CN107067157A - Business risk appraisal procedure, device and air control system - Google Patents
Business risk appraisal procedure, device and air control system Download PDFInfo
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- CN107067157A CN107067157A CN201710117674.3A CN201710117674A CN107067157A CN 107067157 A CN107067157 A CN 107067157A CN 201710117674 A CN201710117674 A CN 201710117674A CN 107067157 A CN107067157 A CN 107067157A
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- 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
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- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
Abstract
The invention provides a kind of business risk appraisal procedure, device and air control system, method therein includes：Business datum to be assessed is received, and according to preset risk rule engine, identifies the risk behavior regular collection of business datum matching；To many rules in the regular collection, according to the risk evaluation model pre-established, each regular corresponding risk score value is assessed；The corresponding risk score value of many rules is added up, and will it is cumulative after the risk total score threshold value of each risk class of the risk score value summation with pre-setting be compared, determine the risk class of business datum.The present invention can improve the generalization ability and treatment effeciency of risk system.
Description
Technical field
The present invention relates to Internet technical field, more particularly to a kind of business risk appraisal procedure, device and air control system
System.
Background technology
Air control system is service security risk control system, it is intended to ensure the operation of the normal safety of each business.Referring to figure
1, it is a kind of typical risk system configuration diagram.The course of work of air control system is：Operation system is by servicing access mould
Block transmits user access activity data to regulation engine, and regulation engine depends on secure data warehouse and model strategy,
Wherein, secure data warehouse refers to social worker storehouse (social engineering database), the i.e. information of malicious user, comprising cell-phone number, IP,
User name etc.；Model strategy mainly include rule and policy that data analyst made by methods such as data minings there is provided
Intercepted to regulation engine.It can be seen that, when the regulation engine of air control system receives the incoming access data of business, by using
Whether the rule of certain behavioral data matching at family is risky and intercepted.As long as rule match here refers to hit one
The rule of predefined, just stops the follow-up rule set of matching.
Existing air control system the rule that manually sets to carry out abnormal behaviour interception by way of " hit exit ", this
At least there are following two problems in the mode of kind.
(1) generalization ability is poor
The regular hold-up interception method of " hit is exited " is difficult to the Rule Information for making full use of abnormal behaviour to trigger other classifications,
So that the generalization ability (Generalization Ability, to the adaptability of fresh sample) of air control system is poor.For example, existing
There is mode to access behavior successively traversal rule set, as long as a hit wherein rule, that is, it is malice to think the access behavior
, and do not continue to match follow-up regular collection.Therefore, for a malicious access, unique rule of its hit can only be obtained
Then, but in fact, a malicious access can hit many rules simultaneously, thus cause to be difficult to combine many rules and carry out while sentencing
Disconnected situation.
(2) efficiency is low
Due to needing the artificial priority set per rule, take time and effort.Because the degree of risk between different rules
It is different, it is therefore desirable to which rule set is ranked up according to its degree of risk, it is desirable to which the larger rule of risk can be ordered in advance
In, but set the degree of risk of Different Rule to need artificial experience, when rule set is larger, the degree of risk per rule is set
It is complex.
The content of the invention
In order to improve the generalization ability and treatment effeciency of air control system, the embodiment of the present invention provides a kind of business risk and assessed
Method, device and air control system.
According to an aspect of the present invention there is provided a kind of business risk appraisal procedure, including：Receive business number to be assessed
According to, and according to preset risk rule engine, identify the risk behavior regular collection of business datum matching；To the rule set
Many rules in conjunction, according to the risk evaluation model pre-established, assess each regular corresponding risk score value；By many rules and regulations
Then corresponding risk score value is added up, and will it is cumulative after risk score value summation and each risk class pre-set wind
Dangerous total score threshold value is compared, and determines the risk class of business datum.
It is preferred that, in addition to：The risk evaluation model is set up, including：Obtain sample data；To the sample data of acquisition
It is trained, obtains each regular Model Weight；Each regular Model Weight is converted into by score value by Linear Mapping；Root
The risk of frequency is triggered according to described each regular sub-rule, the score value for each sub-rule that adds up successively obtains regular point
Value；And, the corresponding risk total score threshold value of the different risk class of setting.
It is preferred that, the sample data to acquisition carries out logistic regression training, obtains each regular Model Weight.
It is preferred that, it is described according to preset risk rule engine, the regular collection of business datum matching is identified, including：
The risk rule engine, based on the malicious user accounts information or operation behavior information in secure data warehouse, matches industry
Corresponding each risk behavior rule of data of being engaged in constitutes the regular collection.
It is preferred that, the business datum includes：Business datum, registering service data, authentication services data are registered, and/or,
The anti-brush business datum of activity；The risk behavior rule refers to what is generated based on malicious user accounts information or operation behavior information
Risk behavior rule.
According to an aspect of the present invention there is provided a kind of business risk apparatus for evaluating, including：Business data processing unit,
For receiving business datum to be assessed, and according to preset risk rule engine, identify the regular collection of business datum matching；
Risk score value assessment unit, for many rules in the regular collection, according to the risk evaluation model pre-established, commenting
Estimate each regular corresponding risk score value；Risk class determining unit, for the corresponding risk score value of many rules to be tired out
Plus, and will it is cumulative after the risk total score threshold value of each risk class of the risk score value summation with pre-setting be compared, really
Make the risk class of business datum.
It is preferred that, in addition to：Risk evaluation model sets up unit, for setting up the risk evaluation model；The risk
Assessment models set up unit specifically for obtaining sample data；Sample data to acquisition is trained, and obtains each rule
Model Weight；Each regular Model Weight is converted into by score value by Linear Mapping；According to described each regular sub-rule
The risk of frequency is triggered, the score value for each sub-rule that adds up successively obtains the regular score value；And, different risks etc. are set
The corresponding risk total score threshold value of level.
It is preferred that, the risk evaluation model sets up unit specifically for the sample data to acquisition carries out logistic
Regression training, obtains each regular Model Weight.
It is preferred that, the business data processing unit specifically for：Using the risk rule engine, based on secure data
Malicious user accounts information or operation behavior information in warehouse, match the regular structure of each corresponding risk behavior of business datum
Into the regular collection.
It is preferred that, the business datum includes：Business datum, registering service data, authentication services data are registered, and/or,
The anti-brush business datum of activity；The risk behavior rule refers to what is generated based on malicious user accounts information or operation behavior information
Risk behavior rule.
According to a further aspect of the invention there is provided a kind of air control system, including business processing device, service access dress
Put, risk rule engine, secure data warehouse, intercept process device, the system also include risk assessment device, wherein：Institute
Business processing device is stated, business datum is linked into risk rule engine by the service access model；The risk rule
Engine, malicious user accounts information or operation behavior information in secure data warehouse, matches business datum corresponding
Each risk behavior rule constitutes risk rule set；The risk assessment device, for a plurality of in the regular collection
Rule, according to the risk evaluation model pre-established, assesses each regular corresponding risk score value, and many rules are corresponding
Risk score value is added up, and will it is cumulative after risk score value summation and each risk class pre-set risk total score threshold
Value is compared, and determines the risk class of business datum；The intercept process device, for risk according to business datum etc.
Level, based on preset interception strategy, is intercepted to business datum.
It is preferred that, the risk assessment device is additionally operable to set up risk evaluation model, specifically, obtaining sample data；It is right
The sample data of acquisition is trained, and obtains each regular Model Weight；Each regular model is weighed by Linear Mapping
Score value is converted into again；The risk of frequency is triggered according to described each regular sub-rule, the score value for each sub-rule that adds up successively
Obtain the regular score value；And, the corresponding risk total score threshold value of the different risk class of setting.
It is preferred that, the business datum includes：Business datum, registering service data, authentication services data are registered, and/or,
The anti-brush business datum of activity；The risk behavior rule refers to what is generated based on malicious user accounts information or operation behavior information
Risk behavior rule.
It can be seen that, in the business risk control method that the present invention is provided, no longer only rely upon the wall scroll that abnormal behaviour is triggered
Rule, but the strictly all rules triggered by the abnormal behaviour, in the way of the regular score value of various dimensions is cumulative carrying out risk sentences
It is disconnected；Moreover, without manually setting the priority per rule, but by training the data of existing air control system to obtain model,
Then according to the risk class of sub-rule, transformation model weight is regular score value in the form of weight is cumulative, and then reaches automatic
Regular score value is set then to export the purpose of risk class.The regular air control mode of wall scroll is only relied on relative to prior art, this
Invention improves the generalization ability of air control system, first for mode of the prior art by artificial setting rule prioritization, this hair
It is bright to improve treatment effeciency.
Brief description of the drawings
Fig. 1 is a kind of air control system structure diagram provided in an embodiment of the present invention
Fig. 2 is a kind of business risk appraisal procedure flow chart provided in an embodiment of the present invention；
Fig. 3 is a kind of business risk appraisal procedure example principles schematic diagram provided in an embodiment of the present invention；
Fig. 4 is a kind of business risk apparatus for evaluating structural representation provided in an embodiment of the present invention；
Fig. 5 is a kind of air control system structure diagram provided in an embodiment of the present invention.
Embodiment
In order to facilitate the understanding of the purposes, features and advantages of the present invention, it is below in conjunction with the accompanying drawings and specific real
Applying mode, the present invention is further detailed explanation.
The strictly all rules information that the embodiment of the present invention is difficult to make full use of triggering for existing air control system, and manually set
Put rule prioritization to take time and effort, propose a kind of business risk appraisal procedure added up based on weight.For example, this method is led to first
The data that the existing air control system of logistic regression Algorithm for Training is obtained are crossed, Model Weight are obtained, then according to every sub-rule
Risk class, Model Weight is converted into sub-rule score value in the form of weight is cumulative, i.e., by the regular low fraction of same type
Value is added to high-grade, to ensure that the high-grade score value of same type rule is more than inferior grade, and then reaches and automatic sets rule point
The purpose of value.
It is a kind of business risk appraisal procedure flow chart provided in an embodiment of the present invention referring to Fig. 2, this method includes：
S201：Business datum to be assessed is received, and according to preset risk rule engine, identifies business datum matching
Risk behavior regular collection.
Wherein, business datum includes but is not limited to registration business datum, registering service data, authentication services data, and/
Or, movable anti-brush business datum, etc..
Being introduced as before, risk rule engine is generally comprised in risk system, in this step, it is possible to use risk rule is drawn
Hold up, based on the malicious user information in secure data warehouse, match corresponding each risk behavior rule of business datum and constitute
Regular collection.Wherein, account information includes but is not limited to cell-phone number, IP, user name；Operation behavior information includes but is not limited to frequency
It is numerous to log in ,/access, bad password is repeatedly logged in/and access, etc. for example, being frequently logged on using same IP address.
It can be seen that, risk behavior rule refers to the risk behavior based on malicious user accounts information or the generation of operation behavior information
Rule, for example, risk behavior rule includes but is not limited to：Malicious user login/access, same address are frequently logged on/is accessed, mistake
Password is frequently logged on/accessed, etc. by mistake.
S202：To many rules in regular collection, according to the risk evaluation model pre-established, each rule is assessed right
The risk score value answered.
It is preferred that, the above method also includes：The step of setting up the risk evaluation model.Specifically, setting up the risk
The process of assessment models includes：Obtain sample data；Sample data to acquisition is trained, and obtains each regular model power
Weight；Each regular Model Weight is converted into by score value by Linear Mapping；Frequency is triggered according to each sub-rule of a rule
The risk of rate, the score value for each sub-rule that adds up successively obtains the regular score value；And, set different risk class corresponding
Risk total score threshold value.
It is preferred that, sample data is trained using logistic regression algorithm.Logistic regression essence is a kind of
Sorting algorithm, has used a sigmod function, and the linear weighted function result of feature is mapped between 0 to 1, and this just can be with
Regard that data sample point belongs to the probability of a certain class as.If result is closer to 0 or 1, illustrate that the confidence level of classification results is got over
It is high.
S203：The corresponding risk score value of many rules is added up, and will it is cumulative after risk score value summation with advance
The risk total score threshold value of each risk class set is compared, and determines the risk class of business datum.
In order to understand that conveniently, a simple case of such scheme is：First, business datum to be assessed matches 3 rules and regulations
Then：Rule1, rule2, rule3 (S201), then, per the corresponding risk score value of rule be respectively score1, score2,
Score3 (S202), finally, the corresponding risk score value of this three rule is added and obtains sum_score (sum_score=
Score1+score2+score3), then by sum_score it is compared with risk class total score threshold value set in advance
(S203), for example, it is assumed that there is tri- risk class of levle1, level2, level3, and these three risk class are corresponded to respectively
Different risk total score threshold values (generally, risk class is higher, and total score threshold value is higher), by sum_score and each etc.
The total score threshold value of level compares, and determines which grade is business datum belong to.
The embodiment of the present invention is illustrated with a concrete instance below.
The business such as registration, login, authentication, the anti-brush of activity that the example can apply in video website, for example, log in industry
Business, malicious user may use the username and password leaked on internet, carry out violence login, then can be according to the malice
The IP of user, User_agent, device_id, visitation frequency, trial user name password number, determine that it is triggered all
Regular collection, then by the method for the embodiment of the present invention, determines the risk class that malicious user is accessed, to be intercepted.
It is a kind of business risk appraisal procedure example principles schematic diagram provided in an embodiment of the present invention referring to Fig. 3.
First, the modules being related to Fig. 3 make following introduce.
Labeled data collection：The sample data provided using existing air control system, sample data is mainly each business
Strictly all rules set that user behavior data, existing air control system are hit to its user behavior and whether risky mark,
For example：For User logs in data, if hit IP high frequencies are accessed and IP code errors rate is higher than the regular collection of threshold value, mark
For " risky "；
Regression training module：It is mainly used in training existing air control system labeled data collection, is having for obtaining each rule
Model Weight under risk label and devoid of risk label, for example：" IP high frequency access rules, risky, weight 2.112345 ",
It represents that weight of the rule under risky label is larger, illustrates that this regular risk class is higher；
Model Weight converts value module：Because Model Weight is all decimal, such as 0.01234, it is unfavorable for artificial judgement,
Therefore, score value is switched to by Linear Mapping, for example, switchs to 0 to 100 point；
Same type rule weight accumulator module：Because in existing air control system, certain rule because the frequency of its triggering not
Together, different risk class may be corresponded to, such as IP access rules, according to the size of its frequency, may correspond to high-risk grade
And low risk level, and this is considered as two sub-rules of same type in existing air control system：IP high frequencies access rule and IP
Low frequency access rule；Therefore, in order to ensure that same type sub-rule becomes big according to its numerical intervals and risk class becomes big, therefore enter
Row score value weight adds up, the regular score value of the cumulative IP low frequencies of the regular score value of such as IP intermediate frequencies, the cumulative IP intermediate frequencies of IP high frequent rules score value
Regular score value；
Air control grading module：Certain user behavior data provided according to business datum to be assessed, identifies that it is triggered
Strictly all rules, and add up these regular score values, then compare total score and the threshold value being previously set, to export risk etc.
Level.
Below, the specific steps to the example make following illustrate.
S1：It is risky and devoid of risk using existing air control system marks data set D, while marking every with dualistic manner
The sub-rule of data-triggered；
S2：D is trained with L2 regularizations using logistic regression algorithm, y in Model Weight β, following formula is obtained and represents
Whether risky, x represents the rule of triggering；
S3：β is mapped as by every sub-rule score value s by Linear Mapping, while being repaiied according to the default level of every rule
The relatively low weight of positive weights；
S=A β
S4：By same type rule inferior grade score value be added to successively it is high-grade, with ensure same type rule it is high-grade
Score value is more than inferior grade, and such as same type rule has Three Estate 1,2,3, then its fraction is as follows：
s1=A β1
s2=s1+Aβ2
s3=s2+Aβ3
S5：The ratio of different brackets data is set according to priori, the boundary value S of different brackets total score is obtained；
S=s1x1+s2x2+...+snxn
S6：For the data of abnormal behaviour, adding up, it triggers regular score value, to determine risk class.
It can be seen that, in the business risk control method provided in an embodiment of the present invention added up based on weight, no longer only rely upon
The wall scroll rule that abnormal behaviour is triggered, but the strictly all rules triggered by the abnormal behaviour, with the regular score value of various dimensions
Cumulative mode carries out risk judgment；Moreover, without manually setting every priority for not having rule, but by training existing wind
The data of control system obtain model, then according to the risk class of sub-rule, using weight it is cumulative in the form of transformation model weight as
Regular score value, and then reach the automatic purpose for setting regular score value then to export risk class.Only relied on relative to prior art
The air control mode of wall scroll rule, the present invention improves the generalization ability of air control system, first for prior art by artificial setting
The mode of rule prioritization, the present invention improves treatment effeciency.
It should be noted that for embodiment of the method, in order to be briefly described, therefore it to be all expressed as to a series of action group
Close, but those skilled in the art should know, 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 be carried out sequentially or simultaneously 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.
Reference picture 4, is a kind of business risk apparatus for evaluating structural representation provided in an embodiment of the present invention.The device bag
Include：Business data processing unit 401, risk score value assessment unit 402 and risk class determining unit 403
Business data processing unit 401, for receiving business datum to be assessed, and according to preset risk rule engine,
Identify the regular collection of business datum matching.
Wherein, business datum includes but is not limited to registration business datum, registering service data, authentication services data, and/
Or, movable anti-brush business datum, etc..Risk behavior rule refers to give birth to based on malicious user accounts information or operation behavior information
Into risk behavior rule, for example, risk behavior rule includes but is not limited to：Malicious user login/access, same address are frequent
Login/access, bad password are frequently logged on/is accessed, etc..
Risk score value assessment unit 402, for many rules in the regular collection, according to the risk pre-established
Assessment models, assess each regular corresponding risk score value；
Risk class determining unit 403, for the corresponding risk score value of many rules to be added up, and will it is cumulative after
The risk total score threshold value of each risk class of the risk score value summation with pre-setting is compared, and determines the wind of business datum
Dangerous grade.
It is preferred that, the device also includes：Risk evaluation model sets up unit 404, for setting up the risk evaluation model；
The risk evaluation model sets up unit 404 specifically for obtaining sample data；Sample data to acquisition is trained, and is obtained
To each regular Model Weight；Each regular Model Weight is converted into by score value by Linear Mapping；According to same type
The risk of rule triggering frequency, the score value for the same type rule that adds up successively；And, the corresponding risk of the different risk class of setting is total
Divide threshold value
It is preferred that, risk evaluation model sets up unit 404 specifically for the sample data to acquisition carries out logistic time
Return training, obtain each regular Model Weight.Logistic regression essence is a kind of sorting algorithm, has used a sigmod
Function, the linear weighted function result of feature is mapped between 0 to 1, and this can just regard that data sample point belongs to a certain as
The probability of class.If result is closer to 0 or 1, illustrate that the confidence level of classification results is higher.
It is preferred that, the business data processing unit 401 specifically for：Using the risk rule engine, based on safety
Malicious user accounts information or operation behavior information in data warehouse, match corresponding each risk behavior rule of business datum
Then constitute the regular collection.
Being introduced as before, risk rule engine is generally comprised in risk system, in this step, it is possible to use risk rule is drawn
Hold up, based on the malicious user information in secure data warehouse, match corresponding each risk behavior rule of business datum and constitute
Regular collection.Wherein, account information includes but is not limited to cell-phone number, IP, user name；Operation behavior information includes but is not limited to frequency
It is numerous to log in ,/access, bad password is repeatedly logged in/and access, etc. for example, being frequently logged on using same IP address.
Reference picture 5, is a kind of air control system structure diagram provided in an embodiment of the present invention.The system includes：At business
Device 501, service access device 502, risk rule engine 503, secure data warehouse 504, intercept process device 505 are managed, it is special
Other, the system also includes risk assessment device 506, wherein：
The business processing device 501, is linked into risk rule by the service access model 502 by business datum and draws
Hold up 503；
The risk rule engine 503, malicious user accounts information or operation behavior in secure data warehouse 504
Information, matches corresponding each risk behavior rule of business datum and constitutes risk rule set；
The risk assessment device 506, for many rules in the regular collection, according to the risk pre-established
Assessment models, assess each regular corresponding risk score value, and the corresponding risk score value of many rules is added up, and will be tired
Plus after the risk total score threshold value of each risk class of the risk score value summation with pre-setting be compared, determine business number
According to risk class；
The intercept process device 505, it is right based on preset interception strategy for the risk class according to business datum
Business datum is intercepted.
It is preferred that, the risk assessment device 506 is additionally operable to set up risk evaluation model, specifically, obtaining sample data；
Sample data to acquisition is trained, and obtains each regular Model Weight；By Linear Mapping by each regular model
Weight is converted into score value；The risk of frequency is triggered according to described each regular sub-rule, point for each sub-rule that adds up successively
It is worth to the regular score value；And, the corresponding risk total score threshold value of the different risk class of setting.
It is preferred that, the business datum includes：Business datum, registering service data, authentication services data are registered, and/or,
The anti-brush business datum of activity；The risk behavior rule refers to what is generated based on malicious user accounts information or operation behavior information
Risk behavior rule.
For device embodiment, because it is substantially similar to embodiment of the method, so description is fairly simple, it is related
Part illustrates 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
Between the difference of other embodiment, 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.Moreover, the embodiment of the present invention can use it is one or more wherein include computer can
With in the computer-usable storage medium (including but is 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 can be by computer program instructions implementation process figure and/or block diagram
In each flow and/or square frame and the flow in flow chart and/or block diagram and/or the combination of square frame.These can be provided
Computer program instructions are set to all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing terminals
Standby processor is to produce 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 flows and/or one square frame of block diagram or multiple square frames
The device for the function of specifying.
These computer program instructions, which may be alternatively stored in, can guide computer or other programmable data processing terminal equipments
In the computer-readable memory worked in a specific way so that the instruction being stored 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 flows and/or one side of 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 processing, 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 frames 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.Moreover, term " comprising ", "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 include 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.
Above to the dispatching method and system of a kind of relevant database provided by the present invention, it is described in detail,
Specific case used herein is set forth to the principle and embodiment of the present invention, and the explanation of above example is to use
Understand the method and its core concept of the present invention in help；Simultaneously for those of ordinary skill in the art, according to the present invention's
Thought, will change in specific embodiments and applications, in summary, and this specification content should not be construed as
Limitation of the present invention.
Claims (13)
1. a kind of business risk appraisal procedure, it is characterised in that including：
Business datum to be assessed is received, and according to preset risk rule engine, identifies the risk behavior of business datum matching
Regular collection；
To many rules in the regular collection, according to the risk evaluation model pre-established, each rule is assessed corresponding
Risk score value；
The corresponding risk score value of many rules is added up, and will it is cumulative after risk score value summation and pre-set each
The risk total score threshold value of risk class is compared, and determines the risk class of business datum.
2. the method as described in claim 1, it is characterised in that also include：
The risk evaluation model is set up, including：Obtain sample data；Sample data to acquisition is trained, and obtains each
The Model Weight of rule；Each regular Model Weight is converted into by score value by Linear Mapping；According to each in the rule
Sub-rule triggers the risk of frequency, and the score value for each sub-rule that adds up successively obtains the regular score value；And, set different
The corresponding risk total score threshold value of risk class.
3. method as claimed in claim 2, it is characterised in that the sample data to acquisition carries out logistic regression training,
Obtain each regular Model Weight.
4. the method as described in claim 1, it is characterised in that described according to preset risk rule engine, identifies business
The regular collection of Data Matching, including：
The risk rule engine, based on the malicious user accounts information or operation behavior information in secure data warehouse, matching
Go out corresponding each risk behavior rule of business datum and constitute the regular collection.
5. the method as described in claim any one of 1-4, it is characterised in that the business datum includes：Registration business datum,
Registering service data, authentication services data, and/or, movable anti-brush business datum；The risk behavior rule refers to based on malice
User account information or the risk behavior rule of operation behavior information generation.
6. a kind of business risk apparatus for evaluating, it is characterised in that including：
Business data processing unit, for receiving business datum to be assessed, and according to preset risk rule engine, identifies industry
The regular collection for Data Matching of being engaged in；
Risk score value assessment unit, for many rules in the regular collection, according to the risk assessment mould pre-established
Type, assesses each regular corresponding risk score value；
Risk class determining unit, for the corresponding risk score value of many rules to be added up, and will it is cumulative after risk point
The risk total score threshold value of each risk class of the value summation with pre-setting is compared, and determines risk of business datum etc.
Level.
7. device as claimed in claim 6, it is characterised in that also include：Risk evaluation model sets up unit, for setting up
State risk evaluation model；
The risk evaluation model set up unit specifically for：Obtain sample data；Sample data to acquisition is trained, and is obtained
To each regular Model Weight；Each regular Model Weight is converted into by score value by Linear Mapping；According to the rule
In each sub-rule trigger frequency risk, successively add up each sub-rule score value obtain the regular score value；And, if
Put the corresponding risk total score threshold value of different risk class.
8. device as claimed in claim 7, it is characterised in that the risk evaluation model sets up unit specifically for obtaining
The sample data taken carries out logistic regression training, obtains each regular Model Weight.
9. device as claimed in claim 6, it is characterised in that the business data processing unit specifically for：Using described
Risk rule engine, based on the malicious user accounts information or operation behavior information in secure data warehouse, matches business number
The regular collection is constituted according to each corresponding risk behavior rule.
10. the device as described in claim any one of 6-9, it is characterised in that the business datum includes：Registration business number
According to, registering service data, authentication services data, and/or, movable anti-brush business datum；The risk behavior rule refers to be based on
Malicious user accounts information or the risk behavior rule of operation behavior information generation.
11. a kind of air control system, including business processing device, service access device, risk rule engine, secure data warehouse,
Intercept process device, it is characterised in that the system also includes risk assessment device, wherein：
The business processing device, risk rule engine is linked into by business datum by the service access model；
The risk rule engine, malicious user accounts information or operation behavior information in secure data warehouse, matching
Go out corresponding each risk behavior rule of business datum and constitute risk rule set；
The risk assessment device, for many rules in the regular collection, according to the risk assessment mould pre-established
Type, assesses each regular corresponding risk score value, and the corresponding risk score value of many rules is added up, and will it is cumulative after
The risk total score threshold value of each risk class of the risk score value summation with pre-setting is compared, and determines the wind of business datum
Dangerous grade；
The intercept process device, for the risk class according to business datum, based on preset interception strategy, to business datum
Intercepted.
12. system as claimed in claim 11, it is characterised in that the risk assessment device is additionally operable to set up risk assessment mould
Type, specifically, obtaining sample data；Sample data to acquisition is trained, and obtains each regular Model Weight；Pass through line
Property mapping each regular Model Weight is converted into score value；The risk of frequency is triggered according to described each regular sub-rule,
The score value of each cumulative sub-rule obtains the regular score value successively；And, the corresponding risk of the different risk class of setting is total
Divide threshold value.
13. the system as described in claim 11 or 12, it is characterised in that the business datum includes：Register business datum, step on
Business datum, authentication services data are recorded, and/or, movable anti-brush business datum；The risk behavior rule refers to use based on malice
Family accounts information or the risk behavior rule of operation behavior information generation.
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| CN201710117674.3A CN107067157A (en) | 2017-03-01 | 2017-03-01 | Business risk appraisal procedure, device and air control system |
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| CN201710117674.3A CN107067157A (en) | 2017-03-01 | 2017-03-01 | Business risk appraisal procedure, device and air control system |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110125672A1 (en) * | 2004-06-08 | 2011-05-26 | Rosenthal Collins Group, L.L.C. | Method and system for providing electronic information for risk assesement and management via dynamic total net worth for multi-market electronic trading |
| CN103514566A (en) * | 2013-10-15 | 2014-01-15 | 国家电网公司 | Risk control system and method |
| CN104881783A (en) * | 2015-05-14 | 2015-09-02 | 中国科学院信息工程研究所 | E-bank account fraudulent conduct and risk detecting method and system |
| CN105279382A (en) * | 2015-11-10 | 2016-01-27 | 成都数联易康科技有限公司 | Medical insurance abnormal data on-line intelligent detection method |
| CN105590055A (en) * | 2014-10-23 | 2016-05-18 | 阿里巴巴集团控股有限公司 | Method and apparatus for identifying trustworthy user behavior in network interaction system |
| CN105763555A (en) * | 2016-03-31 | 2016-07-13 | 世纪禾光科技发展（北京）有限公司 | Website risk control server and method and client |
| CN105809035A (en) * | 2016-03-07 | 2016-07-27 | 南京邮电大学 | Android application real-time behavior based malicious software detection method and system |
| CN106067088A (en) * | 2016-05-30 | 2016-11-02 | 中国邮政储蓄银行股份有限公司 | E-bank accesses detection method and the device of behavior |
-
2017
- 2017-03-01 CN CN201710117674.3A patent/CN107067157A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110125672A1 (en) * | 2004-06-08 | 2011-05-26 | Rosenthal Collins Group, L.L.C. | Method and system for providing electronic information for risk assesement and management via dynamic total net worth for multi-market electronic trading |
| CN103514566A (en) * | 2013-10-15 | 2014-01-15 | 国家电网公司 | Risk control system and method |
| CN105590055A (en) * | 2014-10-23 | 2016-05-18 | 阿里巴巴集团控股有限公司 | Method and apparatus for identifying trustworthy user behavior in network interaction system |
| CN104881783A (en) * | 2015-05-14 | 2015-09-02 | 中国科学院信息工程研究所 | E-bank account fraudulent conduct and risk detecting method and system |
| CN105279382A (en) * | 2015-11-10 | 2016-01-27 | 成都数联易康科技有限公司 | Medical insurance abnormal data on-line intelligent detection method |
| CN105809035A (en) * | 2016-03-07 | 2016-07-27 | 南京邮电大学 | Android application real-time behavior based malicious software detection method and system |
| CN105763555A (en) * | 2016-03-31 | 2016-07-13 | 世纪禾光科技发展（北京）有限公司 | Website risk control server and method and client |
| CN106067088A (en) * | 2016-05-30 | 2016-11-02 | 中国邮政储蓄银行股份有限公司 | E-bank accesses detection method and the device of behavior |
Non-Patent Citations (1)
| Title |
|---|
| 陈刚: "《我国商业银行信用风险的度量与评估研究》", 30 November 2013, 知识产权出版社 * |
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| WO2020082559A1 (en) * | 2018-10-25 | 2020-04-30 | 深圳壹账通智能科技有限公司 | Risk detection method, apparatus and device based on association graph, and storage medium |
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| WO2020087758A1 (en) * | 2018-11-02 | 2020-05-07 | 平安科技（深圳）有限公司 | Abnormal traffic data identification method, apparatus, computer device, and storage medium |
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| CN110059905B (en) * | 2018-12-13 | 2023-04-18 | 创新先进技术有限公司 | Risk quantification method, risk identification system and storage medium |
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