CN106713288A - Fraud risk identification and prevention method and system - Google Patents
Fraud risk identification and prevention method and system Download PDFInfo
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- CN106713288A CN106713288A CN201611123562.0A CN201611123562A CN106713288A CN 106713288 A CN106713288 A CN 106713288A CN 201611123562 A CN201611123562 A CN 201611123562A CN 106713288 A CN106713288 A CN 106713288A
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- fraud
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/1483—Countermeasures against malicious traffic service impersonation, e.g. phishing, pharming or web spoofing
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- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Computer Hardware Design (AREA)
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- General Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
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- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The embodiment of the invention provides a fraud risk identification and prevention method and system. The fraud risk identification and prevention method and system specifically comprises the following steps: firstly receiving device feature information uploaded by a mobile device; then determining fraud behavior features of the mobile device according to the device feature information; and finally calculating the fraud behavior features by using a preset device fraud feature model to obtain a fraud risk index of the mobile device. The fraud risk index can reflect the possible fraud risk of the mobile device, so that a customer can take corresponding prevention measures according to the fraud risk index.
Description
Technical field
The present invention relates to Internet technical field, more particularly to a kind of risk of fraud identification, prevention method and system.
Background technology
With the development of mobile interchange, 80% business occurs on the mobile apparatus, accordingly, absolutely in current online transaction
Most network fraud behavior also all occurs on the mobile apparatus, is that this must do to the fraud occurred on mobile device
It is good to take precautions against.Traditional is mainly based upon what device history behavior was identified for fraud, such as come for rubbish registration
Say that it, based on the equipment a large amount of registrations in a short time, is handed over based on a large amount of frauds for occurring in a short time for high frequency fraudulent trading to be
It is easy to be.Can there is certain hysteresis quality for the fraud recognition methods based on device history behavior, specially in fraud
Risk prevention system rule could be triggered after the certain number of times of generation, it is impossible to fraud is identified in time.
The content of the invention
In view of this, the invention provides a kind of identification of risk of fraud, prevention method and system, for mobile device
Risk of fraud is identified, so that client can take the corresponding measure to carry out risk prevention according to risk of fraud.
In order to solve the above problems, the invention discloses a kind of risk of fraud recognition methods, step is specifically included：
Receive the apparatus characteristic information that mobile device is uploaded；
The fraud feature of the mobile device is determined according to the apparatus characteristic information；
The fraud feature is calculated using default equipment fraud characteristic model, obtains the mobile device
Risk of fraud index.
Optionally, the apparatus characteristic information includes basic hardware information, the network information, running state information and application letter
It is part or all of in breath.
Optionally, the fraud feature row includes that hardware information exception, agency use feature, feature of escaping from prison, brush machine
Feature, program debugging feature, simulator locating feature and plug-in instrument use part or all of in feature.
Optionally, the equipment fraud characteristic model is obtained as follows：
Default fraud Mathematical Modeling；
Obtain history fraud collection；
The fraud Mathematical Modeling is trained using the history fraud collection and the fraud characteristic behavior, is obtained
Characteristic model is cheated to the equipment.
In addition, present invention also offers a kind of risk of fraud prevention method, including step：
When mobile device initiating business request, the apparatus characteristic information of the mobile device is obtained；
The apparatus characteristic information is processed according to risk of fraud recognition methods as described above, obtains the movement
The risk of fraud index of equipment；
The service request is disposed according to the risk of fraud index and default risk control threshold value.
Accordingly, in order to ensure the implementation of the above method, present invention also offers a kind of risk of fraud identifying system, specifically
Including：
Characteristic information receiver module, the apparatus characteristic information for receiving mobile device upload；
Behavioural characteristic determining module, the fraud for determining the mobile device according to the apparatus characteristic information is special
Levy；
Risk index computing module, for being carried out to the fraud feature using default equipment fraud characteristic model
Calculate, obtain the risk of fraud index of the mobile device.
Optionally, the apparatus characteristic information includes basic hardware information, the network information, running state information and application letter
It is part or all of in breath.
Optionally, the fraud feature row includes that hardware information exception, agency use feature, feature of escaping from prison, brush machine
Feature, program debugging feature, simulator locating feature and plug-in instrument use part or all of in feature.
Optionally, also including model training module, the model training module includes：
Mathematical Modeling preset unit, for presetting a fraud Mathematical Modeling；
Fraud acquiring unit, for obtaining history fraud collection；
Fraud model training unit, for being taken advantage of to described using the history fraud collection and the fraud characteristic behavior
Swindleness Mathematical Modeling is trained, and obtains the equipment fraud characteristic model.
In addition, present invention also offers a kind of risk of fraud crime prevention system, including：
Characteristic information acquisition module, for when mobile device initiating business request, the equipment for obtaining the mobile device
Characteristic information；
Risk index determining module, for according to the risk of fraud identifying system pair as described in any one of claim 6~9
The apparatus characteristic information is processed, and obtains the risk of fraud index of the mobile device；
Risk control module, for being asked to the business according to the risk of fraud index and default risk control threshold value
Ask and be disposed.
From above-mentioned technical proposal as can be seen that the invention provides a kind of identification of risk of fraud, prevention method and system, being somebody's turn to do
Risk of fraud recognition methods and system specially receive the apparatus characteristic information that mobile device is uploaded first；Then it is special according to equipment
Reference breath determines the fraud feature of mobile device；Finally characteristic model is cheated to fraud feature using default equipment
Calculated, obtained the risk of fraud index of the mobile device.The risk of fraud index can reflect that mobile device is possible and take advantage of
Swindleness risk, such that it is able to enable a customer to take the corresponding precautionary measures according to the risk of fraud index.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 for the present invention provide a kind of risk of fraud recognition methods embodiment the step of flow chart；
Fig. 2 is flow chart the step of a kind of equipment that the present invention is provided cheats the acquisition methods of characteristic model；
Fig. 3 for the present invention provide a kind of risk of fraud prevention method embodiment the step of flow chart.
A kind of structured flowchart of risk of fraud identifying system embodiment that Fig. 4 is provided for the present invention；
The structured flowchart of another risk of fraud identifying system that Fig. 5 is provided for the present invention；
A kind of structured flowchart of risk of fraud crime prevention system embodiment that Fig. 6 is provided for the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
Embodiment one
Fig. 1 for the present invention provide a kind of risk of fraud recognition methods embodiment the step of flow chart,
Shown in reference picture 1, the risk that the risk of fraud recognition methods that the present embodiment is provided is applied in operation system is known
Other server, for being identified to possible risk of fraud in process of exchange, specific method comprises the following steps：
S101：Receive the apparatus characteristic information that mobile device is uploaded.
Here mobile device presets the information mould existed with APP forms or SDK form
Block, the module is used to obtain the equipment characteristic parameter of mobile device, and the equipment characteristic parameter is uploaded into risk identification clothes
Business device, so as to its further treatment.
The apparatus characteristic information is using the portion in basic hardware information, the network information, running state information and application message
Divide information or full detail.
Basic hardware information includes cpu information, memory information, hard disk information, sensor (temperature, position, gyroscope) letter
Breath, IMEI, IMSI, mac address information etc.；
The network information is then including network agent information, TCP network protocol stacks information, base station information, operator's informaiton etc.；
Whether first running state information then including available machine time information, battery usage amount, appearance, location information etc.；
Application message include the mobile device whether escape from prison or brush machine, the application program installed thereon whether official's application peace
Dress etc..
S102：The fraud feature of mobile device is determined according to apparatus characteristic information.
After the apparatus characteristic information for obtaining mobile device, the fraud of the mobile device is determined according to the apparatus characteristic information
Behavioural characteristic.So-called fraud refers to some settings or operation to mobile device by user, for validated user
Seldom brush machine is carried out to equipment, is escaped from prison etc. modification；And for disabled user, the physical equipment that it is held typically more has
Old apparatus modifications are new equipment often through simulator, the machine instrument, instrument of escaping from prison, so if can be according to obtaining by limit
Equipment characteristic parameter obtain the fraud feature of some doubtful frauds if, it becomes possible to as determining whether fraud
Foundation.
Here fraud feature includes that hardware information exception, agency use feature, feature of escaping from prison, brush machine feature, journey
Sequence debugging feature, simulator locating feature and plug-in instrument use part or all of in feature.Features described above represents user to it
Mobile device in hand has carried out corresponding act of revision, to evade to the legal tracking of the mobile device and positioning.
S103：The risk of fraud index of mobile device is calculated according to equipment wherein characteristic model.
After the fraud feature for obtaining mobile device, the fraud feature is substituted into default equipment fraud feature
Model, by the risk of fraud index for being calculated the mobile device of many fraud features.The risk of fraud index can
Reflect the risk of fraud of the mobile device, risk of fraud here refers to that the mobile device is cheated in network trading behavior
Possibility, the index is more high, and the possibility that expression is cheated is higher, so as to enable a customer to the height according to the index
Taken precautions against accordingly.
From above-mentioned technical proposal as can be seen that present embodiments providing a kind of risk of fraud recognition methods, the method is specific
To receive the apparatus characteristic information of mobile device upload first；Then the fraud row of mobile device is determined according to apparatus characteristic information
It is characterized；Fraud feature is calculated using default equipment fraud characteristic model finally, the mobile device is obtained
Risk of fraud index.The risk of fraud index can reflect the possible risk of fraud of mobile device, such that it is able to enable a customer to
The corresponding precautionary measures are taken according to the risk of fraud index.
Equipment fraud characteristic model in the present embodiment can be obtained by the following method, and the method specifically includes as follows
Step, shown in reference picture 2：
S2001：Default fraud Mathematical Modeling.
For example, fraud Mathematical Modeling is：P=p1x1+p2x2+p3x3+ ...
S2002：Obtain history fraud collection.
For example, obtain history fraud collection E1, E2, E3 ... ... .., for entering to above-mentioned fraud Mathematical Modeling
Row training.
S2003：It is trained using history fraud set pair fraud Mathematical Modeling.
Above-mentioned fraud Mathematical Modeling is substituted into using above-mentioned history fraud collection, is carried out by the fraud Mathematical Modeling
Training obtains model parameter, and obtains equipment fraud characteristic model according to the model parameter and fraud Mathematical Modeling.
Embodiment two
Fig. 3 for the present invention provide a kind of risk of fraud prevention method embodiment the step of flow chart.
Shown in reference picture 3, the risk of fraud prevention method that the present embodiment is provided is applied to the air control service in operation system
Device, is taken precautions against for possible risk of fraud in process of exchange, and to avoid making client cause damage, the method specifically includes step
Suddenly：
S301：When mobile device initiating business request, the apparatus characteristic information of mobile device is obtained.
When there are the mobile devices such as mobile phone or panel computer to initiate the service requests such as shopping, registration, the mobile device is obtained
Apparatus characteristic information.Mobile device initiates the approach of above-mentioned service request generally by the application journey installed on mobile device
Sequence implement, we can in the application program in the form of Software tool kit preset corresponding information collection module,
The information collection module is used to collect the equipment characteristic parameter of the mobile device, and the parameter is uploaded into air control server.
Here equipment characteristic parameter is identical with the apparatus characteristic information of a upper embodiment, repeats no more here.
S302：The risk of fraud index of mobile device is determined according to apparatus characteristic information.
After the said equipment characteristic information is obtained, using a kind of risk of fraud recognition methods of embodiment to the equipment special efficacy
Information is processed, and obtains the risk of fraud index of the mobile device of initiating business request, and the index can use hundred-mark system, example
As 1 point of risk is minimum, and 100 points of risk highests.
Because the risk of fraud method that the present embodiment is provided is applied to air control server, and the risk of fraud recognition methods should
For risk identification server.Therefore in the specific implementation, air control server sends the said equipment characteristic information during this step
To risk identification server, the risk identification server can be processed the equipment characteristic parameter, known using the risk of fraud
Other method obtains risk of fraud index and is back to the air control server.
S303：Service request is disposed according to risk of fraud index and risk control threshold value.
The risk control threshold value is a control parameter being preset in advance in air control server, is taken when risk of fraud is recognized
After the risk of fraud index that business device is returned, the index is compared with risk control threshold value, and according to specific comparative result
Corresponding Disposal Measures are taken, avoids being caused damage to client with this.
Specific Disposal Measures include：When risk of fraud index is less than the risk control threshold value, the mobile device is judged
There is no risk or risk relatively low, now allow the service server in operation system to receive the service request, and according to the industry
Business request performs corresponding operation；When risk of fraud index is equal to or higher than the risk control threshold value, the mobile device is judged
Risk it is higher, now control the service server refuse receive the service request, so as to realize the protection to client.
From above-mentioned technical proposal as can be seen that present embodiments providing a kind of risk of fraud prevention method, the method application
In air control server, specially when mobile device initiating business request, the apparatus characteristic information of mobile device is obtained；Then root
The risk of fraud index of mobile device is determined according to default risk of fraud recognition methods；Finally according to risk of fraud index and default
Risk control threshold value service request is disposed, specific Disposal Measures include allow or refusal service server receive the industry
Business request, so as to realize protecting client to avoid the purpose for incurring loss.
It should be noted that for embodiment of the method, in order to be briefly described, therefore it to be all expressed as a series of action group
Close, but those skilled in the art should know, and the embodiment of the present invention is not limited by described sequence of movement, because according to
According to the embodiment of the present invention, some steps can sequentially or simultaneously be carried out using other.Secondly, those skilled in the art also should
Know, embodiment described in this description belongs to preferred embodiment, the involved action not necessarily present invention is implemented
Necessary to example.
Embodiment three
A kind of structured flowchart of risk of fraud identifying system embodiment that Fig. 4 is provided for the present invention,
Shown in reference picture 4, the risk that the risk of fraud identifying system that the present embodiment is provided is applied in operation system is known
Other server, for being identified to possible risk of fraud in process of exchange, the system specifically includes characteristic information and receives mould
Block 10, behavioural characteristic determining module 20 and risk index computing module 30.
Characteristic information receiver module 10 is used to receive the apparatus characteristic information of mobile device upload.
Here mobile device presets the information mould existed with APP forms or SDK form
Block, the module is used to obtain the equipment characteristic parameter of mobile device, and the equipment characteristic parameter is uploaded into risk identification clothes
Business device, so as to its further treatment.
The apparatus characteristic information is using the portion in basic hardware information, the network information, running state information and application message
Divide information or full detail.
Basic hardware information includes cpu information, memory information, hard disk information, sensor (temperature, position, gyroscope) letter
Breath, IMEI, IMSI, mac address information etc.；
The network information is then including network agent information, TCP network protocol stacks information, base station information, operator's informaiton etc.；
Whether first running state information then including available machine time information, battery usage amount, appearance, location information etc.；
Application message include the mobile device whether escape from prison or brush machine, the application program installed thereon whether official's application peace
Dress etc..
Behavioural characteristic determining module 20 is used to determine according to apparatus characteristic information the fraud feature of mobile device.
After the apparatus characteristic information for obtaining mobile device, the fraud of the mobile device is determined according to the apparatus characteristic information
Behavioural characteristic.So-called fraud refers to some settings or operation to mobile device by user, for validated user
Seldom brush machine is carried out to equipment, is escaped from prison etc. modification；And for disabled user, the physical equipment that it is held typically more has
Old apparatus modifications are new equipment often through simulator, the machine instrument, instrument of escaping from prison, so if can be according to obtaining by limit
Equipment characteristic parameter obtain the fraud feature of some doubtful frauds if, it becomes possible to as determining whether fraud
Foundation.
Here fraud feature includes that hardware information exception, agency use feature, feature of escaping from prison, brush machine feature, journey
Sequence debugging feature, simulator locating feature and plug-in instrument use part or all of in feature.Features described above represents user to it
Mobile device in hand has carried out corresponding act of revision, to evade to the legal tracking of the mobile device and positioning.
Risk indicates computing module 30 for calculating the risk of fraud index of mobile device according to equipment wherein characteristic model.
After the fraud feature for obtaining mobile device, the fraud feature is substituted into default equipment fraud feature
Model, by the risk of fraud index for being calculated the mobile device of many fraud features.The risk of fraud index can
Reflect the risk of fraud of the mobile device, risk of fraud here refers to that the mobile device is cheated in network trading behavior
Possibility, the index is more high, and the possibility that expression is cheated is higher, so as to enable a customer to the height according to the index
Taken precautions against accordingly.
From above-mentioned technical proposal as can be seen that present embodiments providing a kind of risk of fraud identifying system, the system is specific
To receive the apparatus characteristic information of mobile device upload first；Then the fraud row of mobile device is determined according to apparatus characteristic information
It is characterized；Fraud feature is calculated using default equipment fraud characteristic model finally, the mobile device is obtained
Risk of fraud index.The risk of fraud index can reflect the possible risk of fraud of mobile device, such that it is able to enable a customer to
The corresponding precautionary measures are taken according to the risk of fraud index.
Model training module 40 is also included in the present embodiment, shown in reference picture 5, the model training module 40 is used to obtain
Equipment fraud characteristic model specifically includes Mathematical Modeling preset unit 41, fraud acquiring unit 42 and fraud model training list
Unit 43.
Mathematical Modeling preset unit 41 is used to preset a fraud Mathematical Modeling.
For example, fraud Mathematical Modeling is：P=p1x1+p2x2+p3x3+ ...
Fraud acquiring unit 42 is used to obtain history fraud collection.
For example, obtain history fraud collection E1, E2, E3 ... ... .., for entering to above-mentioned fraud Mathematical Modeling
Row training.
Fraud model training unit 43 is used to be trained using history fraud set pair fraud Mathematical Modeling.
Above-mentioned fraud Mathematical Modeling is substituted into using above-mentioned history fraud collection, is carried out by the fraud Mathematical Modeling
Training obtains model parameter, and obtains equipment fraud characteristic model according to the model parameter and fraud Mathematical Modeling.
Example IV
A kind of structured flowchart of risk of fraud crime prevention system embodiment that Fig. 6 is provided for the present invention.
Shown in reference picture 6, the risk of fraud crime prevention system that the present embodiment is provided is applied to the air control service in operation system
Device, is taken precautions against for possible risk of fraud in process of exchange, and to avoid making client cause damage, the system specifically includes spy
Levy data obtaining module 50, risk index determining module 60 and risk control module 70.
Characteristic information acquisition module 50 is used to be obtained when mobile device initiating business request the equipment feature of mobile device
Information.
When there are the mobile devices such as mobile phone or panel computer to initiate the service requests such as shopping, registration, the mobile device is obtained
Apparatus characteristic information.Mobile device initiates the approach of above-mentioned service request generally by the application journey installed on mobile device
Sequence implement, we can in the application program in the form of Software tool kit preset corresponding information collection module,
The information collection module is used to collect the equipment characteristic parameter of the mobile device, and the parameter is uploaded into air control server.
Here equipment characteristic parameter is identical with the apparatus characteristic information of a upper embodiment, repeats no more here.
Risk index determining module 60 is used to determine according to apparatus characteristic information the risk of fraud index of mobile device.
After the said equipment characteristic information is obtained, using a kind of risk of fraud recognition methods of embodiment to the equipment special efficacy
Information is processed, and obtains the risk of fraud index of the mobile device of initiating business request, and the index can use hundred-mark system, example
As 1 point of risk is minimum, and 100 points of risk highests.
Because the risk of fraud method that the present embodiment is provided is applied to air control server, and the risk of fraud recognition methods should
For risk identification server.Therefore in the specific implementation, air control server sends the said equipment characteristic information during this step
To risk identification server, the risk identification server can be processed the equipment characteristic parameter, known using the risk of fraud
Other method obtains risk of fraud index and is back to the air control server.
Risk control module 70 is used to be disposed service request according to risk of fraud index and risk control threshold value.
The risk control threshold value is a control parameter being preset in advance in air control server, is taken when risk of fraud is recognized
After the risk of fraud index that business device is returned, the index is compared with risk control threshold value, and according to specific comparative result
Corresponding Disposal Measures are taken, avoids being caused damage to client with this.
Specific Disposal Measures include：When risk of fraud index is less than the risk control threshold value, the mobile device is judged
There is no risk or risk relatively low, now allow the service server in operation system to receive the service request, and according to the industry
Business request performs corresponding operation；When risk of fraud index is equal to or higher than the risk control threshold value, the mobile device is judged
Risk it is higher, now control the service server refuse receive the service request, so as to realize the protection to client.
From above-mentioned technical proposal as can be seen that present embodiments providing a kind of risk of fraud crime prevention system, the system application
In air control server, specially when mobile device initiating business request, the apparatus characteristic information of mobile device is obtained；Then root
The risk of fraud index of mobile device is determined according to default risk of fraud recognition methods；Finally according to risk of fraud index and default
Risk control threshold value service request is disposed, specific Disposal Measures include allow or refusal service server receive the industry
Business request, so as to realize protecting client to avoid the purpose for incurring loss.
For device embodiment, because it is substantially similar to embodiment of the method, so description is fairly simple, it is related
Part is illustrated referring to the part of embodiment of the method.
Each embodiment in this specification is described by the way of progressive, what each embodiment was stressed be with
The difference of other embodiment, between each embodiment identical similar part mutually referring to.
It should be understood by those skilled in the art that, the embodiment of the embodiment of the present invention can be provided as method, device or calculate
Machine program product.Therefore, the embodiment of the present invention can using complete hardware embodiment, complete software embodiment or combine software and
The form of the embodiment of hardware aspect.And, the embodiment of the present invention can using wherein include computer at one or more can
With in the computer-usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) of program code
The form of the computer program product of implementation.
The embodiment of the present invention is with reference to method according to embodiments of the present invention, terminal device (system) and computer program
The flow chart and/or block diagram of product is described.It should be understood that flow chart and/or block diagram can be realized by computer program instructions
In each flow and/or flow and/or square frame in square frame and flow chart and/or block diagram combination.These can be provided
Computer program instructions set to all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing terminals
Standby processor is producing a machine so that held by the processor of computer or other programmable data processing terminal equipments
Capable instruction is produced for realizing in one flow of flow chart or multiple one square frame of flow and/or block diagram or multiple square frames
The device of the function of specifying.
These computer program instructions may be alternatively stored in can guide computer or other programmable data processing terminal equipments
In the computer-readable memory for working in a specific way so that instruction of the storage in the computer-readable memory produces bag
The manufacture of command device is included, the command device is realized in one flow of flow chart or multiple one side of flow and/or block diagram
The function of being specified in frame or multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing terminal equipments so that
Series of operation steps is performed on computer or other programmable terminal equipments to produce computer implemented treatment, so that
The instruction performed on computer or other programmable terminal equipments is provided for realizing in one flow of flow chart or multiple flows
And/or specified in one square frame of block diagram or multiple square frame function the step of.
Although having been described for the preferred embodiment of the embodiment of the present invention, those skilled in the art once know base
This creative concept, then can make other change and modification to these embodiments.So, appended claims are intended to be construed to
Including preferred embodiment and fall into having altered and changing for range of embodiment of the invention.
Finally, in addition it is also necessary to explanation, herein, such as first and second or the like relational terms be used merely to by
One entity or operation make a distinction with another entity or operation, and not necessarily require or imply these entities or operation
Between there is any this actual relation or order.And, term " including ", "comprising" or its any other variant meaning
Covering including for nonexcludability, so that process, method, article or terminal device including a series of key elements are not only wrapped
Those key elements, but also other key elements including being not expressly set out are included, or also includes being this process, method, article
Or the intrinsic key element of terminal device.In the absence of more restrictions, by wanting that sentence "including a ..." is limited
Element, it is not excluded that also there is other identical element in the process including the key element, method, article or terminal device.
Technical scheme provided by the present invention is described in detail above, specific case used herein is to this hair
Bright principle and implementation method is set forth, the explanation of above example be only intended to help understand the method for the present invention and its
Core concept；Simultaneously for those of ordinary skill in the art, according to thought of the invention, in specific embodiment and application
Be will change in scope, in sum, this specification content should not be construed as limiting the invention.
Claims (10)
1. a kind of risk of fraud recognition methods, it is characterised in that specifically include step：
Receive the apparatus characteristic information that mobile device is uploaded；
The fraud feature of the mobile device is determined according to the apparatus characteristic information；
The fraud feature is calculated using default equipment fraud characteristic model, obtains taking advantage of for the mobile device
Swindleness risk index.
2. risk of fraud recognition methods as claimed in claim 1, it is characterised in that the apparatus characteristic information includes substantially hard
It is part or all of in part information, the network information, running state information and application message.
3. risk of fraud recognition methods as claimed in claim 1, it is characterised in that the fraud feature row includes hardware
Information abnormity, agency are made using feature, feature of escaping from prison, brush machine feature, program debugging feature, simulator locating feature and plug-in instrument
With part or all of in feature.
4. risk of fraud recognition methods as claimed in claim 1, it is characterised in that the equipment fraud characteristic model is by such as
Lower step is obtained：
Default fraud Mathematical Modeling；
Obtain history fraud collection；
The fraud Mathematical Modeling is trained using the history fraud collection and the fraud characteristic behavior, obtains institute
State equipment fraud characteristic model.
5. a kind of risk of fraud prevention method, it is characterised in that including step：
When mobile device initiating business request, the apparatus characteristic information of the mobile device is obtained；
The apparatus characteristic information is processed according to the risk of fraud recognition methods as described in any one of Claims 1 to 4,
Obtain the risk of fraud index of the mobile device；
The service request is disposed according to the risk of fraud index and default risk control threshold value.
6. a kind of risk of fraud identifying system, it is characterised in that specifically include：
Characteristic information receiver module, the apparatus characteristic information for receiving mobile device upload；
Behavioural characteristic determining module, the fraud feature for determining the mobile device according to the apparatus characteristic information；
Risk index computing module, based on being carried out to the fraud feature using default equipment fraud characteristic model
Calculate, obtain the risk of fraud index of the mobile device.
7. risk of fraud identifying system as claimed in claim 6, it is characterised in that the apparatus characteristic information includes substantially hard
It is part or all of in part information, the network information, running state information and application message.
8. risk of fraud identifying system as claimed in claim 6, it is characterised in that the fraud feature row includes hardware
Information abnormity, agency are made using feature, feature of escaping from prison, brush machine feature, program debugging feature, simulator locating feature and plug-in instrument
With part or all of in feature.
9. risk of fraud identifying system as claimed in claim 6, it is characterised in that also including model training module, the mould
Type training module includes：
Mathematical Modeling preset unit, for presetting a fraud Mathematical Modeling；
Fraud acquiring unit, for obtaining history fraud collection；
Fraud model training unit, for utilizing the history fraud collection and the fraud characteristic behavior to the fraud number
Learn model to be trained, obtain the equipment fraud characteristic model.
10. a kind of risk of fraud crime prevention system, it is characterised in that including：
Characteristic information acquisition module, for when mobile device initiating business request, obtaining the equipment feature of the mobile device
Information；
Risk index determining module, for risk of fraud identifying system of the basis as described in any one of claim 6~9 to described
Apparatus characteristic information is processed, and obtains the risk of fraud index of the mobile device；
Risk control module, for being entered to the service request according to the risk of fraud index and default risk control threshold value
Row disposal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
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| CN107528838A (en) * | 2017-08-18 | 2017-12-29 | 上海二三四五金融科技有限公司 | A kind of antifraud control method based on mobile terminal features |
| CN108684044A (en) * | 2018-06-20 | 2018-10-19 | 中诚信征信有限公司 | A kind of user behavior detecting system, method and device |
| CN109657890A (en) * | 2018-09-14 | 2019-04-19 | 阿里巴巴集团控股有限公司 | A kind of risk for fraud of transferring accounts determines method and device |
| CN109670313A (en) * | 2017-10-16 | 2019-04-23 | 腾讯科技（深圳）有限公司 | The method, apparatus and readable storage medium storing program for executing of risk assessment are carried out in system operation |
| CN109785143A (en) * | 2018-12-27 | 2019-05-21 | 上海欣方智能***有限公司 | A kind of fraud prevention recognition methods and system |
| CN110264191A (en) * | 2019-05-17 | 2019-09-20 | 阿里巴巴集团控股有限公司 | A kind of Risk Identification Method and device of payment |
| CN110738396A (en) * | 2019-09-18 | 2020-01-31 | 阿里巴巴集团控股有限公司 | method, device and equipment for extracting characteristics of equipment |
| CN110941863A (en) * | 2019-11-13 | 2020-03-31 | 中信百信银行股份有限公司 | Equipment fingerprint generation method and device and terminal |
| CN111143665A (en) * | 2019-10-15 | 2020-05-12 | 支付宝(杭州)信息技术有限公司 | Fraud qualitative method, device and equipment |
| CN111275546A (en) * | 2020-02-24 | 2020-06-12 | 中国工商银行股份有限公司 | Financial client fraud risk identification method and device |
| CN112150261A (en) * | 2020-09-23 | 2020-12-29 | 上海维信荟智金融科技有限公司 | Financial anti-fraud method and system based on user communication behavior |
| CN112215622A (en) * | 2020-09-18 | 2021-01-12 | 南京欣网互联网络科技有限公司 | Risk prevention and control method and system based on order information |
| CN115392937A (en) * | 2022-10-25 | 2022-11-25 | 成都新希望金融信息有限公司 | User fraud risk identification method and device, electronic equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107528838A (en) * | 2017-08-18 | 2017-12-29 | 上海二三四五金融科技有限公司 | A kind of antifraud control method based on mobile terminal features |
| CN109670313A (en) * | 2017-10-16 | 2019-04-23 | 腾讯科技（深圳）有限公司 | The method, apparatus and readable storage medium storing program for executing of risk assessment are carried out in system operation |
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| CN108684044A (en) * | 2018-06-20 | 2018-10-19 | 中诚信征信有限公司 | A kind of user behavior detecting system, method and device |
| CN109657890A (en) * | 2018-09-14 | 2019-04-19 | 阿里巴巴集团控股有限公司 | A kind of risk for fraud of transferring accounts determines method and device |
| CN109785143A (en) * | 2018-12-27 | 2019-05-21 | 上海欣方智能***有限公司 | A kind of fraud prevention recognition methods and system |
| CN110264191A (en) * | 2019-05-17 | 2019-09-20 | 阿里巴巴集团控股有限公司 | A kind of Risk Identification Method and device of payment |
| CN110738396A (en) * | 2019-09-18 | 2020-01-31 | 阿里巴巴集团控股有限公司 | method, device and equipment for extracting characteristics of equipment |
| CN111143665A (en) * | 2019-10-15 | 2020-05-12 | 支付宝(杭州)信息技术有限公司 | Fraud qualitative method, device and equipment |
| CN111143665B (en) * | 2019-10-15 | 2023-07-14 | 支付宝(杭州)信息技术有限公司 | Qualitative method, device and equipment for fraud |
| CN110941863A (en) * | 2019-11-13 | 2020-03-31 | 中信百信银行股份有限公司 | Equipment fingerprint generation method and device and terminal |
| CN111275546A (en) * | 2020-02-24 | 2020-06-12 | 中国工商银行股份有限公司 | Financial client fraud risk identification method and device |
| CN111275546B (en) * | 2020-02-24 | 2023-08-18 | 中国工商银行股份有限公司 | Financial customer fraud risk identification method and device |
| CN112215622A (en) * | 2020-09-18 | 2021-01-12 | 南京欣网互联网络科技有限公司 | Risk prevention and control method and system based on order information |
| CN112150261A (en) * | 2020-09-23 | 2020-12-29 | 上海维信荟智金融科技有限公司 | Financial anti-fraud method and system based on user communication behavior |
| CN115392937A (en) * | 2022-10-25 | 2022-11-25 | 成都新希望金融信息有限公司 | User fraud risk identification method and device, electronic equipment and storage medium |
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