CN114037460B - Comprehensive anti-fraud platform, method and storage medium - Google Patents
Comprehensive anti-fraud platform, method and storage medium Download PDFInfo
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Abstract
The invention discloses a comprehensive anti-fraud platform, an anti-fraud method and a storage medium, wherein the platform can utilize a classification model construction system to construct various illegal induced occupation identification models according to illegal induced occupation behavior data sets and corresponding call ticket data of illegal induced occupation event collections, and simultaneously construct various illegal induced occupation identification models according to related illegal induced occupation behavior data sets, so that the pertinence is strong, and corresponding types of illegal induced occupation behaviors can be effectively identified; the identification accuracy of the illegal induced occupation behavior is improved for the constructed model through the model training system, the illegal induced occupation behavior identification can be carried out on data from different channels, and then early warning, return visit, countercheck and striking are carried out successively through the anti-fraud business system, so that the cheating probability and property loss of a victim are reduced, the cheating details of the victim are recorded, the illegal induced occupation activity channel of the illegal induced occupation activity molecules is sealed, and the real identity of the illegal induced occupation activity molecules is identified.
Description
Technical Field
The invention relates to the technical field of anti-fraud, in particular to a comprehensive anti-fraud platform, a method and a storage medium.
Background
The anti-fraud work is a process of continuously resisting illegal induction occupation of activity molecules, and based on the current situations that illegal induction occupation means are infinite and illegal induction occupation of various activity communication carriers is achieved, the illegal induction occupation of activity scenes cannot be completely covered only by communication records of a telecommunication network to discover and prevent the illegal induction occupation. The traditional technology has the advantages that the analysis of illegal induction occupied activity groups is single, the analysis result is not comprehensive enough, the accuracy is poor, and certain resistance is generated on the anti-fraud work.
The invention patent application with application publication number CN108156333A discloses a fraud prevention control system, as shown in fig. 1, which mainly comprises:
a data source for providing raw log data;
the data loading module is connected with the data source and used for acquiring original log data, a preprocessing module is arranged in the data loading module and used for performing correlation analysis and real-time statistics on the original log data to obtain intermediate result data;
the data storage module is connected with the data loading module and is used for storing original log data and intermediate result data;
the comprehensive analysis module is connected with the data storage module, a fraud group analysis module is arranged in the comprehensive analysis module and is used for group fusion analysis, group development trend analysis, group organization structure analysis, fraud called distribution analysis, fraud group geographical distribution analysis, harassment law analysis and group fraud success rate analysis, the behavior characteristics and the law of fraud implementation of fraud groups are obtained, and the behavior characteristics and the law of fraud implementation of fraud groups are stored in the data storage module;
and the application module is connected with the data storage module and is used for displaying the behavior characteristics and laws of fraud implemented by fraud groups.
When the method is specifically implemented, the fraud prevention control system excavates and analyzes massive multi-dimensional behavior data such as telecommunication network call detailed logs, anti-fraud system basic data, circuit domain logs, short messages, multimedia messages and internet logs by means of big data analysis, deeply analyzes behavior characteristics and laws of illegal induction occupation activity groups for implementing illegal activities, and provides a basis for fighting against the illegal induction occupation activities.
The fraud prevention control system disclosed in CN108156333A performs fraud prevention based on various data, but actually, there are many illegal induced occupation types, and the illegal induced occupation activity channels and specific illegal induced occupation modes used by different illegal induced occupation behaviors are different, and the prior art has relatively poor precision in performing unified data processing and analysis.
It can be seen that the prior art is still in need of improvement and development.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a comprehensive anti-fraud platform, method and storage medium, which are used for solving the problems of different illegal induced occupation activities using different illegal induced occupation activity channels and different specific illegal induced occupation modes, and the prior art has relatively poor accuracy in performing unified data processing and analysis.
The technical scheme of the invention is as follows:
an integrated anti-fraud platform, comprising: the system comprises a classification model construction system, a model training system, a data acquisition system, a resource storage system and an anti-fraud service system;
the classification model construction system is used for respectively constructing a first wanted illegal induced possession identification model, a first bank card illegal induced possession identification model and a first network loan illegal induced possession identification model according to the ticket data, the wanted illegal induced possession behavior data set, the bank card illegal induced possession behavior data set and the network loan illegal induced possession behavior data set;
the online shopping order illegal induction possession identification model is used for establishing a second network loan illegal induction possession identification model, a first order swiping illegal induction possession identification model, a first impersonation friend illegal induction possession identification model, a first online shopping order illegal induction possession identification model, a first investment illegal induction possession identification model and a first game recharging illegal induction possession identification model respectively according to a behavior data set retained on the Internet by illegal induction possession activities;
the model training system is used for training the models constructed by the classification model construction system through a machine learning technology, and respectively obtaining a second illegal account pickup identification model, a second bank card illegal account pickup identification model, a third network loan illegal account pickup identification model, a fourth network loan illegal account pickup identification model, a second swiping illegal account pickup identification model, a second impersonation friend illegal account pickup identification model, a second online shopping order illegal account pickup identification model, a second investment illegal account pickup identification model and a second game recharging illegal account pickup identification model;
the data acquisition system is used for acquiring first network data, receiving call ticket data and second network data provided by a network service provider through a network crawler technology, performing various illegal induced occupation behavior identifications by using a model obtained by training of a model training system, and extracting illegal induced occupation activity data;
the resource storage system includes: a black pool resource pool, the black pool resource pool comprising: the social software account black library, the mobile phone number black library, the IP black library and the URL black library are respectively used for storing a fraud-related social software account, a fraud-related mobile phone number, a fraud-related IP and a fraud-related URL in the illegal induction possession activity data;
the anti-fraud service system comprises: the early warning center is used for carrying out anti-fraud prompt on victims according to illegal induced occupation activity data, the revisiting center is used for revising and reporting the results of illegal induced occupation events, the countering center is used for forbidding illegal induced occupation activity channels, and the attacking center is used for identifying the identity of illegal induced occupation activity molecules.
The effect of above-mentioned scheme lies in: the classification model construction system can construct various illegal induction occupation identification models for contacting victims through telephones to perform illegal induction occupation according to illegal induction occupation behavior data sets and corresponding call ticket data of the illegal induction occupation event set, and meanwhile, various illegal induction occupation identification models for contacting victims through networks are constructed according to related illegal induction occupation behavior data sets retained on the Internet, so that the pertinence is strong, and the corresponding types of illegal induction occupation behaviors can be effectively identified; the identification accuracy rate of the illegal induced occupation behaviors is improved for the constructed model through a model training system, accordingly, the illegal induced occupation behaviors can be identified for data from different channels, and early warning, return visit, countercheck and striking are carried out successively through an anti-fraud service system, so that the cheating probability and property loss of a victim are reduced, the cheating details of the victim are recorded, the illegal induced occupation activity channel of the illegal induced occupation activity molecules is sealed, and the real identity of the illegal induced occupation activity molecules is identified; the problem of prior art carry out unified data processing and analysis precision relatively poor is solved.
In a further preferred aspect, the resource storage system further includes: an early warning resource pool, the early warning resource pool comprising: the online loan illegal induced possession early warning library, the swiping illegal induced possession early warning library, the investment illegal induced possession early warning library, the counterfeit identity illegal induced possession early warning library, the online purchase order illegal induced possession early warning library, the game recharging illegal induced possession early warning library, the deep loan illegal induced possession early warning library, the wanted illegal induced possession early warning library and the bank card illegal induced possession early warning library;
the network loan illegal induction possession early warning library, the billing illegal induction possession early warning library, the investment illegal induction possession early warning library, the counterfeit identity illegal induction possession early warning library, the online shopping order illegal induction possession early warning library, the game recharging illegal induction possession early warning library, the deep loan illegal induction possession early warning library, the wanted illegal induction possession early warning library and the bank card illegal induction possession early warning library, the method is used for storing the early warning data of illegal induced possession of network loan, the early warning data of illegal induced possession of swiping order, the early warning data of illegal induced possession of investment, the early warning data of illegal induced possession of counterfeit identity, the early warning data of illegal induced possession of network purchase order, the early warning data of illegal induced possession of game charge, the early warning data of illegal induced possession of deep loan, the early warning data of illegal induced possession of wanted order and the early warning data of illegal induced possession of bank card before the early warning is finished.
The effect of above-mentioned scheme lies in: the early warning resource pool can temporarily store various early warning data in a classified mode, and clear the relevant early warning data after the completion of the warning task of the relevant early warning event, so that the management definition of the early warning task data and the statistics convenience of the completion degree of the task after the completion are improved.
In a further preferred aspect, the resource storage system further includes: the method comprises the following steps of anti-illegal induction and occupation of a data resource pool, wherein the anti-illegal induction and occupation of the data resource pool comprises the following steps: the system comprises a social number corresponding database and an identity number corresponding database, wherein the social number corresponding database is used for storing the corresponding relation between a social software account and a mobile phone number, and the identity number corresponding database is used for storing the corresponding relation between identity information and the mobile phone number.
The effect of above-mentioned scheme lies in: the generation of the early warning task needs not only illegal induction of occupation behavior data and victim account data/victim identity information, but also a mobile phone number so that the early warning center can quickly communicate with the victim to give anti-fraud prompts to the victim.
In a further preferred aspect, the resource storage system further includes: an IP-geolocation repository for storing fraud-related IPs and geographic locations corresponding to the fraud-related IPs.
The effect of above-mentioned scheme lies in: the position of the illegal induction activity group can be quickly locked according to the information stored in the IP-geographic position library.
In a further preferred aspect, the anti-fraud service system further comprises: the propaganda center, synthesize anti-fraud platform still includes: the mobile phone user side is used for receiving user registration and label information filled in during the registration, and the label information comprises: gender and age tags; the propaganda center is used for pushing propaganda materials to the mobile phone user side according to the label information.
The effect of above-mentioned scheme lies in: the user is accurately anti-fraud advertised according to the label information, the anti-fraud capacity of the user can be improved, the occurrence probability of illegal induced occupation events is reduced, and the anti-fraud effect is improved.
In a further preferred scheme, the data acquisition system further comprises a data center, and the data center is used for performing data cleaning, information analysis, format unification and home region collision on the first network data, the ticket data and the second network data.
The effect of above-mentioned scheme lies in: the unification of the data formats is beneficial to improving the processing speed of the data, so that the anti-fraud early warning, return visit, countercheck and attack efficiency is improved, and the loss of illegal induced occupation events is reduced; meanwhile, the identity recognition rate of the illegal induction occupied activity group is improved by utilizing the collision of the attribution area.
In a further preferred aspect, said integrated anti-fraud platform further comprises: the system comprises a task distribution system, a PC (personal computer) end early warning system, a public number early warning system and an APP (application) early warning system, wherein the task distribution system is used for generating early warning tasks according to data of an early warning resource pool and sending the early warning tasks to the public number early warning system of an early warning center, the PC end early warning system is used for monitoring task getting conditions and task completion conditions of the APP early warning system, the public number early warning system is used for sending information to a user according to a preset early warning template, and the APP early warning system is used for displaying an early warning task list so as to enable early warning personnel to get the tasks.
The effect of above-mentioned scheme lies in: the task distribution system and the public number early warning system are arranged, so that the user can be ensured to receive the early warning information sent by the public number early warning system.
In a further preferred embodiment, the early warning center further includes: the task distribution system is also used for sending the early warning task to the public number early warning system of the early warning center and sending the early warning task to the PC end early warning system and the APP early warning system.
The effect of above-mentioned scheme lies in: the PC end early warning system and the APP early warning system are arranged, so that most users can be guaranteed to receive manual early warning of early warning personnel, the alertness is still improved under the prompting of the early warning personnel with a high probability under the condition that the users do not pay attention to automatic prompt information, and the occurrence probability of illegal induction occupation events is reduced.
An anti-fraud method implemented based on the above-mentioned integrated anti-fraud platform, comprising:
the classification model construction system respectively constructs a first wanted illegal induced possession identification model, a first bank card illegal induced possession identification model and a first network loan illegal induced possession identification model according to the ticket data, the wanted illegal induced possession behavior data set, the bank card illegal induced possession behavior data set and the network loan illegal induced possession behavior data set; meanwhile, according to a behavior data set reserved on the Internet by illegal induced possession activities, respectively constructing a second network loan illegal induced possession identification model, a first order-swiping illegal induced possession identification model, a first impersonation friend illegal induced possession identification model, a first online purchase order illegal induced possession identification model, a first investment illegal induced possession identification model and a first game illegal recharge induced possession identification model;
the model training system trains the models constructed by the classification model construction system through a machine learning technology, and respectively obtains a second illegal accrual instruction induction possession identification model, a second bank card illegal accrual instruction possession identification model, a third network loan illegal accrual instruction possession identification model, a fourth network loan illegal accrual instruction possession identification model, a second swiping illegal accrual instruction possession identification model, a second impersonation friend illegal accrual instruction possession identification model, a second online shopping order illegal accrual instruction possession identification model, a second investment illegal accrual instruction possession identification model and a second game accrual illegal accrual instruction possession identification model;
the data acquisition system acquires first network data, received call ticket data and second network data provided by a network service provider through a network crawler technology, performs various illegal induced occupation behavior identifications by utilizing a model obtained by training of a model training system, and extracts illegal induced occupation activity data;
constructing a social software account black library, a mobile phone number black library, an IP black library and a URL black library, and respectively storing the fraud-related social software account, the fraud-related mobile phone number, the fraud-related IP and the fraud-related URL in the extracted illegal induction occupation activity data in the social software account black library, the mobile phone number black library, the IP black library and the URL black library;
the early warning center carries out anti-fraud prompt on the victim according to the illegal induction occupation activity data;
the return visit center returns the visit report of the result of the illegal induction occupation event;
the anti-control center blocks the illegal induction activity channel;
the strike center identifies the identity of the illegal induction possessing activity molecules.
The effect of above-mentioned scheme lies in: the classification model construction system can construct various illegal induction occupation identification models occupied by illegal induction through telephone contact with a victim according to an illegal induction occupation behavior data set of an illegal induction occupation event subset and corresponding call ticket data, and meanwhile, various illegal induction occupation identification models occupied by illegal induction through network contact with the victim are constructed according to related illegal induction occupation behavior data sets retained on the Internet, so that the pertinence is strong, and the corresponding types of illegal induction occupation behaviors can be effectively identified; the identification accuracy rate of the illegal induced occupation behaviors is improved for the constructed model through a model training system, accordingly, the illegal induced occupation behaviors can be identified for data from different channels, and early warning, return visit, countercheck and striking are carried out successively through an anti-fraud service system, so that the cheating probability and property loss of a victim are reduced, the cheating details of the victim are recorded, the illegal induced occupation activity channel of the illegal induced occupation activity molecules is sealed, and the real identity of the illegal induced occupation activity molecules is identified; the problem of prior art carry out unified data processing and analysis precision relatively poor is solved.
A storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the anti-fraud method as described above. The storage medium includes all technical features of the anti-fraud method, and therefore, all technical effects of the anti-fraud method are also provided, and further description is omitted.
Compared with the prior art, the comprehensive anti-fraud platform provided by the invention can utilize a classification model construction system to construct various illegal induction occupation identification models occupied by illegal induction through contacting with victims through telephones according to the illegal induction occupation behavior data sets grouped into the illegal induction occupation events and the corresponding call ticket data, and meanwhile, various illegal induction occupation identification models occupied by illegal induction through contacting with victims through networks are constructed according to the related illegal induction occupation behavior data sets retained on the Internet, so that the comprehensive anti-fraud platform is strong in pertinence and can effectively identify corresponding types of illegal induction occupation behaviors; the identification accuracy rate of the illegal induced occupation behaviors is improved for the constructed model through a model training system, accordingly, the illegal induced occupation behaviors can be identified for data from different channels, and early warning, return visit, countercheck and striking are carried out successively through an anti-fraud service system, so that the cheating probability and property loss of a victim are reduced, the cheating details of the victim are recorded, the illegal induced occupation activity channel of the illegal induced occupation activity molecules is sealed, and the real identity of the illegal induced occupation activity molecules is identified; the problem of prior art carry out unified data processing and analysis precision relatively poor is solved.
Drawings
FIG. 1 is a schematic block diagram of a fraud prevention control system disclosed in CN 108156333A.
FIG. 2 is a schematic block diagram of the integrated anti-fraud platform in the preferred embodiment of the present invention.
Detailed Description
The present invention provides a comprehensive anti-fraud platform, method and storage medium, and in order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The present invention provides a comprehensive anti-fraud platform, as shown in fig. 2, comprising: the classification model building system 100, the model training system 200, the data acquisition system 300, the resource storage system 400 and the anti-fraud business system 500.
The classification model construction system 100 is used for respectively constructing a first wanted illegal induced occupation identification model, a first bank card illegal induced occupation identification model and a first network loan illegal induced occupation identification model according to the ticket data, the wanted illegal induced occupation behavior data set, the bank card illegal induced occupation behavior data set and the network loan illegal induced occupation behavior data set; and the online shopping order illegal induction possession identification model is used for respectively constructing a second network loan illegal induction possession identification model, a first order brushing illegal induction possession identification model, a first impersonation friend illegal induction possession identification model, a first online shopping order illegal induction possession identification model, a first investment illegal induction possession identification model and a first game recharging illegal induction possession identification model according to the behavior data set reserved on the Internet by the illegal induction possession activity.
It can be understood that there are at least two embodiments of the illegal share-inducing activity of the network loan: the first is telephone, the second is network; in contrast, the method and the device respectively construct the first network loan illegal induction occupation identification model and the second network loan illegal induction occupation identification model to accurately identify illegal induction occupation behaviors of the same type but different channels.
In a preferred embodiment of the present invention, the classification model construction system 100 can construct a plurality of illegal induced occupation identification models occupied by illegal induction through telephone contact with the victim according to the illegal induced occupation behavior data set of the illegal induced occupation event set and the corresponding call ticket data, and at the same time, construct a plurality of illegal induced occupation identification models occupied by illegal induction through network contact with the victim according to the relevant illegal induced occupation behavior data set retained on the internet, so that the system has strong pertinence, and can effectively identify the corresponding types of illegal induced occupation behaviors.
The model training system 200 is configured to train the models constructed by the classification model construction system 100 through a machine learning technology, and obtain a second illegal induction occupation identification model of the official account, a second illegal induction occupation identification model of the bank card, an illegal induction occupation identification model of the third network loan, an illegal induction occupation identification model of the fourth network loan, an illegal induction occupation identification model of the second swipe order, an illegal induction occupation identification model of the second impersonation friend, an illegal induction occupation identification model of the second online purchase order, an illegal induction occupation identification model of the second investment, and an illegal induction occupation identification model of the second game recharge.
In order to improve the accuracy of the model, the invention continuously provides data for the constructed model through a machine learning technology to enable the constructed model to be learned, the obtained final model is a machine learning product, and the training process is a learning process. The illegal induction and occupation identification model of second negotiable order, the illegal induction and occupation identification model of second bank card and the illegal induction and occupation identification model of third network loan, the illegal induction and occupation identification model of fourth network loan, the illegal induction and occupation identification model of second swiping order, the illegal induction and occupation identification model of second impersonation friend, the illegal induction and occupation identification model of second network purchase order, the illegal induction and occupation identification model of second investment and the illegal induction and occupation identification model of second game recharging are respectively a first illegal induction and occupation identification model of common bussiness, an illegal induction and occupation identification model of first bank card, an illegal induction and occupation identification model of first network loan, an illegal induction and occupation identification model of second network loan, an illegal induction and occupation identification model of first swiping order, an illegal induction and occupation identification model of first impersonation friend, an illegal induction and occupation identification model of first network purchase order, a illegal induction and occupation identification model of first network loan, And the model obtained by training the first investment illegal induced occupation recognition model and the first game recharge illegal induced occupation recognition model.
The data acquisition system 300 is configured to acquire first network data, receive ticket data, and second network data provided by a network service provider through a web crawler technology, perform various illegal induced occupation behavior identifications using a model obtained by training of the model training system 200, and extract illegal induced occupation activity data.
In a further preferred embodiment of the invention, the required data can be acquired by an attack and defense penetration technology, a network agent technology, a password cracking technology, a terminal remote control technology, a port scanning technology fingerprint identification technology and a social fishing technology, so that the comprehensiveness of the data and the accuracy of the constructed model are improved in a manner of enriching the sources of the data; the data is preferably transmitted using link encryption techniques, and the data is processed using user rendering techniques and big data processing techniques.
The resource storage system 400 includes: a black pool resource pool, the black pool resource pool comprising: the social software account black library, the mobile phone number black library, the IP black library and the URL black library are respectively used for storing the fraud-related social software account, the fraud-related mobile phone number, the fraud-related IP and the fraud-related URL in the illegal induction possession activity data.
In a further preferred embodiment of the present invention, the resource storage system 400 further comprises: the system comprises an early warning resource pool, an anti-illegal induction occupation data resource pool and an IP-geographic position library, wherein the early warning resource pool comprises: the method comprises the steps that an illegal induction of network loan is taken up in an early warning library, an illegal induction of swiping a bill is taken up in the early warning library, an illegal induction of investment is taken up in the early warning library, an illegal induction of counterfeit identity is taken up in the early warning library, an illegal induction of online shopping orders is taken up in the early warning library, an illegal induction of game recharging is taken up in the early warning library, an illegal induction of deep loan is taken up in the early warning library, an illegal induction of wanted orders is taken up in the early warning library and an illegal induction of bank cards is taken up in the early warning library; the network loan illegal induction possession early warning library, the billing illegal induction possession early warning library, the investment illegal induction possession early warning library, the counterfeit identity illegal induction possession early warning library, the online shopping order illegal induction possession early warning library, the game recharging illegal induction possession early warning library, the deep loan illegal induction possession early warning library, the wanted illegal induction possession early warning library and the bank card illegal induction possession early warning library, the method is used for storing the early warning data of illegal induction possession of network loan, the early warning data of illegal induction possession of billing, the early warning data of illegal induction possession of investment, the early warning data of illegal induction possession of counterfeit identity, the early warning data of illegal induction possession of online shopping orders, the early warning data of illegal induction possession of game recharge, the early warning data of illegal induction possession of deep loan, the early warning data of illegal induction possession of wanted order and the early warning data of illegal induction possession of bank cards before the early warning is finished.
The method for preventing illegal induction from occupying the data resource pool comprises the following steps: the system comprises a social number corresponding database and an identity number corresponding database, wherein the social number corresponding database is used for storing the corresponding relation between a social software account and a mobile phone number, and the identity number corresponding database is used for storing the corresponding relation between identity information and the mobile phone number; the IP-geographic position library is used for storing the fraud-related IP and the geographic position corresponding to the fraud-related IP.
The anti-fraud service system 500 includes: the early warning center is used for carrying out anti-fraud prompt on victims according to illegal induced occupation activity data, the revisiting center is used for revising and reporting the results of illegal induced occupation events, the countering center is used for forbidding illegal induced occupation activity channels, and the attacking center is used for identifying the identity of illegal induced occupation activity molecules.
In a further preferred embodiment of the present invention, the anti-fraud service system 500 further comprises: the propaganda center, synthesize anti-fraud platform still includes: the mobile phone user side is used for receiving user registration and label information filled in during registration, and the label information comprises: gender and age tags; the propaganda center is used for pushing propaganda materials to the mobile phone user side according to the label information. The task distribution system is used for generating early warning tasks according to data of an early warning resource pool and sending the early warning tasks to a public number early warning system of an early warning center, the PC end early warning system is used for monitoring task getting conditions and task completing conditions of the APP early warning system, the public number early warning system is used for sending information to a user according to a preset early warning template, and the APP early warning system is used for displaying an early warning task list so that early warning personnel can get the tasks.
In specific implementation, the early warning center further comprises: the task distribution system is also used for sending the early warning task to the public number early warning system of the early warning center and sending the early warning task to the PC end early warning system and the APP early warning system.
The invention also provides an anti-fraud method based on the comprehensive anti-fraud platform, which comprises the following steps:
s100, a classification model construction system respectively constructs a first wanted illegal induced possession identification model, a first bank card illegal induced possession identification model and a first network loan illegal induced possession identification model according to the ticket data, the wanted illegal induced possession behavior data set, the bank card illegal induced possession behavior data set and the network loan illegal induced possession behavior data set; meanwhile, according to a behavior data set retained on the internet by illegal induced possession activities, respectively constructing a second network loan illegal induced possession identification model, a first swipe illegal induced possession identification model, a first impersonation friend illegal induced possession identification model, a first online purchase order illegal induced possession identification model, a first investment illegal induced possession identification model and a first game recharge illegal induced possession identification model, which are specifically shown in the above device embodiment;
s200, the model training system trains the models constructed by the classification model construction system through a machine learning technology, and respectively obtains a second illegal account pickup identification model, a second bank card illegal account pickup identification model, a third network loan illegal account pickup identification model, a fourth network loan illegal account pickup identification model, a second swiping illegal account pickup identification model, a second fake friend illegal account pickup identification model, a second online shopping order illegal account pickup identification model, a second investment illegal account pickup identification model and a second game illegal account pickup identification model, which are specifically shown in the embodiment of the device;
s300, a data acquisition system acquires first network data, receives call ticket data and second network data provided by a network service provider through a network crawler technology, performs various illegal induced occupation behavior identifications by using a model obtained by training of a model training system, and extracts illegal induced occupation activity data, wherein the data acquisition system is specifically shown in the embodiment of the device;
s400, constructing a social software account black library, a mobile phone number black library, an IP black library and a URL black library, and respectively storing the fraud-related social software account, the fraud-related mobile phone number, the fraud-related IP and the fraud-related URL in the extracted illegal induced possession activity data in the social software account black library, the mobile phone number black library, the IP black library and the URL black library, which are specifically shown in the above device embodiment;
s500, the early warning center carries out anti-fraud prompt on the victim according to the illegal induction occupation activity data, and the method is specifically shown in the embodiment of the device;
s600, the return visit center returns and reports the result of the illegal induced occupation event, and the return visit center is specifically shown in the embodiment of the device;
s700, the anti-braking center blocks the illegal induction activity channel, and the embodiment of the device is specifically shown;
s800, the striking center identifies the identity of the illegally induced possessed moving molecule, and the specific embodiment of the device is shown in the embodiment.
Preferably, the anti-fraud method disclosed by the present invention has all the technical features and technical effects of the above-mentioned device embodiments, and the detailed description of the present invention is omitted.
A storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the anti-fraud method as described above. The storage medium includes all the technical features of the anti-fraud method, and therefore, all the technical effects of the anti-fraud method are also provided, and are not described in detail.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), synchronous Link (SyNchlinNk) DRAM (SLDRAM), Rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: rather, the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Moreover, those of skill in the art will appreciate that while some embodiments herein include some features included in other embodiments, not others, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, any of the claimed embodiments may be used in any combination.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specified otherwise.
Claims (10)
1. An integrated anti-fraud platform, comprising: the system comprises a classification model construction system, a model training system, a data acquisition system, a resource storage system and an anti-fraud service system;
the classification model construction system is used for respectively constructing a first wanted illegal induced occupation identification model, a first bank card illegal induced occupation identification model and a first network loan illegal induced occupation identification model according to the ticket data, the wanted illegal induced occupation behavior data set, the bank card illegal induced occupation behavior data set and the network loan illegal induced occupation behavior data set;
the online shopping order illegal induction possession identification model is used for establishing a second network loan illegal induction possession identification model, a first order swiping illegal induction possession identification model, a first impersonation friend illegal induction possession identification model, a first online shopping order illegal induction possession identification model, a first investment illegal induction possession identification model and a first game recharging illegal induction possession identification model respectively according to a behavior data set reserved on the Internet by illegal induction possession activities;
the model training system is used for training the models constructed by the classification model construction system through a machine learning technology, and respectively obtaining a second illegal account pickup identification model, a second bank card illegal account pickup identification model, a third network loan illegal account pickup identification model, a fourth network loan illegal account pickup identification model, a second swiping illegal account pickup identification model, a second impersonation friend illegal account pickup identification model, a second online shopping order illegal account pickup identification model, a second investment illegal account pickup identification model and a second game recharging illegal account pickup identification model;
the data acquisition system is used for acquiring first network data, receiving call ticket data and second network data provided by a network service provider through a network crawler technology, performing various illegal induced occupation behavior identifications by using a model obtained by training of a model training system, and extracting illegal induced occupation activity data;
the resource storage system includes: a black pool resource pool, the black pool resource pool comprising: the social software account black library, the mobile phone number black library, the IP black library and the URL black library are respectively used for storing a fraud-related social software account, a fraud-related mobile phone number, a fraud-related IP and a fraud-related URL in the illegal induction possession activity data;
the anti-fraud service system includes: the early warning center is used for carrying out anti-fraud prompt on victims according to illegal induced occupation activity data, the revisiting center is used for revising and reporting the results of illegal induced occupation events, the countering center is used for forbidding illegal induced occupation activity channels, and the attacking center is used for identifying the identity of illegal induced occupation activity molecules.
2. The integrated anti-fraud platform of claim 1, wherein the resource storage system further comprises: an early warning resource pool, the early warning resource pool comprising: the method comprises the steps that an illegal induction of network loan is taken up in an early warning library, an illegal induction of swiping a bill is taken up in the early warning library, an illegal induction of investment is taken up in the early warning library, an illegal induction of counterfeit identity is taken up in the early warning library, an illegal induction of online shopping orders is taken up in the early warning library, an illegal induction of game recharging is taken up in the early warning library, an illegal induction of deep loan is taken up in the early warning library, an illegal induction of wanted orders is taken up in the early warning library and an illegal induction of bank cards is taken up in the early warning library;
the network loan illegal induction possession early warning library, the billing illegal induction possession early warning library, the investment illegal induction possession early warning library, the counterfeit identity illegal induction possession early warning library, the online shopping order illegal induction possession early warning library, the game recharging illegal induction possession early warning library, the deep loan illegal induction possession early warning library, the wanted illegal induction possession early warning library and the bank card illegal induction possession early warning library, the method is used for storing the early warning data of illegal induced possession of network loan, the early warning data of illegal induced possession of swiping order, the early warning data of illegal induced possession of investment, the early warning data of illegal induced possession of counterfeit identity, the early warning data of illegal induced possession of network purchase order, the early warning data of illegal induced possession of game charge, the early warning data of illegal induced possession of deep loan, the early warning data of illegal induced possession of wanted order and the early warning data of illegal induced possession of bank card before the early warning is finished.
3. The integrated anti-fraud platform according to claim 2, wherein said resource storage system further comprises: the method comprises the following steps that anti-illegal induction occupies a data resource pool, and the anti-illegal induction occupies the data resource pool and comprises the following steps: the system comprises a social number corresponding database and an identity number corresponding database, wherein the social number corresponding database is used for storing the corresponding relation between a social software account and a mobile phone number, and the identity number corresponding database is used for storing the corresponding relation between identity information and the mobile phone number.
4. The integrated anti-fraud platform according to claim 3, wherein said resource storage system further comprises: an IP-geolocation repository for storing fraud-related IPs and geographic locations corresponding to the fraud-related IPs.
5. The integrated anti-fraud platform according to claim 4, wherein said anti-fraud business system further comprises: the propaganda center, synthesize anti-fraud platform still includes: the mobile phone user side is used for receiving user registration and label information filled in during the registration, and the label information comprises: gender and age tags; the propaganda center is used for pushing propaganda materials to the mobile phone user side according to the label information.
6. The integrated anti-fraud platform of claim 5, wherein said data collection system further comprises a data center for performing data cleaning, information parsing, format unification, and home zone collision on said first network data, ticket data, and second network data.
7. The integrated anti-fraud platform of claim 6, wherein said integrated anti-fraud platform further comprises: the system comprises a task distribution system, a PC (personal computer) end early warning system, a public number early warning system and an APP (application) early warning system, wherein the task distribution system is used for generating early warning tasks according to data of an early warning resource pool and sending the early warning tasks to the public number early warning system of an early warning center, the PC end early warning system is used for monitoring task getting conditions and task completion conditions of the APP early warning system, the public number early warning system is used for sending information to a user according to a preset early warning template, and the APP early warning system is used for displaying an early warning task list so as to enable early warning personnel to get the tasks.
8. The integrated anti-fraud platform of claim 7, wherein said early warning center further comprises: the task distribution system is also used for sending the early warning task to the public number early warning system of the early warning center and sending the early warning task to the PC end early warning system and the APP early warning system.
9. An anti-fraud method implemented based on said integrated anti-fraud platform of any one of claims 1 to 8, comprising:
the classification model construction system respectively constructs a first wanted illegal induced possession identification model, a first bank card illegal induced possession identification model and a first network loan illegal induced possession identification model according to the ticket data, the wanted illegal induced possession behavior data set, the bank card illegal induced possession behavior data set and the network loan illegal induced possession behavior data set; meanwhile, according to a behavior data set reserved on the Internet by illegal induced possession activities, respectively constructing a second network loan illegal induced possession identification model, a first order-swiping illegal induced possession identification model, a first impersonation friend illegal induced possession identification model, a first online purchase order illegal induced possession identification model, a first investment illegal induced possession identification model and a first game illegal recharge induced possession identification model;
the model training system trains the models constructed by the classification model construction system through a machine learning technology, and respectively obtains a second illegal accrual instruction induction possession identification model, a second bank card illegal accrual instruction possession identification model, a third network loan illegal accrual instruction possession identification model, a fourth network loan illegal accrual instruction possession identification model, a second swiping illegal accrual instruction possession identification model, a second impersonation friend illegal accrual instruction possession identification model, a second online shopping order illegal accrual instruction possession identification model, a second investment illegal accrual instruction possession identification model and a second game accrual illegal accrual instruction possession identification model;
the data acquisition system acquires first network data, received call ticket data and second network data provided by a network service provider through a network crawler technology, performs various illegal induced occupation behavior identifications by utilizing a model obtained by training of a model training system, and extracts illegal induced occupation activity data;
constructing a social software account black library, a mobile phone number black library, an IP black library and a URL black library, and respectively storing the fraud-related social software account, the fraud-related mobile phone number, the fraud-related IP and the fraud-related URL in the extracted illegal induction occupation activity data in the social software account black library, the mobile phone number black library, the IP black library and the URL black library;
the early warning center carries out anti-fraud prompt on the victim according to the illegal induction occupation activity data;
the return visit center returns the visit report of the result of the illegal induction occupation event;
the anti-control center seals off the illegal induction activity occupation channel;
the strike center identifies the identity of the illegal induction possessing activity molecules.
10. A storage medium having stored thereon a computer program, characterized in that the computer program, when being executed by a processor, realizes the steps of the anti-fraud method as claimed in claim 9.
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