CN109214683A - A kind of Application of risk decision method and device - Google Patents
A kind of Application of risk decision method and device Download PDFInfo
- Publication number
- CN109214683A CN109214683A CN201811037817.0A CN201811037817A CN109214683A CN 109214683 A CN109214683 A CN 109214683A CN 201811037817 A CN201811037817 A CN 201811037817A CN 109214683 A CN109214683 A CN 109214683A
- Authority
- CN
- China
- Prior art keywords
- risk
- user
- related data
- parameter
- regulation engine
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
Abstract
The embodiment of the invention discloses a kind of Application of risk decision method and devices, and wherein Application of risk decision method includes: the electronic equipment for monitoring user, obtain the risk related data in the electronic equipment；Parameterized treatment is carried out to risk related data, obtains the standard parameter for being suitable for regulation engine；Standard parameter is imported into regulation engine, obtains risk rating；Decision in the face of risk is made according to risk rating.Using the present invention, the standardization to risk related data can be passed through, rules engines processes and risk rating, influence the generation of decision in the face of risk, the parameter and regulation engine of use improve the comprehensive and standardized degree of risk rating, and by risk rating, the accuracy of decision in the face of risk and the property of can refer to are improved.
Description
Technical field
The present invention relates to data processing fields, and in particular to a kind of Application of risk decision method and device.
Background technique
Risk control refers to that risk managers adopt various measures and method, eliminates or the various of event generation of reducing risks
Possibility or risk control person reduce risks event occur when caused by loss.In internet finance, it is related to much trading
Payment, loan, guarantee or other fund activities in order to identify the risk in funds transaction, and make risk control or anti-in advance
Fraud reply needs to carry out risk rating to user, and makes relevant risk decision.
Third-party decision in the face of risk service is the critical services of financial industry, can make fund loan or fund for enterprise
Decision references are provided when guarantee, it is most important to fund security.There is not localizable deployment in traditional decision in the face of risk service, can not
Depending on changing the problems such as report, air control process are without closed loop etc., it is often more important that, carry out the data sheet one of risk assessment, the risk obtained
Assessment result accuracy is low, and it is low to can refer to value.
Summary of the invention
The embodiment of the present invention provides a kind of Application of risk decision method and device, can pass through the standard to risk related data
Change, rules engines processes and risk rating influence the generation of decision in the face of risk, the parameter and regulation engine of use improve risk and comment
The comprehensive and standardized degree of grade, and by risk rating, improve the accuracy of decision in the face of risk and the property of can refer to.
The first aspect of the embodiment of the present invention provides a kind of Application of risk decision method, and the Application of risk decision method includes:
The electronic equipment for monitoring user, obtains the risk related data in the electronic equipment；
Parameterized treatment is carried out to the risk related data, obtains the standard parameter for being suitable for regulation engine, the rule
Then engine includes that the regular collection that numerical value constraint and/or conflict are examined is carried out to the standard parameter；
The standard parameter is imported into the regulation engine, obtains risk rating；
Decision in the face of risk is made according to the risk rating.
In an alternative scenario, the risk related data includes equipment-related data, described to obtain the electronic equipment
In risk related data include:
Obtain the hardware parameter of equipment, including equipment physical address or equipment unique sequence numbers；
Device network data are obtained, network name or IP address including equipment connection；
According to the hardware parameter and network data, the equipment-related data is determined.
In an alternative scenario, the risk related data includes user related data, described to obtain the electronic equipment
In risk related data include:
Obtain the account information of the user, including name on account or account interactive information；
The action message for obtaining the user, web page address, operation rule or consuming duration including user's browsing etc.；
According to the action message of the account information of the user and the user, the user related data is determined.
In an alternative scenario, described to carry out parameterized treatment to the risk related data, acquisition is drawn suitable for rule
The standard parameter held up, comprising:
According to the risk related data generating device fingerprint；
The device-fingerprint is matched with the standard fingerprint of the equipment, and according to matching result, obtains standard parameter,
Wherein, the device-fingerprint refers to parameter one, the device-fingerprint is obtained when the standard fingerprint successful match with the standard
Line obtains parameter two when it fails to match, the parameter one and the parameter two are all the standard parameter suitable for regulation engine.
In an alternative case, described that parameterized treatment is carried out to the risk related data, it obtains and is suitable for regulation engine
Standard parameter, comprising:
Obtain multiple characteristic values of different risk operations in the risk related data；
The user related data is clustered according to the multiple characteristic value, obtains multiple user's classification, wherein will
Characteristic value not comprising numerical value carries out keyword cluster, and the characteristic value comprising numerical value is carried out to the cluster of numberical range；
Classify for the multiple user and assign weight, obtain the multiple user classification and its corresponding weight, and by institute
Weight is stated as the standard parameter for being suitable for regulation engine.
In an alternative case, described that parameterized treatment is carried out to the risk related data, it obtains and is suitable for regulation engine
Standard parameter, comprising:
Customer relationship map is generated according to the equipment-related data and user related data；
The incidence coefficient that user is threatened in the user and relation map is obtained according to the customer relationship map；
Determine that the threat coefficient of the user, the threat coefficient are to be suitable for regulation engine according to the incidence coefficient
Standard parameter.
In an alternative case, described that the standard parameter is imported into the regulation engine, obtain risk rating, comprising:
One or more standard parameters of acquisition are imported into regulation engine, obtain rule scoring, the regulation engine includes
Weighting processing, binary conversion treatment or condition selection；
According to the rule scoring, risk rating is carried out for the user.
The second aspect of the embodiment of the present invention provides a kind of decision in the face of risk device, and the decision in the face of risk device includes:
Acquiring unit obtains the risk related data in the electronic equipment for monitoring the electronic equipment of user；
Standard processing unit obtains for carrying out parameterized treatment to the risk related data and is suitable for regulation engine
Standard parameter, the regulation engine include to the standard parameter carry out numerical value constraint and/or conflict examine regular collection；
Import unit obtains risk rating for the standard parameter to be imported the regulation engine；
Decision package, for making decision in the face of risk according to the risk rating.
In an alternative case, the risk related data includes equipment-related data, and the acquiring unit is specifically used for:
Obtain the hardware parameter of equipment, including equipment physical address or equipment unique sequence numbers；
Device network data are obtained, network name or internet protocol address including equipment connection；
According to the hardware parameter and network data, the equipment-related data is determined.
In an alternative case, the risk related data includes user related data, and the acquiring unit is specifically used for:
Obtain the account information of the user, including name on account or account interactive information；
The action message for obtaining the user, web page address, operation rule or consuming duration including user's browsing；
According to the action message of the account information of the user and the user, the user related data is determined.
In an alternative case, the standard processing unit is specifically used for:
According to the risk related data generating device fingerprint；
The device-fingerprint is matched with the standard fingerprint of the equipment, and according to matching result, obtains standard parameter,
Wherein, the device-fingerprint refers to parameter one, the device-fingerprint is obtained when the standard fingerprint successful match with the standard
Line obtains parameter two when it fails to match, the parameter one and the parameter two are all the standard parameter suitable for regulation engine.
In an alternative case, the standard processing unit is specifically used for:
Obtain multiple characteristic values of different risk operations in the risk related data；
The user related data is clustered according to the multiple characteristic value, obtains multiple user's classification, wherein will
Characteristic value not comprising numerical value carries out keyword cluster, and the characteristic value comprising numerical value is carried out to the cluster of numberical range；
Classify for the multiple user and assign weight, obtain the multiple user classification and its corresponding weight, and by institute
Weight is stated as the standard parameter for being suitable for regulation engine.
In an alternative case, the standard processing unit is specifically used for:
Customer relationship map is generated according to the equipment-related data and user related data；
The incidence coefficient that user is threatened in the user and relation map is obtained according to the customer relationship map；
Determine that the threat coefficient of the user, the threat coefficient are to be suitable for regulation engine according to the incidence coefficient
Standard parameter.
In an alternative case, the import unit is specifically used for:
One or more standard parameters of acquisition are imported into regulation engine, obtain rule scoring, the regulation engine includes
Weighting processing, binary conversion treatment or condition selection；
It is that the user carries out risk rating, regular higher, the risk rating of scoring according to the rule scoring
Higher grade.
The third aspect of the embodiment of the present invention provides a kind of electronic device, including processor, memory, communication interface, with
And one or more programs, one or more of programs are stored in the memory, and are configured by the processing
Device executes, and described program is included the steps that for executing the instruction in first aspect either method.
Fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, and storage is used for electronic data interchange
Computer program, wherein the computer program make computer execute first aspect either method described in step finger
It enables.
As it can be seen that Application of risk decision method described in the embodiment of the present application, monitors the electronic equipment of user first, institute is obtained
The risk related data in electronic equipment is stated, parameterized treatment then is carried out to risk related data, acquisition is drawn suitable for rule
The standard parameter held up；Standard parameter is imported into regulation engine again, obtains risk rating；Finally risk is made according to risk rating to determine
Plan.In this process, by the risk related data got, more fully consumer's risk can be investigated, enriched
The dimension of risk related data parameterized treatment after risk data is carried out parameterized treatment, imports regulation engine and simultaneously obtains
Risk rating, improves risk rating standardized degree, makes decision in the face of risk finally by risk rating, improves decision in the face of risk
Accuracy and the property of can refer to have very big reference value for the risk control in financial course.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is a kind of Application of risk decision method flow diagram provided in an embodiment of the present invention；
Fig. 2 is another Application of risk decision method flow diagram provided in an embodiment of the present invention；
Fig. 3 is the flow diagram of another Application of risk decision method provided in an embodiment of the present invention；
Fig. 4 is the flow diagram of another Application of risk decision method provided in an embodiment of the present invention；
Fig. 5 is a kind of structural schematic diagram of electronic device provided in an embodiment of the present invention；
Fig. 6 is a kind of structural block diagram of decision in the face of risk device provided in an embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Referenced herein " embodiment " is it is meant that a particular feature, structure, or characteristic described can wrap in conjunction with the embodiments
Containing at least one embodiment of the present invention.It is identical that each position in the description shows that the phrase might not be each meant
Embodiment, nor the independent or alternative embodiment with other embodiments mutual exclusion.Those skilled in the art explicitly and
Implicitly understand, embodiment described herein can be combined with other embodiments.
Electronic device involved by the embodiment of the present application may include the various handheld devices with wireless communication function,
Mobile unit, wearable device calculate equipment or are connected to other processing equipments and various forms of radio modem
User equipment (user equipment, UE), mobile station (mobile station, MS), terminal device (terminal
Device) etc..For convenience of description, apparatus mentioned above is referred to as electronic device.
It describes in detail below to the embodiment of the present invention.
Referring to Fig. 1, Fig. 1 is a kind of Application of risk decision method flow diagram in the embodiment of the present invention, as shown in Figure 1, institute
Stating Application of risk decision method includes:
101, the electronic equipment for monitoring user, obtains the risk related data in the electronic equipment.
Risk control refers to that risk managers adopt various measures and method, eliminates or the various of event generation of reducing risks
Possibility or risk control person reduce risks event occur when caused by loss.In internet finance, it is related to much trading
Payment, loan, guarantee or other fund activities in order to identify the risk in funds transaction, and make risk control or anti-in advance
Fraud reply needs to carry out risk rating to user, and makes relevant risk decision.Further, because the fund of user is living
Dynamic completed by terminal device, so the related data that terminal device can be obtained or be recorded all is risk related data,
Including device hardware data, equipment software data, related data and user account information and user when equipment connects network
Related data etc..Risk control platform can provide clothes by forms such as application program, browser, pop-up or webpages for user
Business, and by obtaining data with interacting for user, monitoring consumer electronic devices are completed, the purpose of risk related data is obtained.
Optionally, risk related data includes equipment-related data, obtains the risk related data in the electronic equipment
It include: to obtain the hardware parameter of equipment, including equipment physical address or equipment unique sequence numbers；Obtain device network data, packet
Include network name or the internet protocol address of equipment connection；According to hardware parameter and network data, equipment-related data is determined.
Specifically, equipment-related data is obtained, is that equipment itself has, it is not easy to the data of change.Such as equipment is hard
Title, model, shape, color, the function of part, physical address (MAC Address), central processing unit (CPU, Central
Processing Unit) model etc. or when equipment connection network get internet protocol address (IP Address), nothing
Gauze network (Wireless Fidelity, WIFI) title or global positioning system (Global Positioning System,
GPS) positioning etc..After getting equipment-related data, it can be found that whether the equipment of user is reequiped or common object
Reason address changed or WIFI title and the WIFI title of some risk subscribers it is mutually same, these parameters can be used
There is risk in the equipment for judging user.Bonding apparatus hardware parameter connects relevant parameter when network with equipment, that is, can determine
The relevant data of equipment.
Optionally, risk related data includes user related data, obtains the risk related data in the electronic equipment
It include: to obtain the account information of user, including name on account or account interactive information；The action message of acquisition user, including with
Web page address, operation rule or consuming duration of family browsing etc.；According to the action message of the account information of user and user, determine
User related data.
Specifically, user has relevant operation in using terminal equipment, and corresponding user related data records and divides
Analyse related data, it can be deduced that the degree of risk of user.Such as user is extremely short in each page residence time, the page and the page it
Between switching duration be less than 1s (second), this be obviously do not meet people operating habit and rule, it is more likely that be machine carry out
Brush single operation.Therefore it can judge that current device user belongs to risk subscribers according to the data.User related data can be divided into
Two classes, one kind is this kind of static information of account information of user, including user in the account of shopping website or social network sites, letter
Jie, buddy list, communication exchange object, communication exchange record or bank's card number, phone number or the user bound commonly use and answer
With the title of program, account etc., another kind of is this kind of multidate information of action message of user, web page address including browsing, clear
Looking at sequence, stay time, click frequency or click on content etc. can obtain in conjunction with the account information of user and the action message of user
To the activity related data of user.
102, parameterized treatment is carried out to the risk related data, obtains the standard parameter for being suitable for regulation engine, institute
Stating regulation engine includes that the regular collection that numerical value constraint and/or conflict are examined is carried out to the standard parameter.
Obtain a series of risk related datas take the form of it is diversified, such as acquisition device hardware name
Title, model, shape, color, function may be English character string, Chinese character string, Chinese and English symbol combination character string, number
Deng the action message of user, it may be possible to a number, a network address or a moment, then, it needs to join these data
Numberization processing, could import regulation engine and obtain risk rating.
Optionally, parameterized treatment is carried out to risk related data, obtains the standard parameter for being suitable for regulation engine, packet
It includes: according to the risk related data generating device fingerprint；The device-fingerprint is matched with the standard fingerprint of the equipment,
And according to matching result, standard parameter is obtained, wherein obtain parameter when the device-fingerprint and the standard fingerprint successful match
One, the device-fingerprint and the standard fingerprint obtain parameter two when it fails to match, and the parameter one and the parameter two are all
Standard parameter.
Specifically, since the relevant data of equipment are not easy change, it can be generated according to risk related data
Device-fingerprint is used to unique authentication equipment.Equipment-related data can be obtained according to prefixed time interval, within this time,
The variation of user equipment related data less, or comprising certain changing rule, after the equipment-related data and changing rule of acquisition,
Generating device fingerprint, as standard fingerprint.So, when judging for the safety of current device, current equipment is obtained
Related data, generating device fingerprint, and being matched with standard fingerprint, if cannot exactly match or matching degree is less than
Some preset threshold, then can determine that device-fingerprint, it fails to match, and setting current device fingerprint parameter two is 0, and otherwise, setting is worked as
Preceding device-fingerprint parameter one is 1.
Wherein, it for the generation of setting fingerprint, can be obtained according to the application program that device mac address and equipment are installed for a long time
, wherein MAC Address is made of 20 16 system characters, and the user that application program has identifies (User
Identification, UID), it is when application program is installed in electronic device, each application program is by one section of acquired word
Symbol.MAC Address head and the tail can be directly carried out with UID to connect, it is later half to be truncated into UID if first half is truncated into MAC Address, form one
Longer character string；Or the two is subjected to insertion connection, such as UID is inserted among MAC Address；Or the two is carried out
It is inserted into a UID character after interconnection, such as two bit mac addresses, is then inserted into two UID characters behind 3 bit mac addresses,
Until MAC Address and UID are thoroughly mixed, the character string of generation is as plaintext, and the insertion method of the two then generates a code key,
When the safety to current device determines, the device mac address and UID of acquisition need to generate newly bright according to code key
Text is that the plaintext of standard fingerprint compares.
As it can be seen that in embodiments of the present invention, it is related as risk to user related data by obtaining equipment-related data
Data, then according to risk related data generating device fingerprint, then by the device-fingerprint of generation therewith previous existence at standard fingerprint
It is matched, standard parameter is obtained according to matching result, this process effectively can be standardized place to equipment Risk data
Reason, so that the risk of the effective indicating equipment of standard parameter generated, improves the accuracy of risk judgment and can refer to value.
Optionally, parameterized treatment is carried out to risk related data, obtains the standard parameter for being suitable for regulation engine, packet
It includes: obtaining multiple characteristic values of different risk operations in risk related data；According to multiple characteristic values to user related data into
Row cluster, obtains multiple user's classification, wherein the characteristic value for not including numerical value is carried out keyword cluster, will include numerical value
The cluster of characteristic value progress numberical range；Classify for multiple users and assign weight, obtains multiple user's classification and its corresponding power
Value.
The type of user related data is very more, and the account information of user including being previously mentioned and the activity of user are believed
Breath, specific and web page address including name on account or account interactive information and user's browsing, operation rule or consuming duration
Deng, if to be clustered to user related data, first have to determine for cluster characteristic value, such as choose user browsing
Web page address, user's operation frequency and the page expend duration as characteristic value, classify to user.Then it is tied according to classification
Fruit assigns weight for different classes of user.This process is as shown in table 1:
User's classification chart that table 1 is obtained according to risk related data
As shown in Table 1, according to cluster condition by user's two classes of classification, one kind is risk subscribers class, another kind of for safety use
Family class, and different cluster conditions obtains different risk subscribers classes, assigns different weights for different risk subscribers classes, and
For all secured user's classes, 0 weight is all assigned.If the same user is divided into multiple risk subscribers classes simultaneously,
Then its weight is multiple risk subscribers class weights sums.
In addition, other than being clustered according to every a kind of data, all data can also be carried out unified poly- in cluster
Class obtains corresponding classification, and assigns different weights to be different classes of.
As it can be seen that in embodiments of the present invention, by according to the risk operations related data in consumer's risk data to user
Classify, then classify to different user and assign different weights, for risk related data parameterized treatment from
It is annotated in terms of family operation related data, enriches the dimension of risk related data parameterized treatment, improve risk judgment
Accuracy and can refer to value.
Optionally, parameterized treatment is carried out to risk related data, obtains the standard parameter for being suitable for regulation engine, packet
It includes: customer relationship map is generated according to equipment-related data and user related data；According to customer relationship map obtain user with
The incidence coefficient of user is threatened in relation map；The threat coefficient of user is determined according to incidence coefficient.
Relation map is the figure of relationship between description individual and individual.It can determine user equipment according to equipment-related data
IP address, wifi title etc. can determine account, telephone number, address list and the call of user according to user related data or chat
Its record etc., the data of each dimension can generate a customer relationship map.Such as address list relationship can form one
Oriented relation map includes the contact method of user B in the address list of user A, then there is the path from A to B.It can also basis
The data of all dimensions generate a common relation map, such as the wifi title of user C and user D is identical, and the two it
Between have message registration, then there are two paths between C and D.It threatens user to refer to unsafe user, may once initiate
Fraud, it is also possible to have non-honest record of refunding, user finally according to unknown subscriber and threatens the number of path between user to sentence
The threat coefficient of disconnected unknown subscriber, wherein the weight of each path may be the same or different, by between assessment user
Path significance level, different weights is set for daily path.Such as having message registration between two users, the path is important
Degree is high, and a biggish weight, such as 10 can be set, and the same webpage was browsed between two users, path weight
It wants degree low, a lesser weight, such as 0.5 can be set.
As it can be seen that in the embodiment of the present application, customer relationship map is generated by risk related data, then according to relational graph
In spectrum, active user and the incidence coefficient for threatening user determine the threat coefficient of active user, for the ginseng of risk related data
Numberization processing is annotated in terms of user social contact relevance, enriches the dimension of risk related data parameterized treatment, is promoted
The accuracy of risk judgment and it can refer to value.
103, the standard parameter is imported into the regulation engine, obtains risk rating.
Regulation engine is parsing, calls, the service of executing rule packet that regulation engine can receive data input, explains industry
Business rule, and operational decision making is made according to business rule, it include that numerical value constraint and/or punching are carried out to standard parameter in regulation engine
The prominent regular collection examined.The data have all been parameterized according to step 102, have been drawn then parameter is imported rule
It holds up, then can get final threat value, and risk rating is determined according to threat value.
Optionally, standard parameter is imported into regulation engine, obtains risk rating, comprising: mark the one or more of acquisition
Quasi- parameter imports regulation engine, obtains rule scoring, and regulation engine includes weighting processing, binary conversion treatment or condition selection；Root
It scores according to rule, carries out risk rating for user.
Regular collection comprising each rule-like composition in regulation engine, to carry out numerical value constraint to all kinds of parameters of acquisition
Or conflict is examined, and all parameters is enable to unify for risk rating.Assuming that the rule for including in regulation engine are as follows: to all ginsengs
Numerical value summation, if all parameter values and be less than or equal to 1, degree of risk is low, if more than 1 and less than 1.5, then degree of risk
In, if more than or be equal to 1.5, then degree of risk is high.The regulation engine is as shown in table 1:
2 regulation engine table of table
It so can get the risk rating of user according to the regulation engine.Such as the device-fingerprint parameter of known users S is
1, it is 0.5 that user, which clusters the parameter value obtained, and the threat coefficient that relation map obtains is 0.2, then, it is known that the rule of user S is commented
It is divided into 1+0.5+0.2=1.7 >=1.5, then, it is known that the risk rating of user S is " degree of risk is high ".
104, decision in the face of risk is made according to the risk rating.
Obtained risk rating according to step 103, then server to be made according to the risk rating of acquisition it is corresponding
Decision in the face of risk, such as when degree of risk is low, server can mark the user for concern user；If, can in degree of risk
Suitably to reduce the debt amount or payment amount of the user, and marking the user is potential risk user, can also be to the use
Family is further verified；If degree of risk is high, the loan application of the user can be refused, and marked the user as
Threaten user.
As it can be seen that monitoring the electronic equipment of user first in inventive embodiments, obtaining the risk phase in the electronic equipment
Data are closed, parameterized treatment then is carried out to risk related data, obtain the standard parameter for being suitable for regulation engine；Again by standard
Parameter imports regulation engine, obtains risk rating；Decision in the face of risk is finally made according to risk rating.In this process, pass through
The risk related data got, can more fully investigate consumer's risk, enrich risk related data parametrization
The dimension of processing after risk data is carried out parameterized treatment, imports regulation engine and obtains risk rating, improve risk and comment
Grade standardized degree, makes decision in the face of risk finally by risk rating, improves the accuracy of decision in the face of risk and the property of can refer to, for
Risk control in financial course has very big reference value.
Referring to Fig. 2, Fig. 2 is another Application of risk decision method flow diagram provided in an embodiment of the present invention, as schemed institute
Show, the Application of risk decision method in the present embodiment includes:
201, the hardware parameter of equipment, including equipment physical address or equipment unique sequence numbers are obtained；
202, device network data are obtained, network name or internet protocol address including equipment connection；
203, according to the hardware parameter and network data, the equipment-related data is determined, and the equipment is related
Data are as risk related data；
204, according to the risk related data generating device fingerprint；
205, the device-fingerprint is matched with the standard fingerprint of the equipment, and according to matching result, obtains standard
Parameter, wherein parameter one, the device-fingerprint and the mark are obtained when the device-fingerprint and the standard fingerprint successful match
Parameter two is obtained when quasi- fingerprint matching fails, the parameter one and the parameter two are all for suitable for the standard of regulation engine ginseng
Number；
206, the standard parameter is imported into the regulation engine, obtains risk rating；
207, decision in the face of risk is made according to the risk rating.
As it can be seen that in embodiments of the present invention, by obtaining equipment-related data as risk related data, then according to wind
Dangerous related data generating device fingerprint, and standard parameter is obtained according to the matching result of device-fingerprint, it completes to risk dependency number
According to parameterized treatment, make the standard parameter obtained in subsequent regulation engine, to obtain risk rating, finally according to risk
Grading carries out decision in the face of risk.This process enriches the dimension of risk related data parameterized treatment, improves risk rating rule
Model degree makes decision in the face of risk finally by risk rating, improves the accuracy of decision in the face of risk and the property of can refer to.
Referring to Fig. 3, Fig. 3 is the flow diagram of another Application of risk decision method provided in an embodiment of the present invention, such as scheme
Shown, the Application of risk decision method in the present embodiment includes:
301, the account information of user, including name on account or account interactive information are obtained；
302, the action message for obtaining user, web page address, operation rule or consuming duration including user's browsing；
303, according to the action message of the account information of the user and the user, the user related data is determined,
And using the user related data as risk related data；
304, multiple characteristic values of different risk operations in the risk related data are obtained；
305, the user related data is clustered according to the multiple characteristic value, obtains multiple user's classification,
In, the characteristic value for not including numerical value is subjected to keyword cluster, the characteristic value comprising numerical value is carried out to the cluster of numberical range；
306, classify for the multiple user and assign weight, obtain the multiple user's classification and its corresponding weight, and
Using the weight as the standard parameter for being suitable for regulation engine；
307, the standard parameter is imported into the regulation engine, obtains risk rating；
308, decision in the face of risk is made according to the risk rating.
As it can be seen that in the embodiment of the present application, by obtaining user related data as risk related data, then according to risk
Related data is clustered, and is obtained multiple user's classification, and assign different weights to multiple classification, is completed to risk dependency number
According to parameterized treatment, make the standard parameter obtained in subsequent regulation engine, to obtain risk rating, finally according to risk
Grading carries out decision in the face of risk.This process enriches the dimension of risk related data parameterized treatment, improves risk rating rule
Model degree makes decision in the face of risk finally by risk rating, improves the accuracy of decision in the face of risk and the property of can refer to.
Referring to Fig. 4, Fig. 4 is the flow diagram of another Application of risk decision method provided in an embodiment of the present invention, such as scheme
Shown, the Application of risk decision method in the present embodiment includes:
401, the electronic equipment for monitoring user, obtains the risk related data in the electronic equipment；
402, customer relationship map is generated according to the risk related data；
403, the incidence coefficient that user is threatened in the user and relation map is obtained according to the customer relationship map；
404, determine that the threat coefficient of the user, the threat coefficient are to be suitable for rule according to the incidence coefficient
The standard parameter of engine；
405, one or more standard parameters of acquisition are imported into regulation engine, obtains rule scoring, the regulation engine
It is selected including weighting processing, binary conversion treatment or condition；
It 406, is that the user carries out risk rating, regular higher, the risk that scores according to the rule scoring
The higher grade of grading；
407, decision in the face of risk is made according to the risk rating.
As it can be seen that in embodiments of the present invention, monitoring the electronic equipment of user, the risk obtained in the electronic equipment is related
Data, and customer relationship map is generated according to risk related data, the threat system of user is then obtained according to customer relationship map
Number completes the parameterized treatment to risk related data, is used for the standard parameter obtained in subsequent regulation engine, to obtain wind
Danger grading, finally carries out decision in the face of risk according to risk rating.This process enriches the dimension of risk related data parameterized treatment
Degree, improves risk rating standardized degree, makes decision in the face of risk finally by risk rating, improve the accuracy of decision in the face of risk
With the property of can refer to.
Fig. 5 is a kind of structural schematic diagram of electronic device provided in an embodiment of the present invention, as shown in figure 5, the electronic device
Including processor, memory, communication interface and one or more programs, wherein said one or multiple programs are stored in
In above-mentioned memory, and it is configured to be executed by above-mentioned processor, above procedure includes the instruction for executing following steps:
The electronic equipment for monitoring user, obtains the risk related data in the electronic equipment；
Parameterized treatment is carried out to the risk related data, obtains the standard parameter for being suitable for regulation engine, the rule
Then engine includes that the regular collection that numerical value constraint and/or conflict are examined is carried out to the standard parameter；
The standard parameter is imported into the regulation engine, obtains risk rating；
Decision in the face of risk is made according to the risk rating.
As can be seen that Application of risk decision method described in the embodiment of the present application, monitors the electronic equipment of user first, obtains
The risk related data in the electronic equipment is taken, parameterized treatment then is carried out to risk related data, obtains and is suitable for rule
The then standard parameter of engine；Standard parameter is imported into regulation engine again, obtains risk rating；Outlet air is finally done according to risk rating
Dangerous decision.In this process, by the risk related data got, more fully consumer's risk can be investigated,
The dimension for enriching risk related data parameterized treatment after risk data is carried out parameterized treatment, imports regulation engine simultaneously
Risk rating is obtained, risk rating standardized degree is improved, makes decision in the face of risk finally by risk rating, improve risk and determine
The accuracy of plan and the property of can refer to have very big reference value for the risk control in financial course.
In a possible example, the risk related data includes equipment-related data, obtains the electricity described
In terms of risk related data in sub- equipment, described program includes the instruction for executing following steps:
Obtain the hardware parameter of equipment, including equipment physical address or equipment unique sequence numbers；
Device network data are obtained, network name or internet protocol address including equipment connection；
According to the hardware parameter and network data, the equipment-related data is determined.
In a possible example, the risk related data includes user related data, obtains the electricity described
In terms of risk related data in sub- equipment, described program further includes the instruction for executing following steps:
Obtain the account information of the user, including name on account or account interactive information；
The action message for obtaining the user, web page address, operation rule or consuming duration including user's browsing；
According to the action message of the account information of the user and the user, the user related data is determined.
In a possible example, parameterized treatment is being carried out to the risk related data, is obtaining and is suitable for rule
In terms of the standard parameter of engine, described program includes the instruction for executing following steps:
According to the risk related data generating device fingerprint；
The device-fingerprint is matched with the standard fingerprint of the equipment, and according to matching result, obtains standard parameter,
Wherein, the device-fingerprint refers to parameter one, the device-fingerprint is obtained when the standard fingerprint successful match with the standard
Line obtains parameter two when it fails to match, the parameter one and the parameter two are all the standard parameter suitable for regulation engine.
In a possible example, parameterized treatment is being carried out to the risk related data, is obtaining and is suitable for rule
In terms of the standard parameter of engine, described program includes the instruction for executing following steps:
Obtain multiple characteristic values of different risk operations in the risk related data；
The user related data is clustered according to the multiple characteristic value, obtains multiple user's classification, wherein will
Characteristic value not comprising numerical value carries out keyword cluster, and the characteristic value comprising numerical value is carried out to the cluster of numberical range；
Classify for the multiple user and assign weight, obtain the multiple user classification and its corresponding weight, and by institute
Weight is stated as the standard parameter for being suitable for regulation engine.
In a possible example, parameterized treatment is being carried out to the risk related data, is obtaining and is suitable for rule
In terms of the standard parameter of engine, described program includes the instruction for executing following steps:
Customer relationship map is generated according to the risk related data；
The incidence coefficient that user is threatened in the user and relation map is obtained according to the customer relationship map；
Determine that the threat coefficient of the user, the threat coefficient are to be suitable for regulation engine according to the incidence coefficient
Standard parameter.
In a possible example, the standard parameter is being imported into the regulation engine, in terms of obtaining risk rating,
Described program includes the instruction for executing following steps:
One or more standard parameters of acquisition are imported into regulation engine, obtain rule scoring, the regulation engine includes
Weighting processing, binary conversion treatment or condition selection；
It is that the user carries out risk rating, regular higher, the risk rating of scoring according to the rule scoring
Higher grade.
Fig. 6 is the functional unit composition block diagram of decision in the face of risk device 600 involved in the embodiment of the present invention.The risk is determined
Plan device 600 is applied to electronic device, and the decision in the face of risk device includes:
Acquiring unit 601 obtains the risk related data in the electronic equipment for monitoring the electronic equipment of user；；
Standard processing unit 602, for carrying out parameterized treatment to the risk related data, acquisition is drawn suitable for rule
The standard parameter held up, the regulation engine include that the rule set that numerical value constraint and/or conflict are examined is carried out to the standard parameter
It closes；
Import unit 603 obtains risk rating for the standard parameter to be imported the regulation engine；
Decision package 604, for making decision in the face of risk according to the risk rating.
As can be seen that in embodiments of the present invention, electronic device monitors the electronic equipment of user first, obtains the electronics
Then risk related data in equipment carries out parameterized treatment to risk related data, obtain the mark for being suitable for regulation engine
Quasi- parameter；Standard parameter is imported into regulation engine again, obtains risk rating；Decision in the face of risk is finally made according to risk rating.?
During this, by the risk related data got, more fully consumer's risk can be investigated, enrich risk
The dimension of related data parameterized treatment after risk data is carried out parameterized treatment, imports regulation engine and obtains risk and comment
Grade, improves risk rating standardized degree, makes decision in the face of risk finally by risk rating, improve the accuracy of decision in the face of risk
With the property of can refer to, there is very big reference value for the risk control in financial course.
In an alternative case, the risk related data includes equipment-related data, and the acquiring unit 601 is specifically used
In:
Obtain the hardware parameter of equipment, including equipment physical address or equipment unique sequence numbers；
Device network data are obtained, network name or internet protocol address including equipment connection；
According to the hardware parameter and network data, the equipment-related data is determined.
In an alternative case, the risk related data includes user related data, and the acquiring unit 601 is specifically used
In:
Obtain the account information of the user, including name on account or account interactive information；
The action message for obtaining the user, web page address, operation rule or consuming duration including user's browsing；
According to the action message of the account information of the user and the user, the user related data is determined.
In an alternative case, the standard processing unit 602 is specifically used for:
According to the risk related data generating device fingerprint；
The device-fingerprint is matched with the standard fingerprint of the equipment, and according to matching result, obtains standard parameter,
Wherein, the device-fingerprint refers to parameter one, the device-fingerprint is obtained when the standard fingerprint successful match with the standard
Line obtains parameter two when it fails to match, the parameter one and the parameter two are all the standard parameter suitable for regulation engine.
In an alternative case, the standard processing unit 602 is specifically used for:
Obtain multiple characteristic values of different risk operations in the risk related data；
The user related data is clustered according to the multiple characteristic value, obtains multiple user's classification, wherein will
Characteristic value not comprising numerical value carries out keyword cluster, and the characteristic value comprising numerical value is carried out to the cluster of numberical range；
Classify for the multiple user and assign weight, obtain the multiple user classification and its corresponding weight, and by institute
Weight is stated as the standard parameter for being suitable for regulation engine.
In an alternative case, the standard processing unit 602 is specifically used for:
Customer relationship map is generated according to the equipment-related data and user related data；
The incidence coefficient that user is threatened in the user and relation map is obtained according to the customer relationship map；
Determine that the threat coefficient of the user, the threat coefficient are to be suitable for regulation engine according to the incidence coefficient
Standard parameter.
In an alternative case, the import unit 603 is specifically used for:
One or more standard parameters of acquisition are imported into regulation engine, obtain rule scoring, the regulation engine includes
Weighting processing, binary conversion treatment or condition selection；
It is that the user carries out risk rating, regular higher, the risk rating of scoring according to the rule scoring
Higher grade.
The embodiment of the present invention also provides a kind of computer storage medium, wherein computer storage medium storage is for electricity
The computer program of subdata exchange, the computer program make computer execute any as recorded in above method embodiment
Some or all of method step, above-mentioned computer include mobile terminal.
The embodiment of the present invention also provides a kind of computer program product, and above-mentioned computer program product includes storing calculating
The non-transient computer readable storage medium of machine program, above-mentioned computer program are operable to that computer is made to execute such as above-mentioned side
Some or all of either record method step in method embodiment.The computer program product can be a software installation
Packet, above-mentioned computer includes mobile terminal.
In several embodiments provided herein, it should be understood that disclosed device, it can be by another way
It realizes.For example, the apparatus embodiments described above are merely exemplary, such as the division of said units, it is only a kind of
Logical function partition, there may be another division manner in actual implementation, such as multiple units or components can combine or can
To be integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Coupling, direct-coupling or communication connection can be through some interfaces, the indirect coupling or communication connection of device or unit,
It can be electrical or other forms.
Above-mentioned unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, each functional unit in each embodiment of the application can integrate in one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If above-mentioned integrated unit is realized in the form of SFU software functional unit and when sold or used as an independent product,
It can store in a computer-readable access to memory.Based on this understanding, the technical solution of the application substantially or
Say that all or part of the part that contributes to existing technology or the technical solution can embody in the form of software products
Out, which is stored in a memory, including some instructions are used so that a computer equipment (can
For personal computer, server or network equipment etc.) execute all or part of step of each embodiment above method of the application
Suddenly.And memory above-mentioned includes: USB flash disk, read-only memory (Read-Only Memory, ROM), random access memory
The various media that can store program code such as (Random Access Memory, RAM), mobile hard disk, magnetic or disk.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of above-described embodiment is can
It is completed with instructing relevant hardware by program, which can store in a computer-readable memory, memory
It may include: flash disk, ROM, RAM, disk or CD etc..
The embodiment of the present invention has been described in detail above, specific case used herein to the principle of the application and
Embodiment is expounded, the description of the example is only used to help understand the method for the present application and its core ideas；
At the same time, for those skilled in the art can in specific embodiments and applications according to the thought of the application
There is change place, in conclusion the contents of this specification should not be construed as limiting the present application.
Claims (10)
1. a kind of Application of risk decision method, which is characterized in that the described method includes:
The electronic equipment for monitoring user, obtains the risk related data in the electronic equipment；
Parameterized treatment is carried out to the risk related data, obtains the standard parameter for being suitable for regulation engine, the rule is drawn
It holds up including carrying out the regular collection that numerical value constraint and/or conflict are examined to the standard parameter；
The standard parameter is imported into the regulation engine, obtains risk rating；
Decision in the face of risk is made according to the risk rating.
2. the method according to claim 1, wherein the risk related data includes equipment-related data, institute
Stating the risk related data obtained in the electronic equipment includes:
Obtain the hardware parameter of equipment, including equipment physical address or equipment unique sequence numbers；
Device network data are obtained, network name or internet protocol address including equipment connection；
According to the hardware parameter and network data, the equipment-related data is determined.
3. method according to claim 1 or 2, which is characterized in that the risk related data includes user related data,
The risk related data obtained in the electronic equipment includes:
Obtain the account information of the user, including name on account or account interactive information；
The action message for obtaining the user, web page address, operation rule or consuming duration including user's browsing；
According to the action message of the account information of the user and the user, the user related data is determined.
4. according to the method described in claim 3, it is characterized in that, described carry out at parametrization the risk related data
Reason obtains the standard parameter for being suitable for regulation engine, comprising:
According to the risk related data generating device fingerprint；
The device-fingerprint is matched with the standard fingerprint of the equipment, and according to matching result, obtains standard parameter,
In, the device-fingerprint and acquisition parameter one, the device-fingerprint and the standard fingerprint when standard fingerprint successful match
Parameter two is obtained when it fails to match, the parameter one and the parameter two are all the standard parameter suitable for regulation engine.
5. according to the method described in claim 4, it is characterized in that, described carry out at parametrization the risk related data
Reason obtains the standard parameter for being suitable for regulation engine, comprising:
Obtain multiple characteristic values of different risk operations in the risk related data；
The user related data is clustered according to the multiple characteristic value, obtains multiple user's classification, wherein will not wrap
Characteristic value containing numerical value carries out keyword cluster, and the characteristic value comprising numerical value is carried out to the cluster of numberical range；
Classify for the multiple user and assign weight, obtain the multiple user classification and its corresponding weight, and by the power
It is worth as the standard parameter for being suitable for regulation engine.
6. according to the method described in claim 5, it is characterized in that, described carry out at parametrization the risk related data
Reason obtains the standard parameter for being suitable for regulation engine, comprising:
Customer relationship map is generated according to the risk related data；
The incidence coefficient that user is threatened in the user and relation map is obtained according to the customer relationship map；
The threat coefficient of the user, the mark for threatening coefficient to be as suitable for regulation engine are determined according to the incidence coefficient
Quasi- parameter.
7. method described in -6 according to claim 1, which is characterized in that described to draw the standard parameter importing rule
It holds up, obtains risk rating, comprising:
One or more standard parameters of acquisition are imported into regulation engine, obtain rule scoring, the regulation engine includes weighting
Processing, binary conversion treatment or condition selection；
It is that the user carries out risk rating according to the rule scoring, the rule scoring is higher, the risk rating etc.
Grade is higher.
8. a kind of decision in the face of risk device, which is characterized in that the decision in the face of risk device includes:
Acquiring unit obtains the risk related data in the electronic equipment for monitoring the electronic equipment of user；
Standard processing unit obtains the mark for being suitable for regulation engine for carrying out parameterized treatment to the risk related data
Quasi- parameter；
Import unit obtains risk rating for the standard parameter to be imported the regulation engine；
Decision package, for making decision in the face of risk according to the risk rating.
9. a kind of electronic device, including processor, memory, communication interface, and one or more programs, one or more
A program is stored in the memory, and is configured to be executed by the processor, and described program includes being used for right of execution
Benefit requires the instruction of the step in 1-7 any means.
10. a kind of computer readable storage medium, storage is used for the computer program of electronic data interchange, wherein the calculating
Machine program makes the instruction of step described in any one of computer perform claim requirement 1-7.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811037817.0A CN109214683A (en) | 2018-09-06 | 2018-09-06 | A kind of Application of risk decision method and device |
| PCT/CN2018/123887 WO2020048056A1 (en) | 2018-09-06 | 2018-12-26 | Risk decision method and apparatus |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811037817.0A CN109214683A (en) | 2018-09-06 | 2018-09-06 | A kind of Application of risk decision method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109214683A true CN109214683A (en) | 2019-01-15 |
Family
ID=64987206
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811037817.0A Pending CN109214683A (en) | 2018-09-06 | 2018-09-06 | A kind of Application of risk decision method and device |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN109214683A (en) |
| WO (1) | WO2020048056A1 (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111104664A (en) * | 2019-11-29 | 2020-05-05 | 北京云测信息技术有限公司 | Risk identification method of electronic equipment and server |
| CN111641594A (en) * | 2020-05-09 | 2020-09-08 | 同济大学 | Method, system, medium and device for detecting fraudulent user based on page behavior |
| CN111724069A (en) * | 2020-06-22 | 2020-09-29 | 百度在线网络技术（北京）有限公司 | Method, apparatus, device and storage medium for processing data |
| CN112508677A (en) * | 2020-11-06 | 2021-03-16 | 无锡艺界科技有限公司 | Financial system based on big data wind accuse |
| CN113505823A (en) * | 2021-07-02 | 2021-10-15 | 中国联合网络通信集团有限公司 | Supply chain security analysis method and computer-readable storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090089869A1 (en) * | 2006-04-28 | 2009-04-02 | Oracle International Corporation | Techniques for fraud monitoring and detection using application fingerprinting |
| CN107067157A (en) * | 2017-03-01 | 2017-08-18 | 北京奇艺世纪科技有限公司 | Business risk appraisal procedure, device and air control system |
| CN108038700A (en) * | 2017-12-22 | 2018-05-15 | 上海前隆信息科技有限公司 | A kind of anti-fraud data analysing method and system |
| CN108492173A (en) * | 2018-03-23 | 2018-09-04 | 上海氪信信息技术有限公司 | A kind of anti-Fraud Prediction method of credit card based on dual-mode network figure mining algorithm |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040267660A1 (en) * | 2003-02-21 | 2004-12-30 | Automated Financial Systems, Inc. | Risk management system |
| CN101930585A (en) * | 2010-09-01 | 2010-12-29 | 中国建设银行股份有限公司 | Credit business risk monitoring system and method thereof |
| CN104392391A (en) * | 2014-11-14 | 2015-03-04 | 国家电网公司 | Power grid running safety risk quantification method |
| CN107025509B (en) * | 2016-02-01 | 2021-06-18 | 腾讯科技（深圳）有限公司 | Decision making system and method based on business model |
-
2018
- 2018-09-06 CN CN201811037817.0A patent/CN109214683A/en active Pending
- 2018-12-26 WO PCT/CN2018/123887 patent/WO2020048056A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090089869A1 (en) * | 2006-04-28 | 2009-04-02 | Oracle International Corporation | Techniques for fraud monitoring and detection using application fingerprinting |
| CN107067157A (en) * | 2017-03-01 | 2017-08-18 | 北京奇艺世纪科技有限公司 | Business risk appraisal procedure, device and air control system |
| CN108038700A (en) * | 2017-12-22 | 2018-05-15 | 上海前隆信息科技有限公司 | A kind of anti-fraud data analysing method and system |
| CN108492173A (en) * | 2018-03-23 | 2018-09-04 | 上海氪信信息技术有限公司 | A kind of anti-Fraud Prediction method of credit card based on dual-mode network figure mining algorithm |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111104664A (en) * | 2019-11-29 | 2020-05-05 | 北京云测信息技术有限公司 | Risk identification method of electronic equipment and server |
| CN111641594A (en) * | 2020-05-09 | 2020-09-08 | 同济大学 | Method, system, medium and device for detecting fraudulent user based on page behavior |
| CN111641594B (en) * | 2020-05-09 | 2021-11-30 | 同济大学 | Method, system, medium and device for detecting fraudulent user based on page behavior |
| CN111724069A (en) * | 2020-06-22 | 2020-09-29 | 百度在线网络技术（北京）有限公司 | Method, apparatus, device and storage medium for processing data |
| CN112508677A (en) * | 2020-11-06 | 2021-03-16 | 无锡艺界科技有限公司 | Financial system based on big data wind accuse |
| CN113505823A (en) * | 2021-07-02 | 2021-10-15 | 中国联合网络通信集团有限公司 | Supply chain security analysis method and computer-readable storage medium |
| CN113505823B (en) * | 2021-07-02 | 2023-06-23 | 中国联合网络通信集团有限公司 | Supply chain security analysis method and computer readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2020048056A1 (en) | 2020-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109214683A (en) | A kind of Application of risk decision method and device | |
| CN106453061B (en) | A kind of method and system identifying network fraudulent act | |
| CN107688667A (en) | Intelligent robot client service method, electronic installation and computer-readable recording medium | |
| CN106713579B (en) | Telephone number identification method and device | |
| CN106874253A (en) | Recognize the method and device of sensitive information | |
| CN106469196A (en) | Data processing method and its device, method of insuring and its system of insuring | |
| CN106201890B (en) | The performance optimization method and server of a kind of application | |
| CN107656918B (en) | Obtain the method and device of target user | |
| CN108255936A (en) | A kind of edit methods of webpage, system and editing machine | |
| CN109582844A (en) | A kind of method, apparatus and system identifying crawler | |
| CN109815377A (en) | Method for building up, device, computer equipment and the storage medium of label | |
| CN112765364A (en) | Group chat session ordering method and device, storage medium and electronic equipment | |
| CN106992975A (en) | The recognition methods of malice network address and device | |
| CN106571933A (en) | Service processing method and device | |
| CN106856474A (en) | A kind of processing method and processing device of checking information | |
| CN108182180B (en) | Method and apparatus for generating information | |
| CN106372992A (en) | Access control method and access control device | |
| CN103780590B (en) | Automatically prompting user the registration method of microblogging, Apparatus and system | |
| CN108076032A (en) | A kind of abnormal behaviour user identification method and device | |
| CN106998386B (en) | A kind of method and device thereof of newly-increased contact method, user terminal | |
| CN109560937A (en) | Command identifying method, device and computer readable storage medium | |
| CN110213281A (en) | Safety protecting method and device | |
| CN112688939B (en) | Method and device for determining illegal organization information, electronic equipment and storage medium | |
| CN109376287A (en) | House property map construction method, device, computer equipment and storage medium | |
| CN109981712A (en) | Method and apparatus for pushed information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |