CN106156027A - The recognition methods of a kind of abnormal transaction and device - Google Patents
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Abstract
The embodiment of the invention discloses recognition methods and the device of a kind of abnormal transaction, described method includes: obtains user and proposes to identify the transaction data of online transaction；If judging that described transaction is not wash sale according to described transaction data, then judge whether described both parties are association user；If described both parties are association user, it is determined that described transaction is abnormal transaction.In the embodiment of the present invention, when judging that online transaction is arm's length dealing, whether it is that association user is to judge whether described transaction is abnormal transaction further with both parties.
Description
Technical field
The present invention relates to Internet technical field, particularly to recognition methods and the device of a kind of abnormal transaction；
Background technology
Along with the development of the Internet, increasing user starts shopping at network (abbreviation net purchase), thing followed problem
More and more, such as, conclude the business the most problematic.Along with the increase of trading volume, abnormal transaction also gets more and more how
Various certain types of abnormal transaction becomes present urgent problem to utilize Internet technology effectively to identify.
Summary of the invention
The embodiment of the present invention provides recognition methods and the device of a kind of abnormal transaction, to improve the identification of online abnormal transaction
Rate.
In order to solve above-mentioned technical problem, the embodiment of the invention discloses following technical scheme:
First aspect provides the recognition methods of a kind of abnormal transaction, including:
Obtain user and propose to identify the transaction data of online transaction；
If judging that described transaction is not wash sale according to described transaction data, then judge whether described both parties are to close combination
Family；
If described both parties are association user, it is determined that described transaction is abnormal transaction.
Optionally, also include: if described both sides are not association users, it is determined that described transaction is arm's length dealing；Or
If it is determined that described transaction is wash sale, it is determined that described transaction is abnormal transaction.
Optionally, whether the described both sides judging described transaction are association user, including:
Collect the described both parties nontransaction relation data in different nontransaction scenes；
If collecting the described both parties nontransaction relation data in different nontransaction scenes, it is determined that described friendship
Easily both sides are association user.
Optionally, whether the described both sides judging described transaction are association user, also include:
When collecting the described both parties nontransaction relation data in different nontransaction scenes, according to described non-friendship
Easily relation data determines the degree of association of described both parties；
If described degree of association is more than predetermined threshold value, it is determined that described both parties are association user.
Optionally, the described degree of association determining described both parties according to described nontransaction relation data, including:
Different weighted values is given for described different nontransaction scene；
Calculate the score value of each described nontransaction scene；
Weighted value according to each nontransaction scene and score value calculate the total score of each nontransaction scene, and by described always
Score value is as the degree of association of both parties.
Second aspect provides the identification device of a kind of abnormal transaction, including:
Acquiring unit, proposes to identify the transaction data of online transaction for obtaining user；
According to described transaction data, first judging unit, for judging whether described transaction is wash sale；
Second judging unit, for when described first judging unit judges that described transaction is not wash sale, continues to judge
Whether described both parties are association user；
First determines unit, for when described second judging unit judges described both parties as association user, determining institute
State transaction for abnormal transaction.
Optionally, also include: second determines unit, for judging that described both parties are not at described second judging unit
During association user, determine that described transaction is arm's length dealing；And/or
3rd determines unit, for when judging that described transaction is wash sale at described first judging unit, determines described
Transaction is abnormal transaction.
Optionally, described second judging unit includes:
Collector unit, for when described first judging unit judges that described transaction is not wash sale, collects described transaction
The both sides' nontransaction relation data in different nontransaction scenes；
First association user determines unit, for when described collector unit collects described nontransaction relation data, determines
Described both parties are association user.
Optionally, described second judging unit also includes:
Second association user determines unit, is used for when described collector unit collects described nontransaction relation data, according to
Described nontransaction relation data determines the degree of association of described both parties；
Association user's judging unit, for when described degree of association is more than predetermined threshold value, it is determined that described both parties are association
User.
Optionally, described second association user determines that unit includes:
Unit is set, for giving different weighted values for described different nontransaction scene；
Score value computing unit, for calculating the score value of each described nontransaction scene；
Correlation calculating unit, calculates each nontransaction scene for the weighted value according to each nontransaction scene and score value
Total score, and using described total score as the degree of association of both parties.
As shown from the above technical solution, in the embodiment of the present invention, when judging that online transaction is arm's length dealing, sentence further
Whether the easy both sides that break off a friendship are association user, and when judging both parties as association user, determine that this transaction is handed over for abnormal
Easily.It is to say, the embodiment of the present invention, when the behavioral data of online transaction is normal, further by both parties'
Nontransaction relation data judges whether this transaction is abnormal transaction, thus improves the discrimination of online abnormal transaction.
Accompanying drawing explanation
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to required in embodiment
Accompanying drawing to be used is briefly described, it should be apparent that, the accompanying drawing in describing below is only some enforcements of the present invention
Example, for those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to attached according to these
Figure obtains other accompanying drawing.
The flow chart of the recognition methods of a kind of abnormal transaction that Fig. 1 provides for the embodiment of the present invention；
The flow chart of the application example of the identification of a kind of abnormal transaction that Fig. 2 provides for the embodiment of the present invention；
Whether a kind of both parties of judgement that Fig. 3 provides for the embodiment of the present invention are the flow chart associating user；
The structural scheme of mechanism identifying device of a kind of abnormal transaction that Fig. 4 provides for the embodiment of the present invention；
The structural representation of a kind of webserver that Fig. 5 provides for the embodiment of the present invention；
The structural representation of the application example of a kind of webserver that Fig. 6 provides for the embodiment of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Description, it is clear that described embodiment is only a part of embodiment of the present invention rather than whole embodiments.Base
Embodiment in the present invention, it is all that those of ordinary skill in the art are obtained under not making creative work premise
Other embodiments, broadly fall into the scope of protection of the invention.
The term used in embodiments of the present invention is only merely for describing the purpose of specific embodiment, and is not intended to be limiting this
Invention." a kind of ", " described " and " being somebody's turn to do " of singulative used in the embodiment of the present invention and appended claims
It is also intended to include most form, unless context clearly shows that other implications.It is also understood that art used herein
Any or all possible combination that language "and/or" refers to and comprises one or more project of listing being associated.
Although should be appreciated that and term first, second, third, etc. may being used in embodiments of the present invention to describe various letter
Breath, but these information should not necessarily be limited by these terms.These terms are only used for same type of information is distinguished from each other out.Example
As, in the case of without departing from range of embodiment of the invention, the first information can also be referred to as the second information, it is not necessary to
Seek or imply relation or the order that there is any this reality between these entities or operation.Similarly, the second information
The first information can also be referred to as.Depend on linguistic context, word as used in this " if " can be construed to
" ... time " or " when ... " or " in response to determining ".And, term " includes ", " comprising " or its
Any other variant is intended to comprising of nonexcludability, so that include the process of a series of key element, method, article
Or equipment not only includes those key elements, but also includes other key elements being not expressly set out, or also includes for this
The key element that the process of kind, method, article or equipment are intrinsic.
Refer to the flow chart of the recognition methods of a kind of abnormal transaction that Fig. 1, Fig. 1 provide for the embodiment of the present invention, described
Method includes:
Step 101: obtain user and propose to identify the transaction data of online transaction；
In this step, after user's shopping on the web, if it find that commercial quality problem, and after consulting to have no result with seller, for
Safeguard the interests of self, identification request can be proposed to network service end, in order to network service end (such as Taobao visitor
Family end etc.) intervention process.Now, the server of networking client receives the identification request that user proposes, and collects this friendship
Easy transaction data.
Step 102: if judging that described transaction is not wash sale according to described transaction data, then judge that described transaction is double
Whether side is association user, if association user, performs step 103；
In this step, described association user is the people (i.e. acquaintance) being familiar with, or is the user that can be simultaneously benefited.
When server at networking client receives identification request, first judge whether with this transaction be wash sale, and it is sentenced
This transaction disconnected be whether wash sale according to being:
First obtain the behavioral data of each transaction of both parties in this transaction flow, then, it is judged that both parties are respective
Trading activity data are the most abnormal, if abnormal, determine that this transaction is wash sale, otherwise, it determines this transaction is not empty
False transaction (i.e. arm's length dealing).
In this step, if it is determined that this transaction is arm's length dealing, then continue to judge whether these both parties are association user,
Its process judged includes two ways, specifically includes:
A kind of mode is: 1) when judging that this transaction is arm's length dealing, first collect described both parties in different non-friendships
The easily nontransaction relation data in scene；
It is to say, networking client the both parties of this transaction of online collection in actual life whether about coefficient
According to, this relation data is the data unrelated with this transaction, and such as, before or after this transaction is, whether both parties send out
Gave birth to the most nontransaction transferring accounts；Whether both parties are stored in the cell-phone number of the other side in the address list of oneself；Both parties
Microblogging, wechat are paid close attention to the most mutually；Whether both parties are through a conventional ship-to；Or, both parties are
No it is connected on a wireless router etc..But, the nontransaction relation data of these information reflects not in process of exchange
Out.
It should be noted that the nontransaction relation data collected in the present embodiment is not limited to, this is above-mentioned, applies in reality
It also has a lot of source, and such as, operator has the information of communication, SNS website to have direct social networks information, position
Service provider has geographical location information, Department of Civil Affairs information etc. of calling cousin with to be all nontransaction relation data.In the present embodiment,
Main with microblogging, wallet, as a example by the relation data that Alipay etc. is collected.
2) if collecting the described both parties nontransaction relation data in different nontransaction scenes, it is determined that institute
State both parties for association user.
If it is to say, the both parties collecting this transaction have nontransaction relation data in actual life, it is determined that
Known to these both parties are, it is thus regarded that these both parties are association user.
Another way is: this mode on the basis of aforesaid way, for the nontransaction relation data collected make into
The judgement of one step, i.e. first determines the degree of association of both parties, then determines according to degree of association according to nontransaction relation data
Whether both parties are association user, and its detailed process includes:
1) the described both parties nontransaction relation data in different nontransaction scenes is collected；
In this step, networking client is collected the process of this nontransaction relation data and is referred to said process, does not repeats them here.
2) if collecting the described both parties nontransaction relation data in different nontransaction scenes, according to described
Nontransaction relation data determines the degree of association of described both parties；
Wherein it is determined that a kind of mode of the degree of association of described both parties is: give not for described different nontransaction scene
Same weighted value；Calculate the score value of each described nontransaction scene；Weighted value according to each nontransaction scene and score
Value calculates the total score (being referred to as relation score value) of each nontransaction scene, and using described total score as both parties
Degree of association.
Illustrate in order to make it easy to understand, existing.Such as, user ujTo user uiFor, they are in the most relation scenes
Middle appearance, occurrence number is the most in each scene, and user u is describedjWith user uiRelation the strongest.Specific amounts
Change calculating can be adopted with the following method but is not limited to this, and the present embodiment is that this score value is for user u as exampleiCome
Say, user ujComputational methods be similar to:
The computing formula of total score (i.e. relation score value) is:Wherein, n represents pass
It is scene number, such as user ujWith user uiExisted and transferred accounts, in address list, had the other side, microblogging was mutually paid close attention to three kinds of relation scenes,
So n=3；wkRepresent the weighted value of this scene, scorekRepresent the score value under this scene.
Wherein, scorekComputing formula be:Wherein, Num (ui,uj)kRepresent user
ui,ujInteraction times in scene k, this formula Middle molecule represents two users interaction times in scene k, and denominator represents
Total interaction times of the contact person Scene k of user ui.
Wherein, wkRepresent the weighted value of this scene, following formula can be passed throughDetermine, N (ui)k
Represent user ui number of contacts under k scene.
It follows that user ujWith user uiTotal score (i.e. relation score value) between two people can take both maximums i.e.:
Scoreij=max (Score ＜ ui,uj＞, Score ＜ uj,ui＞).
In this step, networking client when collecting the both parties' nontransaction relation data in actual life, according to
This nontransaction relation data judges in real life, whether has the strongest relation (i.e. degree of association) between both parties, from
And determine whether both parties know.
3) if described degree of association is more than predetermined threshold value, it is determined that described both parties are association user.
In this step, when the degree of association of both parties reaches certain predetermined threshold value, being considered as both parties is to close combination
Family.Wherein, predetermined threshold value can arrange different threshold values according to different demands.
Accordingly, if degree of association is less than predetermined threshold value, it is determined that described both parties are not association users, i.e. stranger.
Step 103: determine that described transaction is for abnormal transaction.
Certainly, in this embodiment, if in step 102, it is judged that described both parties are not association users, it is determined that
Described transaction is arm's length dealing；Fig. 1 does not shows.
In a step 102, network customer service end is if it is determined that both parties are association user, then explanation both parties are acquaintance,
So that it is determined that the transaction of both parties is problematic, herein problematic for both parties transaction is referred to as abnormal transaction.The most just
It is to say, at network customer service end when determining that this transaction is problematic transaction, the repudiation of claims, and refuse to described user transmission
The response compensated absolutely.
In the embodiment of the present invention, when judging that online transaction is arm's length dealing, determine whether whether the both sides of transaction are pass
Combination family, and when judging both parties as association user, determine that this transaction is for abnormal transaction.It is to say, the present invention
Embodiment, when the behavioral data of online transaction is normal, is judged by the nontransaction relation data of both parties further
Whether this transaction is abnormal transaction, thus improves the discrimination of online abnormal transaction.
Optionally, in another embodiment, this embodiment is on the basis of above-described embodiment, and described method can also include:
If described both sides are not association users, it is determined that described transaction is arm's length dealing, sends the response of compensation to described user.
Optionally, in another embodiment, this embodiment is on the basis of above-described embodiment, and described method can also include:
If it is determined that described transaction is wash sale, then send the response of the repudiation of claims to described user.
In the embodiment of the present invention, under some trade deal both sides are online with regard to time associated association user, by their behavior
Data can only judge that online trading is arm's length dealing, but can not identify whether this transaction is abnormal transaction, and
In the present embodiment, utilize the nontransaction relation data that some are unrelated with this transaction, such as nontransaction cash flow, address list, micro-
Rich good friend, with information such as machine log in, can identify in these arm's length dealings, and which is abnormal transaction, and which is normal
Transaction.Thus improve the discrimination of online abnormal transaction.Further, for abnormal transaction, refused satisfaction, reduce
The association user fraudulent claim rate by online transaction.
Also refer to the application example of the recognition methods of a kind of abnormal transaction that Fig. 2, Fig. 2 provide for the embodiment of the present invention
Flow chart, this embodiment is as a example by for the identification request (such as right-safeguarding request) proposed after user's shopping online, certainly
It is not limited to this in actual applications.Described method includes:
Step 200: receive the identification request that user proposes for online transaction；
Wherein, this identification request can be the right-safeguarding request provided for network trading, it is, of course, also possible to other requests,
The present embodiment is not restricted.
Step 201: propose to identify the transaction data of online transaction according to described identification acquisition request user；
I.e. collect the respective trading activity data of both parties in this transaction flow.
Step 202: judge whether described transaction is wash sale according to described transaction data, if wash sale, hold
Row step 204；Otherwise, step 203 is performed；
In this step, it is judged that foundation, it is judged that whether both parties' respective trading activity data abnormal, if abnormal,
Determine that this transaction is wash sale；Otherwise, this transaction is arm's length dealing.Its concrete judge process refers to above-mentioned, at this not
Repeat again.
Step 203: judge whether described both parties are association user, if association user, performs step 204；
If not association user, perform step 205；
It judges whether described both parties are that the judge process associating user refers to, shown in lower Fig. 3, not repeat them here.
Step 204: determine that described transaction is for abnormal transaction；And send, to described user, the sound that described transaction is abnormal transaction
Should；
In this embodiment, customer side, networking is after sending the response that described transaction is abnormal transaction, it is also possible to described use
Family sends the information of the repudiation of claims.Certainly the information of the repudiation of claims can be included in described response, it is also possible to independently transmitted,
The present embodiment is not restricted.
Step 205: determine that described transaction is arm's length dealing, and send, to described user, the sound that described transaction is arm's length dealing
Should.
In this embodiment, after transmission described transaction in customer side, networking is arm's length dealing, it is also possible to send this to described user
Transaction is the response of arm's length dealing, it should be noted that the information compensated can be included in described response, it is also possible to solely
Vertical transmission, the present embodiment is not restricted.
It should be noted that this embodiment can apply in the right-safeguarding of user, such as, when there is dispute in both parties,
If buyer initiates right-safeguarding application to network customer service end (i.e. third party), network customer service end needs to judge that this transaction is the most empty
False transaction, its foundation judged, the behavioral data only relying on both parties judges, if both parties are online real
Execute and conclude the business the most really, then judge that this transaction is not the most wash sale according to the behavioral data of this transaction, then need
Buyer is compensated by the company insured.But, if both parties are acquaintances, both parties are ready to pay the least
Cost (such as freight charges etc.) implements a bigger true sale of the amount of money, in order to during follow-up right-safeguarding, wholesale obtains
Gang up between profit, i.e. acquaintance, gain compensation by cheating by online trading.It is to say, in prior art, network customer service
End is to have no idea to identify this acquaintance to be carried out the problem of fraudulent claim by online transaction, based on this, in the embodiment of the present invention,
Network customer service end, when judging that described online transaction is not wash sale, needs to continue to judge whether described both parties are pass
Combination family (i.e. acquaintance or the people etc. of understanding)；And when determining these both parties for association user, determine that described transaction is different
Often transaction, the repudiation of claims, i.e. solve to identify the problem by online transaction fraudulent claim of ganging up between acquaintance.Pass through the present invention
In embodiment, not only increase the discrimination of online abnormal transaction, but also reduce association user by online transaction
Fraudulent claim rate.
In this embodiment, the specific descriptions of each step, refer to the description of corresponding step in said method, the most superfluous at this
State.
Whether a kind of both parties of judgement that also referring to Fig. 3, Fig. 3 provides for the embodiment of the present invention are the stream associating user
Cheng Tu, specifically includes:
Step 301: collect the described both parties nontransaction relation data in different nontransaction scenes；
Step 302: give different weighted values for described different nontransaction scene；
Step 303: calculate the score value of each described nontransaction scene；
Step 304: according to weighted value and the total score of the score value each nontransaction scene of calculating of each nontransaction scene,
And using described total score as the degree of association of both parties；
Step 305: judge whether the degree of association of described both parties is more than predetermined threshold value, if it is, perform step 306；
Otherwise, step 307 is performed；
Step 306: determine that described both parties are for association user；
Step 307: determine that described both parties are not association users.
Wherein, the association user in this embodiment, can be with acquaintance or the user known.
The process of realization based on said method, the embodiment of the present invention also provides for the identification device of a kind of abnormal transaction, its structure
As shown in Figure 4, described device includes schematic diagram: acquiring unit 41, the first judging unit 42, the second judging unit 33
Unit 44 is determined with first, wherein,
Described acquiring unit 41, proposes to identify the transaction data of online transaction for obtaining user；
Wherein, described acquiring unit specifically includes: first receives unit and obtain subelement, and wherein, first receives unit,
For receiving the identification request that user proposes for online transaction；Obtain subelement, for according to described identification acquisition request
The transaction data of described online transaction.
Wherein, in this embodiment, described identification request can be specifically right-safeguarding request, it is, of course, also possible to be other requests,
The present embodiment is not restricted.
According to described transaction data, described first judging unit 42, for judging whether described transaction is wash sale；
Described second judging unit 43, for when described first judging unit judges that described transaction is not wash sale, continues
Continue and judge whether described both parties are association user；
Described first determines unit 44, is used for when described second judging unit judges described both parties as association user,
Determine that described transaction is for abnormal transaction.
Optionally, when first determines that unit determines described transaction for abnormal transaction, described device can also include: first
Transmitting element, for when first determines that unit determines described transaction for abnormal transaction, to the described user feedback repudiation of claims
Response.Wherein, identifying that request is asked for right-safeguarding if described, the most described response is right-safeguarding response.
Optionally, in another embodiment, described device also includes: second determines unit (not shown), wherein,
Described second determines unit, for when described second judging unit judges that described both parties are not association users, determining
Described transaction is arm's length dealing；
Optionally, described device can also include: the second transmitting element, described for determining that unit determines described second
When transaction is for arm's length dealing, the response compensated to described user feedback.Wherein, identify that request is asked for right-safeguarding if described,
The most described response is right-safeguarding response.
Optionally, in another embodiment, described second judging unit 43 includes: collector unit and the first association user
Determine unit (not shown),
Wherein, described collector unit, for when described first judging unit judges that described transaction is not wash sale, receive
Collect the described both parties nontransaction relation data in different nontransaction scenes；
Described first association user determines unit, is used for when described collector unit collects described nontransaction relation data,
Determine that described both parties are for association user.
Optionally, described second judging unit can also include: the second association user determines that unit judges list with associating user
Unit's (not shown), wherein,
Described second association user determines unit, is used for when described collector unit collects described nontransaction relation data,
The degree of association of described both parties is determined according to described nontransaction relation data；
Described association user's judging unit, for when described degree of association is more than predetermined threshold value, it is determined that described both parties are
Association user.
Optionally, in another embodiment, described second association user determines that unit includes: arranging unit, score value calculates
Unit and correlation calculating unit, wherein,
Described unit is set, for giving different weighted values for described different nontransaction scene；
Described score value computing unit, for calculating the score value of each described nontransaction scene；
Described correlation calculating unit, calculates each nontransaction for the weighted value according to each nontransaction scene and score value
The total score of scene, and using described total score as the degree of association of both parties.
Optionally, in another embodiment, described device also includes: the 3rd determines unit, for judging described first
When transaction described in unit judges is for wash sale, determine that described transaction is for abnormal transaction.
Optionally, described device can also include the 3rd transmitting element, for determining that unit determines described friendship the described 3rd
When being easily abnormal transaction, send the response of the repudiation of claims to described user, wherein, identify that request please for right-safeguarding if described
Asking, the most described response is right-safeguarding response.
It should be noted that described device can also include that second determines that unit and the 3rd determines unit simultaneously.
In described device the function of unit and effect realize process, refer to the realization of corresponding step in said method
Journey, does not repeats them here.
In the embodiment of the present invention, when the behavioral data of online transaction is normal, further by the nontransaction pass of both parties
Coefficient is according to judging that this transaction is the most problematic, and for problematic transaction, the repudiation of claims, not only increases the most different
The often discrimination of transaction, but also reduce acquaintance's fraudulent claim rate by online transaction.
The embodiment of the present invention also provides for a kind of webserver, and its structural representation is as it is shown in figure 5, the described webserver
5 include: transceiver 51 and processor 52, wherein,
Described transceiver 51, proposes to identify the transaction data of online transaction for obtaining user；
Described processor 52, for judging whether described transaction is wash sale according to described transaction data, and is judging institute
Stating transaction when being not wash sale, continuing to judge whether described both parties are to associate user；
Described processor 52, is additionally operable to, when described processor judges described both parties as association user, determine described friendship
It it is easily abnormal transaction.
Optionally, described transceiver 51, it is additionally operable to when described processor determines described transaction for abnormal transaction, to described
User sends the response that described transaction is abnormal transaction.It should be noted that the information of the repudiation of claims can be included in described
In response, it is also possible to independently transmitted, the present embodiment is not restricted.
Optionally, described processor 52, it is additionally operable to judge that described both sides are not association users at described processor, determines institute
Stating transaction is arm's length dealing；
Described transceiver 51, is additionally operable to, when described processor determines that described transaction is arm's length dealing, send to described user
The response compensated.
Optionally, described processor 52 judges whether the both sides of described transaction are association user, specifically include: collect institute
State the both parties' nontransaction relation data in different nontransaction scenes；If collecting described both parties in difference
Nontransaction scene in nontransaction relation data, it is determined that described both parties for association user.
Optionally, described processor 52 judges whether the both sides of described transaction are association user, the most also include: receiving
When collecting to the described both parties nontransaction relation data in different nontransaction scenes, according to described nontransaction pass coefficient
According to the degree of association determining described both parties；If described degree of association is more than predetermined threshold value, it is determined that described both parties are
Association user.
Optionally, described in described processor 52, determine the degree of association of described both parties according to described nontransaction relation data,
Including: give different weighted values for described different nontransaction scene；Calculate the score value of each described nontransaction scene；
Weighted value according to each nontransaction scene and the total score of the score value each nontransaction scene of calculating, and by described total score
Degree of association as both parties.
Optionally, described processor 52, it is additionally operable to, when described processor judges described transaction as wash sale, determine institute
State transaction for abnormal transaction；
Described transceiver 51, is additionally operable to, when described processor determines described transaction for abnormal transaction, send to described user
The response of the repudiation of claims.
Also refer to the structural representation of the application example of a kind of webserver that Fig. 6, Fig. 6 provide for the embodiment of the present invention
Figure, this webserver 600 includes: processor 610, memorizer 620, transceiver 630 and bus 640；
Processor 610, memorizer 620, transceiver 630 are connected with each other by bus 640；Bus 640 can be ISA
Bus, pci bus or eisa bus etc..Described bus can be divided into address bus, data/address bus, control bus etc..
For ease of representing, Fig. 6 only represents with a thick line, it is not intended that an only bus or a type of bus.
Memorizer 620, is used for depositing program.Specifically, program can include that program code, described program code include
Computer-managed instruction.Memorizer 620 may comprise high-speed RAM memorizer, it is also possible to also includes nonvolatile memory
(non-volatile memory), for example, at least one disk memory.
Described transceiver 630 is used for connecting other equipment, and communicates with other equipment.Concrete described transceiver 530
May be used for: obtain user and propose to identify the transaction data of online transaction；；
Described processor 610 performs the described program code of storage in memorizer 620, for sentencing according to described transaction data
Whether fixed described transaction is wash sale, and when judging that described transaction is not wash sale, continues to judge that described transaction is double
Whether side is association user, and when judging described both parties as association user, determines that described transaction is for abnormal transaction.
Alternatively, described processor 610 can be also used for: when judging that described both sides are not association users, determines described
Transaction is arm's length dealing.
Alternatively, described processor 610 can be also used for: when judging that described transaction is wash sale, determines described friendship
It it is easily abnormal transaction.
In the embodiment of the present invention, under some trade deal both sides are online with regard to time associated association user, by their behavior
Data can only judge that online trading is arm's length dealing, but can not identify whether this transaction is abnormal transaction, and
In the present embodiment, utilize the nontransaction relation data that some are unrelated with this transaction, such as nontransaction cash flow, address list, micro-
Rich good friend, with information such as machine log in, can identify in these arm's length dealings, and which is abnormal transaction, and for exception
Transaction, refused satisfaction.Not only increase the discrimination of online abnormal transaction, but also reduce association user by online
The fraudulent claim rate of transaction.
Those skilled in the art it can be understood that can add by software to the technology in the embodiment of the present invention required
The mode of general hardware platform realizes.Based on such understanding, the technical scheme in the embodiment of the present invention substantially or
Saying that the part contributing prior art can embody with the form of software product, this computer software product is permissible
It is stored in storage medium, such as ROM/RAM, magnetic disc, CD etc., instructs with so that a computer sets including some
Standby (can be personal computer, server, or the network equipment etc.) performs each embodiment of the present invention or embodiment
The method described in some part.
Each embodiment in this specification all uses the mode gone forward one by one to describe, identical similar part between each embodiment
Seeing mutually, what each embodiment stressed is the difference with other embodiments.Especially for system
For embodiment, owing to it is substantially similar to embodiment of the method, so describe is fairly simple, relevant part sees method
The part of embodiment illustrates.
Invention described above embodiment, is not intended that limiting the scope of the present invention.Any the present invention's
Amendment, equivalent and the improvement etc. made within spirit and principle, should be included within the scope of the present invention.
Claims (10)
1. the recognition methods of an abnormal transaction, it is characterised in that including:
Obtain user and propose to identify the transaction data of online transaction；
If judging that described transaction is not wash sale according to described transaction data, then judge whether described both parties are pass
Combination family；
If described both parties are association user, it is determined that described transaction is abnormal transaction.
Method the most according to claim 1, it is characterised in that also include:
If described both sides are not association users, it is determined that described transaction is arm's length dealing；Or
If judging that described transaction is as wash sale according to described transaction data, it is determined that described transaction is abnormal transaction.
Method the most according to claim 1, it is characterised in that whether the described both sides judging described transaction are pass
Combination family, including:
Collect the described both parties nontransaction relation data in different nontransaction scenes；
If collecting the described both parties nontransaction relation data in different nontransaction scenes, it is determined that described friendship
Easily both sides are association user.
Method the most according to claim 3, it is characterised in that whether the described both sides judging described transaction are pass
Combination family, also includes:
When collecting the described both parties nontransaction relation data in different nontransaction scenes, according to described non-friendship
Easily relation data determines the degree of association of described both parties；
If described degree of association is more than predetermined threshold value, it is determined that described both parties are association user.
Method the most according to claim 4, it is characterised in that described determine according to described nontransaction relation data
The degree of association of described both parties, including:
Different weighted values is given for described different nontransaction scene；
Calculate the score value of each described nontransaction scene；
Weighted value according to each nontransaction scene and score value calculate the total score of each nontransaction scene, and by described always
Score value is as the degree of association of both parties.
6. the identification device of an abnormal transaction, it is characterised in that including:
Acquiring unit, proposes to identify the transaction data of online transaction for obtaining user；
According to described transaction data, first judging unit, for judging whether described transaction is wash sale；
Second judging unit, for when described first judging unit judges that described transaction is not wash sale, continues to judge
Whether described both parties are association user；
First determines unit, for when described second judging unit judges described both parties as association user, determining institute
State transaction for abnormal transaction.
Device the most according to claim 6, it is characterised in that also include:
Second determines unit, for when described second judging unit judges that described both parties are not association users, determining
Described transaction is arm's length dealing；And/or
3rd determines unit, for when judging that described transaction is wash sale at described first judging unit, determines described
Transaction is abnormal transaction.
Device the most according to claim 6, it is characterised in that described second judging unit includes:
Collector unit, for when described first judging unit judges that described transaction is not wash sale, collects described transaction
The both sides' nontransaction relation data in different nontransaction scenes；
First association user determines unit, for when described collector unit collects described nontransaction relation data, determines
Described both parties are association user.
Device the most according to claim 8, it is characterised in that described second judging unit also includes:
Second association user determines unit, is used for when described collector unit collects described nontransaction relation data, according to
Described nontransaction relation data determines the degree of association of described both parties；
Association user's judging unit, for when described degree of association is more than predetermined threshold value, it is determined that described both parties are association
User.
Device the most according to claim 9, it is characterised in that described second association user determines that unit includes:
Unit is set, for giving different weighted values for described different nontransaction scene；
Score value computing unit, for calculating the score value of each described nontransaction scene；
Correlation calculating unit, calculates each nontransaction scene for the weighted value according to each nontransaction scene and score value
Total score, and using described total score as the degree of association of both parties.
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| CN201510130496.9A CN106156027A (en) | 2015-03-24 | 2015-03-24 | The recognition methods of a kind of abnormal transaction and device |
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| CN201510130496.9A CN106156027A (en) | 2015-03-24 | 2015-03-24 | The recognition methods of a kind of abnormal transaction and device |
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