score by the corresponding weight, and adding to obtain an average value; comparing the average value with a preset standard value; and if the difference between the average value and a preset standard value is larger than a preset threshold value, determining that the advertising cheating behavior exists.
In a specific application scenario, the determining unit 23 may be further configured to obtain, according to check analysis results under different preset check rules, a ratio of the check analysis results of the abnormal behavior of the advertisement campaign; detecting whether the ratio is larger than a preset ratio threshold value or not; if yes, determining that the advertisement cheating behavior exists.
In a specific application scenario, in order to help users know which advertisement cheating behaviors appear and which users and terminals participate in the cheating behaviors, so that the subsequent settlement of advertisement fees is used as a reference, as shown in fig. 3, the apparatus further includes: a saving unit 24 and a generating unit 25;
the obtaining unit 21 may be further configured to obtain advertisement information with an advertisement cheating behavior, and corresponding cheating user and/or cheating terminal information;
a saving unit 24, configured to save the cheating user and/or cheating terminal information in a blacklist;
the generating unit 25 may be configured to generate analysis report information of the advertisement cheating activity according to the advertisement information with the advertisement cheating behavior, the cheating user information, and the cheating terminal information.
In a specific application scenario, in order to facilitate subsequent tracking of a cheating user and a cheating terminal, as shown in fig. 3, the apparatus further includes: a counting unit 26;
a counting unit 26, configured to count location information corresponding to the cheating user and/or the cheating terminal information, and historical movement track information;
the generating unit 25 may be specifically configured to generate analysis report information of the advertisement cheating activity according to the advertisement information with the advertisement cheating behavior, the cheating user information, and the cheating terminal information, in combination with the position information and the historical movement track information.
It should be noted that, other corresponding descriptions of the functional units involved in the apparatus for determining advertisement cheating behavior provided in the embodiment of the present invention may refer to the corresponding description in fig. 1, and are not described herein again.
Based on the method shown in fig. 1, correspondingly, the embodiment of the invention further provides a storage device, on which a computer program is stored, and the program, when executed by a processor, implements the method for determining advertising cheating behavior shown in fig. 1.
Based on the method shown in fig. 1, an embodiment of the present invention further provides a cloud server, and as shown in fig. 4, the cloud server includes: a storage device 32 and a processor 31, and a computer program stored on the storage device and executable on the processor, wherein the storage device 32 and the processor 31 are both disposed on a bus 33, and the processor 31 implements the method for determining advertising cheating activities described in fig. 1 when executing the program.
By applying the technical scheme of the invention, the accuracy of advertisement cheating behavior analysis can be improved, wrong counting can be avoided, the user behavior in a certain period before the advertisement behavior occurs can be analyzed, the authenticity of the user can be determined, the judgment can be made more quickly, the advertisement fee does not need to be settled for a period of time so as to observe whether the advertisement cheating behavior is observed, the advertisement activity can be analyzed quickly, and the advertisement period is accelerated.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by hardware, and also by software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.), and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the implementation scenarios of the present application.
Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present application.
Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above application serial numbers are for description purposes only and do not represent the superiority or inferiority of the implementation scenarios.
The above disclosure is only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.

Claims (20)

1. A method of determining advertising cheating activities, comprising:
acquiring telecom operator data corresponding to the advertisement behaviors;
extracting characteristic data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule;
determining whether the advertisement cheating behavior exists according to verification analysis results under different preset verification rules;
extracting characteristic data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule, wherein the method specifically comprises the following steps:
extracting user terminal internet access record list information of the advertisement behavior from the telecom operator data;
according to the online record list information, the ratio of the access advertisement flow of the user terminal of the advertisement behavior in a preset time period and/or unit time in all the flows is counted, and the online record list information comprises: accessing key word information and network protocol address information;
detecting whether the ratio of the access advertisement flow in all flows is larger than a preset ratio threshold value or not;
if yes, determining that abnormal behaviors of the advertisement activities exist;
extracting characteristic data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule, wherein the method specifically comprises the following steps:
extracting terminal identification information of a user terminal of an advertising behavior from the telecom operator data;
inquiring terminal information of a user terminal of the advertising behavior according to the terminal identification information, wherein the terminal information comprises machine type information, factory time information, place of production information and factory batch information;
detecting whether a plurality of cheating terminals with the same or similar terminal information exist or not, wherein the number of the cheating terminals is larger than a preset number threshold value, and if yes, determining that an advertisement activity abnormal behavior exists;
extracting terminal access position information and corresponding access time information of a user terminal of an advertising behavior when accessing telecommunication operator service equipment from the telecommunication operator data;
if yes, determining that the abnormal behavior of the advertisement activity exists, specifically comprising:
if a plurality of cheating terminals exist, comprehensively determining whether an advertisement activity abnormal behavior exists or not by combining the terminal access position information and the access time information, and specifically comprising the following steps: if a plurality of cheating terminals with the same or similar terminal information exist in the terminals of the same advertising campaign, the terminal access position information of the cheating terminals is in the same position range, and the access time information of the cheating terminals is in the same time range, determining that an advertising campaign abnormal behavior exists;
extracting characteristic data corresponding to a preset check rule from the telecom operator data, and performing check analysis by combining the preset check rule, wherein the method specifically comprises the following steps:
extracting international mobile equipment identification code IMEI code or MAC address of the user terminal of the advertising behavior and service number information from the telecom operator data;
detecting whether the IMEI code or the MAC address and the service number information are registered uniquely on the network;
detecting whether the corresponding service number conversion number of the IMEI code or the MAC address in a preset time period is greater than a preset threshold value or not;
detecting whether the IMEI code or MAC address conversion number of the service number corresponding to the IMEI code or MAC address in a preset time period is greater than a preset threshold value;
detecting whether the IMEI code or the MAC address is consistent with the IMEI code or the MAC address of the advertising behavior terminal collected from terminal data;
if the IMEI code or the MAC address and the service number information are not registered uniquely on the network if inconsistency is detected, the service number conversion number is larger than a preset threshold value, and the IMEI code or the MAC address conversion number is larger than the preset threshold value, it is determined that abnormal behaviors of the advertisement activities exist.
2. The method according to claim 1, wherein extracting feature data corresponding to a preset verification rule from the telecom operator data, and performing verification analysis in combination with the preset verification rule specifically includes:
extracting terminal access position information and corresponding access time information when the user terminal of the advertising behavior accesses the telecom operator service equipment from the telecom operator data;
detecting whether a user mobile terminal with a moving range smaller than a preset range threshold exists in a preset time according to the terminal access position information and the access time information, wherein the user mobile terminal has a plurality of different advertisement access behaviors; and/or
Detecting whether a plurality of user mobile terminals with the same position change tracks exist or not;
and if a plurality of user mobile terminals with the same position change tracks exist and/or the user mobile terminals exist within a preset time, determining that the advertisement activity abnormal behaviors exist.
3. The method according to any one of claims 1 to 2, wherein extracting feature data corresponding to a preset check rule from the telecom operator data, and performing a check analysis in combination with the preset check rule specifically includes:
extracting user terminal internet flow detailed record information of the advertisement behavior from the telecom operator data;
detecting whether the flow information of websites or applications related to the advertisement page exists before and after the access record of the advertisement page according to the internet surfing flow detailed record information;
if not, determining that the abnormal behavior of the advertising activity exists.
4. The method according to claim 1, wherein extracting feature data corresponding to a preset verification rule from the telecom operator data, and performing verification analysis in combination with the preset verification rule specifically includes:
extracting user profile information of the advertising behavior from the telecom operator data;
detecting whether the advertisement behavior user with the advertisement activity times larger than a preset threshold is a server user or not according to the user data information; and/or
If the times of carrying out the same advertisement activities by the advertisement behavior users with the same IP address or the similar IP addresses are larger than a preset time threshold value, detecting whether the advertisement behavior users with the same IP address or the similar IP addresses are collective internet surfing users or not according to the user information; and/or
Detecting whether the advertisement behavior users accessing the same advertisement are the same user or the user with the account opening time interval smaller than the preset interval threshold value according to the user data information; and/or
Detecting whether the advertisement behavior users accessing the same advertisement are users with registered network access user names close to each other or users with network access addresses close to each other or not according to the user information;
when the advertising behavior user with the advertising activity times larger than the preset threshold is detected to be a server user, and/or the advertising behavior user with the same IP address or the similar IP address is not a collective internet user, and/or the advertising behavior user accessing the same advertisement is the same user or the user with the account opening time interval smaller than the preset interval threshold, and/or the advertising behavior user accessing the same advertisement is a user with the name similar to that of the registered internet user or the internet address similar to that of the registered internet user, determining that the advertising activity abnormal behavior exists.
5. The method according to claim 1, wherein extracting feature data corresponding to a preset verification rule from the telecom operator data, and performing verification analysis in combination with the preset verification rule specifically includes:
extracting communication activity information of advertisement behaviors from the telecom operator data, wherein the communication activity information comprises average network access duration information, average call duration information and average communication service consumption information;
detecting whether the communication activity of the advertising behavior is abnormal or not according to the communication activity information;
if yes, determining that the advertisement activity abnormal behavior exists.
6. The method according to claim 1, wherein the determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules specifically comprises:
respectively configuring respective corresponding weights for the verification analysis results under different preset verification rules;
calculating scores respectively corresponding to the verification analysis results under different preset verification rules;
multiplying each item score by the corresponding weight, and adding to obtain an average value;
comparing the average value with a preset standard value;
and if the difference between the average value and a preset standard value is larger than a preset threshold value, determining that the advertising cheating behavior exists.
7. The method according to claim 1, wherein the determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules specifically comprises:
acquiring the proportion of the verification analysis results of the abnormal behaviors of the advertisement activities according to the verification analysis results under different preset verification rules;
detecting whether the ratio is larger than a preset ratio threshold value or not;
if yes, determining that the advertisement cheating behavior exists.
8. The method of claim 6 or 7, wherein after determining that advertising cheating action exists, the method further comprises:
acquiring advertisement information with advertisement cheating behaviors and corresponding cheating user and/or cheating terminal information;
storing the cheating user and/or cheating terminal information in a blacklist; and
and generating analysis report information of the advertisement cheating activities according to the advertisement information with the advertisement cheating behaviors, the cheating users and the cheating terminal information.
9. The method of claim 8, further comprising:
counting position information corresponding to the cheating user and/or the cheating terminal information and historical movement track information;
generating analysis report information of the advertisement cheating activities according to the advertisement information with the advertisement cheating behaviors, the cheating users and the cheating terminal information, and specifically comprising the following steps:
and generating analysis report information of the advertisement cheating activities according to the advertisement information with the advertisement cheating behaviors, the cheating users and the cheating terminal information and by combining the position information and the historical movement track information.
10. An apparatus for determining advertising cheating activities, comprising:
the acquisition unit is used for acquiring telecommunication operator data corresponding to the advertisement behaviors;
the analysis unit is used for extracting characteristic data corresponding to a preset check rule from the telecom operator data and carrying out check analysis by combining the preset check rule;
the determining unit is used for determining whether the advertisement cheating behavior exists according to the verification analysis results under different preset verification rules;
the analysis unit is specifically used for extracting internet access record list information of the user terminal of the advertisement behavior from the telecom operator data; according to the online record list information, the ratio of the access advertisement flow of the user terminal of the advertisement behavior in a preset time period and/or unit time in all the flows is counted, and the online record list information comprises: accessing key word information and network protocol address information; detecting whether the ratio of the access advertisement flow in all flows is larger than a preset ratio threshold value or not; if yes, determining that abnormal behaviors of the advertisement activities exist;
the analysis unit is specifically configured to extract terminal identification information of a user terminal of an advertisement behavior from the telecom operator data; inquiring terminal information of a user terminal of the advertising behavior according to the terminal identification information, wherein the terminal information comprises machine type information, factory time information, place of production information and factory batch information; detecting whether a plurality of cheating terminals with the same or similar terminal information exist or not, wherein the number of the cheating terminals is larger than a preset number threshold value; if so, determining that the abnormal behavior of the advertising activity exists;
the analysis unit is specifically further configured to extract, from the telecom operator data, terminal access location information when the user terminal of the advertisement behavior accesses the telecom operator service device, and corresponding access time information; if a plurality of the cheating terminals exist, comprehensively determining whether the abnormal behavior of the advertising activity exists or not by combining the terminal access position information and the access time information,
the analysis unit is specifically configured to determine that an advertisement campaign abnormal behavior exists if multiple cheating terminals with the same or similar terminal information exist in terminals of the same advertisement campaign, terminal access position information of the multiple cheating terminals is in the same position range, and access time information of the multiple cheating terminals is in the same time range;
the analysis unit is specifically further configured to extract an International Mobile Equipment Identity (IMEI) code or a Media Access Control (MAC) address of the user terminal of the advertisement behavior and service number information from the telecom operator data; detecting whether the IMEI code or the MAC address and the service number information are registered uniquely on the network; detecting whether the corresponding service number conversion number of the IMEI code or the MAC address in a preset time period is greater than a preset threshold value or not; detecting whether the IMEI code or MAC address conversion number of the service number corresponding to the IMEI code or MAC address in a preset time period is greater than a preset threshold value; detecting whether the IMEI code or the MAC address is consistent with the IMEI code or the MAC address of the advertising behavior terminal collected from terminal data; if the IMEI code or the MAC address is detected to be inconsistent, the IMEI code or the MAC address is not registered uniquely on the network, the service number conversion number is larger than a preset threshold value, and the IMEI code or the MAC address conversion number is larger than the preset threshold value, the abnormal behavior of the advertisement activity is determined to exist.
11. The apparatus of claim 10,
the analysis unit is specifically configured to extract, from the telecom operator data, terminal access location information and corresponding access time information when a user terminal of an advertisement behavior accesses a telecom operator service device;
detecting whether a user mobile terminal with a moving range smaller than a preset range threshold exists in a preset time according to the terminal access position information and the access time information, wherein the user mobile terminal has a plurality of different advertisement access behaviors; and/or
Detecting whether a plurality of user mobile terminals with the same position change tracks exist or not;
and if a plurality of user mobile terminals with the same position change tracks exist and/or the user mobile terminals exist within a preset time, determining that the advertisement activity abnormal behaviors exist.
12. The apparatus of claim 10,
the analysis unit is specifically used for extracting user terminal internet traffic detailed record information of advertisement behaviors from the telecom operator data;
detecting whether the flow information of websites or applications related to the advertisement page exists before and after the access record of the advertisement page according to the internet surfing flow detailed record information;
if not, determining that the abnormal behavior of the advertising activity exists.
13. The apparatus of claim 10,
the analysis unit is specifically used for extracting user profile information of the advertisement behavior from the telecom operator data;
detecting whether the advertisement behavior user with the advertisement activity times larger than a preset threshold is a server user or not according to the user data information; and/or
If the times of carrying out the same advertisement activities by the advertisement behavior users with the same IP address or the similar IP addresses are larger than a preset time threshold value, detecting whether the advertisement behavior users with the same IP address or the similar IP addresses are collective internet surfing users or not according to the user information; and/or
Detecting whether the advertisement behavior users accessing the same advertisement are the same user or the user with the account opening time interval smaller than the preset interval threshold value according to the user data information; and/or
Detecting whether the advertisement behavior users accessing the same advertisement are users with registered network access user names close to each other or users with network access addresses close to each other or not according to the user information;
when the advertising behavior user with the advertising activity times larger than the preset threshold is detected to be a server user, and/or the advertising behavior user with the same IP address or the similar IP address is not a collective internet user, and/or the advertising behavior user accessing the same advertisement is the same user or the user with the account opening time interval smaller than the preset interval threshold, and/or the advertising behavior user accessing the same advertisement is a user with the name similar to that of the registered internet user or the internet address similar to that of the registered internet user, determining that the advertising activity abnormal behavior exists.
14. The apparatus of claim 10,
the analysis unit is specifically further configured to extract communication activity information of the advertisement behavior from the telecom operator data, where the communication activity information includes average network access duration information, average call duration information, and average communication service consumption information;
detecting whether the communication activity of the advertising behavior is abnormal or not according to the communication activity information;
if yes, determining that the advertisement activity abnormal behavior exists.
15. The apparatus of any one of claims 10 to 14,
the determining unit is specifically configured to configure respective corresponding weights for the verification analysis results under different preset verification rules;
calculating scores respectively corresponding to the verification analysis results under different preset verification rules;
multiplying each item score by the corresponding weight, and adding to obtain an average value;
comparing the average value with a preset standard value;
and if the difference between the average value and a preset standard value is larger than a preset threshold value, determining that the advertising cheating behavior exists.
16. The apparatus of claim 10,
the determining unit is specifically configured to obtain a ratio of the verification analysis results of the abnormal behavior of the advertisement campaign according to the verification analysis results under different preset verification rules;
detecting whether the ratio is larger than a preset ratio threshold value or not;
if yes, determining that the advertisement cheating behavior exists.
17. The apparatus of claim 16, further comprising: a saving unit and a generating unit;
the acquisition unit is also used for acquiring advertisement information with advertisement cheating behaviors and corresponding cheating user and/or cheating terminal information;
the storage unit is used for storing the cheating user and/or the cheating terminal information in a blacklist;
and the generating unit is used for generating analysis report information of the advertising cheating activities according to the advertising information with the advertising cheating behaviors, the cheating users and the cheating terminal information.
18. The apparatus of claim 17, further comprising: a counting unit;
the statistical unit is used for counting the position information corresponding to the cheating user and/or the cheating terminal information and the historical movement track information;
and the generating unit is specifically used for generating analysis report information of the advertising cheating activities according to the advertising information with the advertising cheating behaviors, the cheating users and the cheating terminal information and by combining the position information and the historical movement track information.
19. A storage device having a computer program stored thereon, wherein the program, when executed by a processor, implements the method of determining advertising cheating behavior of any of claims 1-9.
20. A cloud server comprising a storage device, a processor and a computer program stored on the storage device and executable on the processor, wherein the processor implements the method of determining advertising cheating behavior of any one of claims 1-9 when executing the program.
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