CN112533209A - Black product identification method and black product identification device - Google Patents
Black product identification method and black product identification device Download PDFInfo
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Abstract
The application provides a black product identification method and a black product identification device. According to the technical scheme, a more accurate black product account library is generated by utilizing the mobile phone account and the broadband account in the unique 3A log data of the operator and the associated information (online time, second-variable times and the like), and the black product is identified based on the black product account library, so that the identification accuracy of the black product can be improved. According to the technical scheme, the recognition accuracy of the black products can be improved through the accurate matching of the login time of the broadband account. In addition, the technical scheme of the application can improve the identification speed through fuzzy identification of the mobile phone number.
Description
Technical Field
The present application relates to the field of information technology, and in particular, to a black product identification method and a black product identification device.
Background
The network black product (hereinafter referred to as "black product") refers to an illegal behavior which takes the internet as a medium and a network technology as a main means and brings potential threats (major potential safety hazards) to the safety of a computer information system, the order of network space management and the like.
For example, enterprises will usually provide some commodity incentives or preferential policies, when people make money using this information, an event of "pulling wool" and "wool party" are formed, when the action of "pulling wool" is formed in a certain scale, a group of "pulling wool" is formed, these groups often adopt robots to remove pulling wool to maximize the benefit, and this robot is called black birth, generally this system includes the actions of robot registration, identity pretended by hitting a warehouse, short wool, etc.
To prevent blackcurrencies, in the related art, a blackcurrant is identified by a service system attacked by the blackcurrant. The existing black product identification method often has the phenomenon of inaccurate identification such as wrong identification.
For example, after the black product account verification system identifies an Internet Protocol (IP) address as a black product IP address according to the fact that the number of times of login for a certain period of time exceeds a preset number of times, login behaviors of all accounts through the IP address are identified as black products.
Disclosure of Invention
The embodiment of the application provides a black product identification method and a black product identification device, so that the identification accuracy of the black product can be improved through accurate matching of the login time of a broadband account, the identification speed can be improved through fuzzy identification of a mobile phone number, and the identification accuracy of the black product is integrally improved.
In a first aspect, the present application provides a black product identification method, including: receiving a black product identification request message, wherein the black product identification request message carries a mobile phone number to be identified, login time of the mobile phone number to be identified and an Internet Protocol (IP) address used by the mobile phone number to be identified in the login time; determining the broadband account associated with the mobile phone number to be identified when the IP address is used at the login time as the broadband account to be identified; judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is black production or not according to the distance between the to-be-identified broadband account and the black production broadband account in a black production account library and the distance between the login time and the black production time of the black production broadband account; sending a moment accurate black product identification result, wherein the moment accurate black product identification result comprises: and the information is used for indicating whether the mobile phone number to be identified is a black product or not by using the behavior identification of the IP address at the login time.
In the method, the black product identification is carried out based on the login time of the account corresponding to the mobile phone number and the IP address at the login time, so that the time of the login behavior can be accurately reached, the black product identification is not carried out based on the IP address, the error identification can be avoided, and the accuracy of the black product identification can be improved.
With reference to the first aspect, in a first possible implementation manner, the determining, according to a distance between the to-be-identified broadband account and a blackout broadband account in a blackout broadband account library and a distance between the login time and a blackout time of the blackout broadband account, whether a behavior of the to-be-identified mobile phone number using the IP address at the login time is a blackout or not includes: calculating the time accurate matching distance between the broadband account to be identified and each broadband account of the black product in the black product account library according to the following formula:
x＝1,2,3,…,C
wherein C is the number of the black product broadband account numbers in the black product account library;
is composed of
Transposing; mu is an adjustment coefficient; l is the autonomous adjustment time range;
is the login time;
the black yield time is the time of the black yield,
for the broadband account to be identified,
is the x-th black product broadband account number in the black product account library, dxAccurately matching the distance between the broadband account to be identified and the xth black-yield broadband account;
and when the minimum moment accurate matching distance in the C moment accurate matching distances obtained by calculation is smaller than or equal to a moment accurate matching distance threshold value, determining that the behavior of the mobile phone number to be identified using the IP address at the login time is black.
In the implementation mode, a method for accurately matching the broadband account is described in detail to identify whether the broadband account is a black product account, so that the identification accuracy of the black product can be improved.
With reference to the first possible implementation manner, in a second possible implementation manner, before determining whether a behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product according to a distance between the to-be-identified broadband account and a black product broadband account in a black product account library and a distance between the login time and a black product time of the black product broadband account, the method further includes: judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product or not according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library; sending a fuzzy black product identification result, wherein the fuzzy black product identification result comprises: and the information is used for indicating that the behavior of using the IP address by the mobile phone number to be identified in the login time is black production.
In the implementation mode, before the accurate black product identification result is provided, fuzzy black product identification can be rapidly carried out, and fuzzy black product identification result reference is provided.
With reference to the second possible implementation manner, in a third possible implementation manner, the determining, according to a distance between the to-be-identified mobile phone number and a blacklist mobile phone number in the blacklist account library, whether a behavior of the to-be-identified mobile phone number using the IP address at the login time is a blacklist includes: calculating the fuzzy matching distance between the mobile phone number to be identified and each of the mobile phone numbers of the black product in the black product account library according to the following formula:
k＝1,2,3,…,Ω
wherein Ω is the number of the mobile phone numbers of the black product in the black product account library; i. j and t are respectively the three-dimensional coordinates of the three-dimensional storage space point of the mobile phone number to be identified, SmiThe last 10 digits of the mobile phone number to be identified,
the last 10 digits, D, of the kth Heiyao mobile phone number in the Heiyao account libraryk(i, j, t) is a fuzzy matching distance between the mobile phone number to be identified and the kth mobile phone number of the black product, and the mod represents a remainder operation;
and when the minimum fuzzy matching distance in the omega fuzzy matching distances obtained by calculation is smaller than or equal to a fuzzy matching distance threshold value, determining that the behavior of the mobile phone number to be identified using the IP address at the login time is black.
In the implementation mode, a method for fuzzy matching of the mobile phone number is specifically introduced to identify whether the mobile phone number is a black product account, so that the identification speed of the black product can be increased, and a fuzzy black product identification result reference can be provided.
With reference to the third possible implementation manner, in a fourth possible implementation manner, the blackout identification request message further carries identification requirement indication information, where the identification requirement indication information is used to indicate whether to request fuzzy blackout identification;
correspondingly, the step of judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library includes: and when the identification demand indication information indicates that the fuzzy black product identification is requested, judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product or not according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library.
In the implementation mode, the fuzzy black product identification is carried out under the condition that the fuzzy black product identification is required, so that the resource waste can be avoided, and the efficiency of accurate black product identification is improved.
With reference to the first aspect or any one of the foregoing possible implementation manners, in a fifth possible implementation manner, the blackout account library is generated based on a 3A log database of an operator, where the database contains more information, and can generate a more accurate blackout account library, so that accuracy of identifying the blackout product can be improved, and the method is also beneficial to performing previous identification of the blackout product behavior.
With reference to the first aspect or any one of the foregoing possible implementation manners, in a sixth possible implementation manner, the time-accurate black product identification result includes: the mobile phone number to be identified, the broadband account to be identified, the login time and the IP address.
In a second aspect, the present application provides a black product identification apparatus, comprising: the system comprises a receiving module, a processing module and a processing module, wherein the receiving module is used for receiving a black product identification request message, and the black product identification request message carries a mobile phone number to be identified, login time of the mobile phone number to be identified and an Internet Protocol (IP) address used by the mobile phone number to be identified in the login time; the determining module is used for determining the broadband account associated with the mobile phone number to be identified when the IP address is used at the login time as the broadband account to be identified; the judging module is used for judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is black according to the distance between the to-be-identified broadband account and the black broadband account in the black broadband account library and the distance between the login time and the black time of the black broadband account; the sending module sends the identification result of the accurate black products at the moment, and the identification result of the accurate black products at the moment comprises: and the information is used for indicating whether the mobile phone number to be identified is a black product or not by using the behavior identification of the IP address at the login time.
With reference to the second aspect, in a first possible implementation manner, the determining module is specifically configured to: calculating the time accurate matching distance between the broadband account to be identified and each broadband account of the black product in the black product account library according to the following formula:
x＝1,2,3,…,C
wherein C is the number of the black product broadband account numbers in the black product account library;
is composed of
Transposing; mu is an adjustment coefficient; l is the autonomous adjustment time range;
is the login time;
the black yield time is the time of the black yield,
for the broadband account to be identified,
is the x-th black product broadband account number in the black product account library, dxAccurately matching the distance between the broadband account to be identified and the xth black-yield broadband account;
and when the minimum moment accurate matching distance in the C moment accurate matching distances obtained by calculation is smaller than or equal to a moment accurate matching distance threshold value, determining that the behavior of the mobile phone number to be identified using the IP address at the login time is black.
With reference to the first possible implementation manner, in a second possible implementation manner, the determining module is further configured to: judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product or not according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library; the sending module is further configured to send a fuzzy black product identification result, where the fuzzy black product identification result includes: and the information is used for indicating that the behavior of using the IP address by the mobile phone number to be identified in the login time is black production.
With reference to the second possible implementation manner, in a third possible implementation manner, the determining module is specifically configured to: calculating the fuzzy matching distance between the mobile phone number to be identified and each of the mobile phone numbers of the black product in the black product account library according to the following formula:
k＝1,2,3,…,Ω
wherein Ω is the number of the mobile phone numbers of the black product in the black product account library; i. j and t are respectively the three-dimensional coordinates of the three-dimensional storage space point of the mobile phone number to be identified, SmiThe last 10 digits of the mobile phone number to be identified,
the last 10 digits, D, of the kth Heiyao mobile phone number in the Heiyao account libraryk(i, j, t) is a fuzzy matching distance between the mobile phone number to be identified and the kth mobile phone number of the black product, and the mod represents a remainder operation;
and when the minimum fuzzy matching distance in the omega fuzzy matching distances obtained by calculation is smaller than or equal to a fuzzy matching distance threshold value, determining that the behavior of the mobile phone number to be identified using the IP address at the login time is black.
With reference to the third possible implementation manner, in a fourth possible implementation manner, the blackout identification request message further carries identification requirement indication information, where the identification requirement indication information is used to indicate whether to request fuzzy blackout identification;
correspondingly, the judging module is specifically configured to: and when the identification demand indication information indicates that the fuzzy black product identification is requested, judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product or not according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library.
With reference to the second aspect or any one of the foregoing possible implementation manners, in a fifth possible implementation manner, the blackout account library is generated based on a 3A log database of an operator, where the database contains more information, and can generate a more accurate blackout account library, so that accuracy of identifying the blackout product can be improved, and the method is also beneficial to performing previous identification of the blackout product behavior.
With reference to the second aspect or any one of the foregoing possible implementation manners, in a sixth possible implementation manner, the time-accurate black product identification result includes: the mobile phone number to be identified, the broadband account to be identified, the login time and the IP address.
In a third aspect, the present application provides a black product identification device, including: a memory and a processor; the memory is to store program instructions; the processor is configured to invoke program instructions in the memory to perform a method according to the first aspect or any one of its possible implementations.
Where the apparatus is a computing device, in some implementations, the apparatus may also include a transceiver or a communication interface for communicating with other devices.
When the apparatus is a chip for a computing device, in some implementations, the apparatus may also include a communication interface for communicating with other apparatus in the computing device, such as for communicating with a transceiver of the computing device.
In a fourth aspect, the present application provides a computer-readable medium storing program code for execution by a computer, the program code comprising instructions for performing the method according to the first aspect or any one of its possible implementations.
In a fifth aspect, the present application provides a computer program product comprising instructions which, when run on a processor, cause the processor to carry out the method of the first aspect or any one of its implementations.
In a sixth aspect, the present application provides a black product identification system including the black product identification device in the second or third aspect.
Drawings
Fig. 1 is a schematic structural diagram of a blackout identification system according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a black product identification method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a black product identification device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a blackout identification apparatus according to another embodiment of the present application.
Detailed Description
Fig. 1 is a diagram illustrating a structure of a blackout identification system according to an embodiment of the present application. As shown in fig. 1, the blackout identification system of the present embodiment may include a 3A log database of an operator, a data conversion device, a terminal device, a blackout account verification system, and a blackout account library.
The 3A log is original data information unique to an operator, and the information comprises a broadband account, a mobile phone number associated with the broadband account, login time of the broadband account when the broadband account is accessed to a network each time, an IP address, online time after the broadband account is accessed to the network each time, and the amount of traffic used after the broadband account is accessed to the network. An example of a login time is a month, a day, a minute, and a second of a year.
The data conversion device generates a blackout account library based on the 3A log data. For example, the data conversion device determines whether a broadband account is a black generation account according to the number of times of conversion of the IP address associated with the broadband account in one time period in the 3A log data. For another example, the data conversion device determines whether the mobile phone account is a black generation account according to the conversion of the IP address associated with one mobile phone number in a time period in the 3A log data. For another example, the data conversion device determines whether the broadband account is a black generation account according to the average online time of each IP address associated with the broadband user in the 3A log.
The broadband account identified as the black product account is included in the black product account library. In addition, the mobile phone number account associated with the broadband account of the black product is also identified as the account of the black product. The black product account library can also record the black product action occurrence time of each black product broadband account.
The terminal device can access the black generation account identification system through an application (App) or a website. For example, when the terminal device needs to identify whether a certain mobile phone number is a blackout account, the mobile phone number may be sent to the blackout account identification system based on a blackout identification App or a blackout identification website on the terminal device to request the blackout account identification system to identify. An example of a terminal device is a mobile phone.
After receiving the mobile phone number sent by the terminal device, the blacklist account identification system can read the information in the blacklist account library, identify whether the mobile phone number requested to be identified by the terminal device is the blacklist account according to the read information, and send an identification result to the terminal device.
Fig. 2 is a flowchart of a black product identification method according to an embodiment of the present application. As shown in fig. 2, the method may include S201, S202, S203, S204, S205, and S206.
S201, the terminal equipment sends a black product identification request message to a black product account verification system, wherein the black product identification request message carries a mobile phone number to be identified, login time of the mobile phone number to be identified and an IP address used by the mobile phone number to be identified in the login time. Accordingly, the black product account verification system receives the black product identification request message.
The blacklist product identification request message is used for requesting the blacklist product account verification system to verify whether the mobile phone number to be identified is a blacklist product mobile phone number or not, or is used for requesting the blacklist product account verification system to verify whether the action of logging in the mobile phone number to be identified by using the IP address at the login time is a blacklist product or not.
The terminal equipment can be a mobile phone or a computer and the like. The terminal equipment can send the black product identification request message to the black product account verification system through the APP or the website. The mobile phone number to be identified in this embodiment may also be referred to as a mobile phone number to be verified.
In this embodiment, the login time of the to-be-identified mobile phone number may be understood as the time for the user account associated with the to-be-identified mobile phone number to access or log in the service system, and the IP address used by the to-be-identified mobile phone number at the login time may be understood as the IP address used by the user account associated with the to-be-identified mobile phone number to access or log in the service system at the login time.
The business system in this embodiment may be any system capable of providing a service to a user, and may be, for example, a shopping website or a scoring website.
In this embodiment, the IP address may be an IPV4 address or an IPV6 address, and the IP address may be an address allocated by the telecommunications access network for a device (for example, a mobile phone) used when logging in the service system using the mobile phone number. The address allocated by the telecommunication access network to the equipment (such as a mobile phone) used when the mobile phone number is used for logging in the service system can be changed continuously along with the on-line and off-line of the mobile phone number account.
S202, judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product or not according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library.
The step can be called as fuzzy matching black product identification of the mobile phone number to be identified, and the result obtained by identification is called as a fuzzy black product identification result.
The blacklist account library may include a mobile phone number initiating a blacklist behavior, and the mobile phone number initiating the blacklist behavior may be referred to as a blacklist mobile phone number.
In an exemplary case where the blacklist account verification system performs fuzzy matching on the to-be-recognized mobile phone number, the following formula can be used to calculate a fuzzy matching distance between the to-be-recognized mobile phone number and each of the blacklist mobile phone numbers in the blacklist account library:
k＝1,2,3,…,Ω
in the formula, omega is the number of the mobile phone numbers of the black product in the black product account library; i. j and t are respectively the three-dimensional coordinates of the three-dimensional storage space point of the mobile phone number to be identified, SmiThe last 10 digits of the mobile phone number to be identified,
the last 10 digits, D, of the k-th Heiyao mobile phone number in the Heiyao account libraryk(i, j, t) is the fuzzy matching distance between the mobile phone number to be identified and the k < th > mobile phone number of the black product in the black product account library, and the mod represents the remainder operation.
And after the blacklist account verification system calculates the fuzzy matching distance between the mobile phone number to be identified and each blacklist mobile phone number in the blacklist account library, selecting the minimum fuzzy matching distance, and identifying the login behavior of the mobile phone number to be identified based on the IP address at the login time as the blacklist under the condition that the minimum fuzzy matching distance is smaller than or equal to a preset fuzzy matching distance threshold value. In this case, the fuzzy black product recognition result may include: and the information is used for indicating that the mobile phone number to be identified is identified as black products based on the login behavior of the IP address at the login time.
It can be understood that the above formula for calculating the fuzzy matching distance is only an example, and in this embodiment, other distance calculation formulas may also be used to calculate the fuzzy matching distance between the mobile phone number to be identified and the black product mobile phone number, for example, a manhattan distance or a cosine distance between the mobile phone number after the mobile phone number to be identified is fuzzy and the mobile phone number after the mobile phone number in black product is fuzzy may be calculated as the fuzzy matching distance.
S203, the blackout account verification system sends a fuzzy blackout identification result to the terminal equipment. Correspondingly, the terminal equipment receives the fuzzy black product identification result sent by the black product account verification system.
And S204, determining the broadband account associated with the mobile phone number to be identified when the IP address is used at the login time as the broadband account to be identified by the black product account verification system according to the information carried in the black product identification request message.
In this embodiment, the to-be-identified broadband account may also be referred to as a broadband account associated with the to-be-identified mobile phone number when the IP address is used at the login time.
For example, the blacklist account verification system may determine, based on a 3A log database of the operator, a broadband account associated with the mobile phone number to be identified when the IP address is used at the login time.
S205, the blacklist account verification system judges whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a blacklist according to the distance between the to-be-identified broadband account and the blacklist broadband account in the blacklist account library and the distance between the login time and the blackness time of the blacklist broadband account.
The black product account library can also comprise broadband accounts with black products, and the broadband accounts with black products can be called as the black product broadband accounts. Further, the black yield account library records the time of the black yield behavior of each black yield broadband account, and the time of the black yield behavior of the black yield broadband account can be referred to as the black yield time of the black yield broadband account.
This step can be understood as: and the black product account verification system carries out accurate verification on the annual, monthly, hour, minute and second granularity on the broadband account to be identified and each black product broadband account in the black product account library.
For example, the blackout account verification system calculates a time exact matching distance between the broadband account associated with the received mobile phone number and each broadband account in the blackout account library according to the following formula:
x＝1,2,3,…,C
in the formula, C is the number of black band broadband account numbers in the black generation account library;
is composed of
Transposing; mu is an adjustment coefficient; l is the autonomous adjustment time range;
logging in the mobile phone number to be identified based on the IP address;
for the black yield time of the xth broadband account in the black yield account library,
for the broadband account to be identified,
is the x-th black product broadband account number in the black product account library, dxAnd accurately matching the distance between the broadband account to be identified and the xth black-yield broadband account. Where both μ and L are empirically set.
And after the moment accurate matching distance between the broadband account to be identified and each black product broadband account in the black product account library is obtained through calculation, finding out the minimum moment accurate matching distance, and judging whether the minimum moment accurate matching distance is smaller than or equal to an accurate matching distance threshold value or not. If the minimum time accurate matching distance is smaller than or equal to the accurate matching distance threshold, the login behavior of the mobile phone number to be recognized based on the IP address at the login time can be accurately considered as a black product. In this case, the obtained accurate black product identification result for performing accurate black product identification may include: and the information is used for indicating that the mobile phone number to be identified identifies the black product based on the login behavior of the IP address at the login time.
Optionally, the accurate black product identification result may further include the to-be-identified mobile phone number, the login time, and the IP address, so that the terminal device can obtain the mobile phone number, the login time, and the IP address corresponding to the black product. Further, the accurate black product identification result may further include a broadband account associated with the mobile phone number to be identified.
It is understood that the above formula for calculating the accurate matching distance at the time is only an example, and the embodiment may also use other formulas for calculating the distance to calculate the accurate matching distance at the time between the broadband account to be identified and the blackout broadband account, for example, the manhattan distance between the broadband account to be identified and the blackout broadband account, and the manhattan distance between the login time and the blackout time may be calculated respectively, and the accurate matching distance at the time is calculated according to the two manhattan distances.
S206, the black product account verification system sends an accurate black product identification result to the terminal equipment. Correspondingly, the terminal equipment receives the accurate black product identification result.
In this embodiment, the blackout identification request message may further carry identification requirement indication information, where the identification requirement indication information is used to indicate whether the blackout account verification system is requested to provide a fuzzy blackout identification result.
If the identification requirement indication information indicates that the blackjack account verification system is requested to provide the fuzzy blackjack identification result, the blackjack account verification system may perform S202 and S203 to provide the fuzzy blackjack identification result to the terminal device, and then perform S204 to S206 to provide the accurate blackjack identification result to the terminal device.
If the identification requirement indication information indicates that the blackout account verification system is not requested to provide the fuzzy blackout identification result, the blackout account verification system may not perform S202 and S203.
If the blackout identification request message does not carry identification requirement indication information, or the identification requirement request information does not indicate whether the blackout account verification system is requested to provide a fuzzy blackout identification result, the blackout account verification system may determine whether to execute S202 and S203 according to default settings. The default setting may be to execute S202 and S203 by default, or may be to execute S202 and S203 by default.
Fig. 3 is a schematic structural diagram of a blackout identification apparatus according to an embodiment of the present application. The apparatus shown in fig. 3 may be used to perform the method described in any of the previous embodiments. As shown in fig. 3, the apparatus 300 of the present embodiment may include: a receiving module 301, a determining module 302, a judging module 303 and a sending module 304.
In one example, the apparatus 300 may be configured to perform the method described in fig. 2. For example, the receiving module 301 may be configured to perform S201, the determining module 302 may be configured to perform S204, the determining module 303 may be configured to perform S202 and S205, and the sending module 304 may be configured to perform S203 and S206.
Fig. 4 is a schematic structural diagram of a blackout identification apparatus according to another embodiment of the present application. The apparatus shown in fig. 4 may be used to perform the method described in any of the previous embodiments.
As shown in fig. 4, the apparatus 400 of the present embodiment includes: memory 401, processor 402, communication interface 403, and bus 404. The memory 401, the processor 402 and the communication interface 403 are connected to each other by a bus 404.
The memory 401 may be a Read Only Memory (ROM), a static memory device, a dynamic memory device, or a Random Access Memory (RAM). The memory 401 may store a program and the processor 402 is adapted to perform the steps of the method shown in fig. 2 when the program stored in the memory 401 is executed by the processor 402.
The processor 402 may be a general-purpose Central Processing Unit (CPU), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits, and is configured to execute related programs to implement the methods in the embodiments of the present application.
The processor 402 may also be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the method of the embodiments of the present application may be implemented by integrated logic circuits of hardware or instructions in the form of software in the processor 402.
The processor 402 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory 401, and a processor 402 reads information in the memory 401, and performs functions required by units included in the apparatus according to the present application in combination with hardware thereof, for example, to perform various steps/functions of the embodiment shown in fig. 2.
The communication interface 403 may use transceiver means, such as, but not limited to, a transceiver, to enable communication between the apparatus 400 and other devices or communication networks.
Bus 404 may include a path that transfers information between various components of apparatus 400 (e.g., memory 401, processor 402, communication interface 403).
It should be understood that the apparatus 400 shown in the embodiments of the present application may be a computing device, or may also be a chip configured in a computing device.
It will also be appreciated that the memory in the embodiments of the subject application can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of example, but not limitation, many forms of Random Access Memory (RAM) are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct bus RAM (DR RAM).
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. The procedures or functions according to the embodiments of the present application are wholly or partially generated when the computer instructions or the computer program are loaded or executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more collections of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
It should be understood that the term "and/or" herein is merely one type of association relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. In addition, the "/" in this document generally indicates that the former and latter associated objects are in an "or" relationship, but may also indicate an "and/or" relationship, which may be understood with particular reference to the former and latter text.
In the present application, "at least one" means one or more, "a plurality" means two or more. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: u disk, removable hard disk, read only memory, random access memory, magnetic or optical disk, etc. for storing program codes.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A black product identification method is characterized by comprising the following steps:
receiving a black product identification request message, wherein the black product identification request message carries a mobile phone number to be identified, login time of the mobile phone number to be identified and an Internet Protocol (IP) address used by the mobile phone number to be identified in the login time;
determining the broadband account associated with the mobile phone number to be identified when the IP address is used at the login time as the broadband account to be identified;
judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is black production or not according to the distance between the to-be-identified broadband account and the black production broadband account in a black production account library and the distance between the login time and the black production time of the black production broadband account;
sending a moment accurate black product identification result, wherein the moment accurate black product identification result comprises: and the information is used for indicating whether the mobile phone number to be identified is a black product or not by using the behavior identification of the IP address at the login time.
2. The method according to claim 1, wherein the determining whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product according to the distance between the to-be-identified broadband account and a black product broadband account in a black product account library and the distance between the login time and a black product time of the black product broadband account comprises:
calculating the time accurate matching distance between the broadband account to be identified and each broadband account of the black product in the black product account library according to the following formula:
wherein C is the number of the black product broadband account numbers in the black product account library;
is composed of
Transposing; mu is an adjustment coefficient; l is the autonomous adjustment time range;
is the login time;
the black yield time is the time of the black yield,
for the broadband account to be identified,
is the x-th black product broadband account number in the black product account library, dxAccurately matching the distance between the broadband account to be identified and the xth black-yield broadband account;
and when the minimum moment accurate matching distance in the C moment accurate matching distances obtained by calculation is smaller than or equal to a moment accurate matching distance threshold value, determining that the behavior of the mobile phone number to be identified using the IP address at the login time is black.
3. The method according to claim 2, wherein before the step of determining whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is black production according to the distance between the to-be-identified broadband account and the black production broadband account in the black production account library and the distance between the login time and the black production time of the black production broadband account, the method further comprises:
judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product or not according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library;
sending a fuzzy black product identification result, wherein the fuzzy black product identification result comprises: and the information is used for indicating that the behavior of using the IP address by the mobile phone number to be identified in the login time is black production.
4. The method as claimed in claim 3, wherein the determining whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library comprises:
calculating the fuzzy matching distance between the mobile phone number to be identified and each of the mobile phone numbers of the black product in the black product account library according to the following formula:
wherein Ω is the number of the mobile phone numbers of the black product in the black product account library; i. j and t are respectively the three-dimensional coordinates of the three-dimensional storage space point of the mobile phone number to be identified, SmiThe last 10 digits of the mobile phone number to be identified,
the last 10 digits, D, of the kth Heiyao mobile phone number in the Heiyao account libraryk(i, j, t) is a fuzzy matching distance between the mobile phone number to be identified and the kth mobile phone number of the black product, and the mod represents a remainder operation;
and when the minimum fuzzy matching distance in the omega fuzzy matching distances obtained by calculation is smaller than or equal to a fuzzy matching distance threshold value, determining that the behavior of the mobile phone number to be identified using the IP address at the login time is black.
5. The method according to claim 4, wherein the black product identification request message further carries identification requirement indication information, and the identification requirement indication information is used for indicating whether fuzzy black product identification is requested or not;
correspondingly, the step of judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library includes:
and when the identification demand indication information indicates that the fuzzy black product identification is requested, judging whether the behavior of the to-be-identified mobile phone number using the IP address at the login time is a black product or not according to the distance between the to-be-identified mobile phone number and the black product mobile phone number in the black product account library.
6. The method of any one of claims 1 to 5, wherein the library of bankrupt accounts is generated based on an operator's 3A log database.
7. The method according to any one of claims 1 to 5, wherein the time accurate black product identification result comprises: the mobile phone number to be identified, the broadband account to be identified, the login time and the IP address.
8. A black product identification device, characterized by comprising various functional modules required for implementing the method of any one of claims 1 to 7.
9. A black product identification device, comprising: a memory and a processor;
the memory is to store program instructions;
the processor is configured to call program instructions in the memory to perform the method of any one of claims 1 to 7.
10. A computer-readable medium, characterized in that the computer-readable medium stores program code for computer execution, the program code comprising instructions for performing the method of any of claims 1 to 7.
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