CN109658260A - Method and device, medium and electronic equipment are determined based on the fraud of block chain - Google Patents
Method and device, medium and electronic equipment are determined based on the fraud of block chain Download PDFInfo
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- CN109658260A CN109658260A CN201811504282.3A CN201811504282A CN109658260A CN 109658260 A CN109658260 A CN 109658260A CN 201811504282 A CN201811504282 A CN 201811504282A CN 109658260 A CN109658260 A CN 109658260A
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Abstract
The invention discloses a kind of frauds based on block chain to determine method and device, medium and electronic equipment, is related to block chain technical field.The fraud determines that method includes: by block chain network memory of driving accident information；Wherein, the accident information that drives includes the image before driving accident occurs；Image before the driving accident of block chain network storage occurs identifies, to determine the vehicle operation characteristic before the generation of driving accident；Determine vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.The disclosure can determine vehicle insurance Claims Resolution with the presence or absence of fraud.
Description
Technical field
This disclosure relates to block chain technical field, in particular to a kind of fraud determination side based on block chain
Method, fraud determining device, storage medium and electronic equipment based on block chain.
Background technique
As the improvement of people's living standards, motor vehicles become more and more popular.When there is accident in vehicle, Ke Yitong
Automobile insurance (abbreviation vehicle insurance) is crossed to retrieve a loss.Vehicle insurance refers to motor vehicles by natural calamity or contingency institute
Caused by personal injury or a kind of business insurance of the negative liability to pay compensation of property loss.Currently, vehicle insurance has become Chinese property insurance
One of most important insurance kind in business.
For this field of vehicle insurance, fraud, insurance fraud event take place frequently, and make vehicle insurance companies losses heavy.Currently, mainly manually
The mode reconnoitred whether there is fraud to find that vehicle insurance is settled a claim in the process.However, manual identified efficiency is lower, and cost
It is high.
It should be noted that information is only used for reinforcing the reason to the background of the disclosure disclosed in above-mentioned background technology part
Solution, therefore may include the information not constituted to the prior art known to persons of ordinary skill in the art.
Summary of the invention
A kind of fraud based on block chain of being designed to provide of the disclosure determines method, the fraud based on block chain
Behavior determining device, storage medium and electronic equipment, and then overcome go due to manually cheating vehicle insurance at least to a certain extent
Cause recognition efficiency lower and problem at high cost to be confirmed.
According to one aspect of the disclosure, a kind of fraud based on block chain is provided and determines method, the fraud row
To determine that method includes: by block chain network memory of driving accident information；Wherein, the driving accident information includes to drive thing
Therefore the image before occurring；Image before the driving accident of block chain network storage occurs identifies, is driven with determining
Vehicle operation characteristic before accident generation；Determine vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.
In a kind of exemplary embodiment of the disclosure, the block chain network is stored with vehicle historical information；Wherein, root
Determine that vehicle insurance Claims Resolution with the presence or absence of fraud includes: in conjunction with the vehicle historical information and described according to the vehicle operation characteristic
Accident information is driven, determines vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.
In a kind of exemplary embodiment of the disclosure, in conjunction with the vehicle historical information and the driving accident information,
Determining that vehicle insurance Claims Resolution whether there is fraud according to the vehicle operation characteristic includes: to be determined according to the vehicle historical information
History driving feature vector；Accident Characteristic vector is determined according to the driving accident information；Determine the history drive a vehicle feature to
Similarity between amount and the Accident Characteristic vector；Determine that vehicle insurance is managed according to the vehicle operation characteristic in conjunction with the similarity
It pays for and whether there is fraud.
In a kind of exemplary embodiment of the disclosure, vehicle is determined according to the vehicle operation characteristic in conjunction with the similarity
Danger Claims Resolution includes: the first assessment determined according to the vehicle operation characteristic for assessing fraud with the presence or absence of fraud
Parameter；Using the similarity as the second assessment parameter for being used to assess fraud；According to the first assessment parameter and institute
The weighted results for stating the second assessment parameter determine vehicle insurance Claims Resolution with the presence or absence of fraud.
In a kind of exemplary embodiment of the disclosure, vehicle is determined according to the vehicle operation characteristic in conjunction with the similarity
Danger Claims Resolution includes: the first assessment determined according to the vehicle operation characteristic for assessing fraud with the presence or absence of fraud
Parameter；Using the similarity as the second assessment parameter for being used to assess fraud；It is determined from the vehicle historical information
Vehicle is in danger number as the third for assessing fraud and assesses parameter；According to the first assessment parameter, described second
The weighted results of assessment parameter and third assessment parameter determine vehicle insurance Claims Resolution with the presence or absence of fraud.
It include: to pass through by block chain network memory of driving accident information in a kind of exemplary embodiment of the disclosure
The automobile data recorder and/or road monitoring camera of vehicle obtain the image before driving accident occurs, and by the driving accident
Image before generation is stored to the block chain network.
In a kind of exemplary embodiment of the disclosure, the fraud determines method further include: if vehicle insurance is settled a claim
There are frauds, then send a warning message to vehicle insurance platform.
According to one aspect of the disclosure, a kind of fraud determining device based on block chain, the fraud row are provided
It include information storage module, characteristic determination module and fraud judgment module for determining device.
Specifically, information storage module is used to pass through block chain network memory of driving accident information；Wherein, the driving thing
Therefore information includes the image before driving accident occurs；Characteristic determination module is used for the driving accident stored to the block chain network
Image before generation is identified, to determine the vehicle operation characteristic before the generation of driving accident；Fraud judgment module is used for
Determine vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.
In a kind of exemplary embodiment of the disclosure, the block chain network is stored with vehicle historical information；Wherein, it takes advantage of
Swindleness behavior judgment module is configurable in conjunction with the vehicle historical information and the driving accident information, according to the vehicle
Travelling characteristic determines vehicle insurance Claims Resolution with the presence or absence of fraud.
In a kind of exemplary embodiment of the disclosure, fraud judgment module is configurable for according to the vehicle
Historical information determines history driving feature vector；Accident Characteristic vector is determined according to the driving accident information；It is gone through described in determination
The similarity that history is driven a vehicle between feature vector and the Accident Characteristic vector；It is special according to the vehicle driving in conjunction with the similarity
It levies and determines that vehicle insurance Claims Resolution whether there is fraud.
In a kind of exemplary embodiment of the disclosure, fraud judgment module is configurable for according to the vehicle
Travelling characteristic determines the first assessment parameter for assessing fraud；Using the similarity as being used to assess fraud
Second assessment parameter；Whether vehicle insurance Claims Resolution is determined according to the weighted results of the first assessment parameter and the second assessment parameter
There are frauds.
In a kind of exemplary embodiment of the disclosure, fraud judgment module is configurable for according to the vehicle
Travelling characteristic determines the first assessment parameter for assessing fraud；Using the similarity as being used to assess fraud
Second assessment parameter；Determine that vehicle is in danger number as the third for assessing fraud and comments from the vehicle historical information
Estimate parameter；It is determined according to the weighted results of the first assessment parameter, the second assessment parameter and third assessment parameter
Vehicle insurance Claims Resolution whether there is fraud.
In a kind of exemplary embodiment of the disclosure, information storage module includes image storage unit.
Specifically, image storage unit is used to drive by automobile data recorder and/or road monitoring the camera acquisition of vehicle
The image before accident occurs is sailed, and the image before driving accident generation is stored to the block chain network.
In a kind of exemplary embodiment of the disclosure, fraud determining device further includes alarm sending module.
If sending and alerting to vehicle insurance platform specifically, alarm sending module is settled a claim for vehicle insurance there are fraud
Information.
According to one aspect of the disclosure, a kind of storage medium is provided, computer program, the computer are stored thereon with
It is realized when program is executed by processor and method is determined based on the fraud of block chain described in above-mentioned any one.
According to one aspect of the disclosure, a kind of electronic equipment is provided, comprising: processor；And memory, for storing
The executable instruction of the processor；Wherein, the processor is configured to above-mentioned to execute via the executable instruction is executed
Fraud described in any one based on block chain determines method.
It include driving accident by the storage of block chain network in the technical solution provided by some embodiments of the present disclosure
The driving accident information of image before occurring, the image before driving accident occurs identify, before determining that driving accident occurs
Vehicle operation characteristic, and determine vehicle insurance Claims Resolution with the presence or absence of fraud according to vehicle operation characteristic.On the one hand, it is based on the disclosure
Scheme, vehicle insurance Claims Resolution can be effectively determined out with the presence or absence of fraud.It, then can will be timely if there is fraud
Alarm is issued, to take measures, avoids losing；On the other hand, the disclosure passes through the memory of driving in block chain network
Accident information, making it possible to guarantee by block chain network to drive accident information can not distort, and can be based on block chain
Network stores to realize the traceable processing for driving accident information, and then the safety that can effectively ensure to drive accident information is total
It enjoys；In another aspect, the disclosure can based on stored in block chain network sail accident information determine vehicle insurance Claims Resolution whether there is
Fraud peomotes effective popularization of the block chain technology in terms of vehicle insurance settles a claim anti-fraud management.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.It should be evident that the accompanying drawings in the following description is only the disclosure
Some embodiments for those of ordinary skill in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.In the accompanying drawings:
Fig. 1 diagrammatically illustrates the fraud determination side based on block chain according to an exemplary embodiment of the present disclosure
The flow chart of method；
Fig. 2 diagrammatically illustrate according to an exemplary embodiment of the present disclosure realize fraud in block chain network
The block diagram of determining system；
Fig. 3 diagrammatically illustrates the fraud based on block chain according to an exemplary embodiment of the present disclosure and determines dress
The block diagram set；
Fig. 4 diagrammatically illustrates the block diagram of information storage module according to an exemplary embodiment of the present disclosure；
Fig. 5 diagrammatically illustrates true according to the fraud based on block chain of the another exemplary embodiment of the disclosure
Determine the block diagram of device；
Fig. 6 shows the schematic diagram of storage medium according to an exemplary embodiment of the present disclosure；And
Fig. 7 diagrammatically illustrates the block diagram of electronic equipment according to an exemplary embodiment of the present disclosure.
Specific embodiment
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be with a variety of shapes
Formula is implemented, and is not understood as limited to example set forth herein；On the contrary, thesing embodiments are provided so that the disclosure will more
Fully and completely, and by the design of example embodiment comprehensively it is communicated to those skilled in the art.Described feature, knot
Structure or characteristic can be incorporated in any suitable manner in one or more embodiments.In the following description, it provides perhaps
More details fully understand embodiment of the present disclosure to provide.It will be appreciated, however, by one skilled in the art that can
It is omitted with technical solution of the disclosure one or more in the specific detail, or others side can be used
Method, constituent element, device, step etc..In other cases, be not shown in detail or describe known solution to avoid a presumptuous guest usurps the role of the host and
So that all aspects of this disclosure thicken.
In addition, attached drawing is only the schematic illustrations of the disclosure, it is not necessarily drawn to scale.Identical attached drawing mark in figure
Note indicates same or similar part, thus will omit repetition thereof.Some block diagrams shown in the drawings are function
Energy entity, not necessarily must be corresponding with physically or logically independent entity.These function can be realized using software form
Energy entity, or these functional entitys are realized in one or more hardware modules or integrated circuit, or at heterogeneous networks and/or place
These functional entitys are realized in reason device device and/or microcontroller device.
Flow chart shown in the drawings is merely illustrative, it is not necessary to including all steps.For example, the step of having
It can also decompose, and the step of having can merge or part merges, therefore the sequence actually executed is possible to according to the actual situation
Change.
With the development of society, the means of swindle are more and more, insurance fraud event takes place frequently, especially for this field of vehicle insurance,
The means of insurance fraud emerge one after another, of all shapes and colors, make vehicle insurance companies losses heavy.However, at present and without a set of efficient prevention
Measure, mainly by artificially discovery fraud is reconnoitred, this mode recognition efficiency is low, at high cost.
In consideration of it, present disclose provides a kind of new frauds to determine method.
Fraud described below based on block chain determines that method can be realized based on server, in such case
Under, the fraud determining device of the disclosure can be only fitted in the server.However, the fraud of the disclosure determines method
It can also be realized by terminal device, not do particular determination in this illustrative embodiment to this.
The fraud based on block chain that Fig. 1 diagrammatically illustrates the illustrative embodiments of the disclosure determines method
Flow chart.With reference to Fig. 1, the fraud based on block chain determines that method may comprise steps of:
S12. pass through block chain network memory of driving accident information；Wherein, the driving accident information includes driving accident
Image before generation.
In the illustrative embodiments of the disclosure, it may include relevant to the driving accident of vehicle for driving accident information
Any information.Occur for example, driving accident information and may include the image before driving accident occurs, place where the accident occurred point, accident
Speed, accident occurrence cause etc. when time, accident occur.Wherein, driving the image before accident occurs can be driving accident
Image before occurring in preset time period, for example, the preset time period can be 10 seconds, 20 seconds etc., the disclosure is to preset time
The specific value of section is with no restrictions.It can also be comprising the information with vehicle maintenance, for example, maintenance factory in addition, driving accident information
Classification (for example, the shop 4S or non-shop 4S), the content (for example, vehicle face of metal plate, touch-up paint etc.) of vehicle maintenance, etc..
According to some embodiments of the present disclosure, the available driving accident information of server, and will drive accident information with
The form of block is sent to each node of block chain network.
Image before occurring for acquisition driving accident.Server can obtain driving accident from the automobile data recorder of vehicle
Image before generation.It in one embodiment, can be taking human as before copying out the generation of driving accident in the automobile data recorder of vehicle
Image, and the image is uploaded to server；In another embodiment, the automobile data recorder of vehicle can with server into
Row connection, so that server can directly acquire the image before driving accident occurs.Next, server can will drive accident
Image before generation is stored to block chain network.
In addition, server can obtain the image before driving accident occurs from road monitoring camera.In this case,
Server can establish connection with road traffic control department and obtain trust.Server can be obtained from road traffic control department as a result,
The image relevant to the accident of driving of road monitoring camera shooting, and image is stored to block chain network.
In order to avoid image is abused, in the scene shown in the embodiment of the present disclosure, encrypted transmission can be carried out to image.
For example, firstly, road traffic control department receive server transmission image acquisition request after, the public affairs of available server
Key, and the public key based on server is encrypted image using Encryption Algorithm；Next, road traffic control department can incite somebody to action
The relevant image of encrypted driving accident is sent to server；Then, server can be carried out based on itself corresponding private key
Decryption, to obtain the relevant image of driving accident.
In addition, server can also obtain road monitoring camera and clap under the premise of obtaining the image of automobile data recorder
The image taken the photograph, and these images are stored to block chain network.
According to some embodiments of the present disclosure, above-mentioned place where the accident occurred point, traffic injury time, accident occur when vehicle
The information such as speed, accident occurrence cause can determine by accident driver, and by these information that accident driver determines store to
Block chain network.In addition, server can also be by identifying the image got, the result based on identification determines this
A little information.
The disclosure makes it possible to guarantee by block chain network to drive by the memory of driving accident information in block chain
Accident information can not be distorted, and the traceable processing for driving accident information can be realized based on the storage of block chain network,
And then the safety that can effectively ensure to drive accident information is shared.
S14. the image before the driving accident of block chain network storage occurring identifies, to determine driving accident
Vehicle operation characteristic before generation.
According to some embodiments of the present disclosure, vehicle operation characteristic can be speed variation degree.Specifically, server can
It is identified with the image before driving accident occurs, to determine the speed variation degree before the accident of driving occurs.For example, first
First, the section that road monitoring camera can take can be determined；Next, determination relates to thing vehicle on the image of a moment point
Position, determined on the image of another moment point and relate to the position of thing vehicle；Then, pass through the time between two moment points
The distance of difference and vehicle corresponding position, determines the speed that vehicle travels in the road monitoring camera.By continuously holding
The row above process can determine that the variation degree of speed.It is easily understood that being also based on the driving note configured in vehicle
It records instrument and records image, to determine the variation degree of speed.
According to other embodiments of the disclosure, vehicle operation characteristic can be the variation degree of vehicle driving trace.Tool
Body, the image before server can occur driving accident identifies, to determine the vehicle row before the accident of driving occurs
Sail the variation degree of track.For example, it is possible, firstly, to determine the image that shoots in a moment point of road monitoring camera, and be based on
The image determines the position of the moment vehicle；Next it may be determined to the image that road monitoring camera is shot at another moment,
And it determines in the position of this moment vehicle.By continuously performing the above process, that is, it can determine that the variation of vehicle driving trace
Degree.It is easily understood that the automobile data recorder record image configured in vehicle is also based on, to determine vehicle driving trace
Variation degree.
According to other embodiments of the disclosure, vehicle operation characteristic may include speed variation degree and vehicle driving rail
The variation degree of mark.In addition, vehicle operation characteristic described in the disclosure is without being limited thereto, it can also include other features, for example, system
Traverse degree and the hedging extent of reaction etc..
S16. determine vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.
According to some embodiments of the present disclosure, after determining vehicle operation characteristic, server can be according to vehicle driving
Feature determines vehicle insurance Claims Resolution with the presence or absence of fraud.
By vehicle operation characteristic be speed variation degree for, drive accident occur before, if speed do not reduce or
Person's speed improves, then can determine that there are frauds for the vehicle insurance Claims Resolution based on the driving accident.For example, close when relating to thing vehicle
When one barrier, speed is improved, then can determine that there are frauds for vehicle insurance Claims Resolution.
By taking vehicle operation characteristic is the variation degree of vehicle driving trace as an example, before the accident of driving occurs, vehicle exists
The track for being biased to danger source intentionally is mobile, then can determine that there are frauds for the vehicle insurance Claims Resolution based on the driving accident.For example,
The vehicle travelled on river levee in the driving trace diverted stream of vehicle, then can determine vehicle insurance when not having emergency
There are frauds for Claims Resolution.
In addition, the variation degree that the disclosure can also block up variation degree and/or vehicle driving trace for vehicle is set separately
Threshold value, if it is determined that the vehicle operation characteristic gone out reaches set threshold value, then can determine that there are frauds for vehicle insurance Claims Resolution.
In other embodiments of the disclosure, vehicle historical information is stored in block chain network, wherein vehicle history
Information may include image, vehicle maintenance maintenance information, the vehicle traveling information etc. that automobile data recorder in history is recorded.Separately
Outside, vehicle historical information can also record information, driver personal be levied in violation of rules and regulations comprising vehicle insurance contract terms information, driver history
Letter information etc..Server can also will be helpful to further confirm that related vehicle insurance settle a claim the movable picture concerned of anti-fraud management or
Video is uploaded to block chain network.
In this case, server can combine vehicle historical information and drive accident information, and according to vehicle driving
Feature determines vehicle insurance with the presence or absence of fraud.
According to one embodiment of the disclosure, it is possible, firstly, to determine history driving feature vector according to vehicle historical information.
Specifically, history driving feature vector can be the vector being made of multiple features in vehicle historical information.For example, by history
Driving feature vector is denoted as H, then history driving feature vector H={ x1, x2, x3, x4 }, wherein x1 indicates vehicle high frequency traveling
Section, x2 indicate the vehicle high frequency travel time, and x3 indicates that vehicle average speed, x4 indicate history maintenance factory type (for example, with 0
The shop 4S is characterized, use 1 indicates the non-shop 4S).However, without being limited thereto, those skilled in the art are easy to associate in vehicle historical information
Multiple features other combinations, particular determination is not done to vehicle characteristics vector in this illustrative embodiment.
Next, can determine Accident Characteristic vector according to accident information is driven.Specifically, Accident Characteristic vector can be by
Drive the vector of multiple features composition in accident information.For example, Accident Characteristic vector is denoted as V, then Accident Characteristic vector V=
{ y1, y2, y3, y4 }, wherein y1 indicates that place where the accident occurred point, y2 indicate that traffic injury time, y3 indicate that vehicle meets accident front truck
Speed, y4 indicate this emergency maintenance factory type.It should be noted that Accident Characteristic vector V described herein and history above
The feature vector H that drives a vehicle is corresponding.However, it is understood that Accident Characteristic vector can be represented as driving in accident information
Other combinations of multiple features do not do particular determination to Accident Characteristic vector in this illustrative embodiment.
Then, server can determine the similarity between history driving feature vector and Accident Characteristic vector.Specifically,
The Euclidean distance of history driving feature vector H and Accident Characteristic vector V can be calculated, and really using Euclidean distance as similarity
Calibration is quasi-.Specifically, the Euclidean distance d of history driving feature vector H and Accident Characteristic vector V can be calculated by formula 1:
D=[sum (xi-yi) ^2] ^ (1/2), i=1,2,3,4 (formula 1)
It is to be understood, however, that can also using other modes characterization history driving feature vector and Accident Characteristic to
Similarity between amount, for example, Jie Kade distance, COS distance etc., do not do particular determination to this in this illustrative embodiment.
It is then possible to determine vehicle insurance Claims Resolution with the presence or absence of fraud in conjunction with similarity and according to vehicle operation characteristic.?
In this case, the first assessment parameter for assessing fraud can be determined according to vehicle operation characteristic, it will be above-mentioned similar
It spends as the second assessment parameter for assessing fraud, according to the weighted results of the first assessment parameter and the second assessment parameter
Determine vehicle insurance Claims Resolution with the presence or absence of fraud.Specifically, can establish risk evaluation model, as shown in formula 2:
Q1=w1*q+w2*d (formula 2)
Wherein, Q1 is the risk of fraud under this embodiment；Q is the first assessment parameter, i.e., above-mentioned to be based only upon vehicle driving
The risk of fraud that feature is determined；D is the second assessment parameter, i.e. phase between history driving feature vector and Accident Characteristic vector
Like degree；W1 and w2 is preset weight.Furthermore it is possible to which the value of the value ratio w2 of default w1 is big, for example, 0.8 is set by w1, by w2
It is set as 0.5, however, developer can fit w1 and w2 by testing, this is not done in this illustrative embodiment
Particular determination.
Furthermore it is possible to which above-mentioned parameter is normalized, calculated with facilitating, the disclosure is without limitation.
According to another embodiment of the present disclosure, it can determine that vehicle is in danger number as being used for from vehicle historical information
The third for assessing fraud assesses parameter, and above-mentioned the first assessment parameter determined and the second assessment parameter is combined to determine vehicle
Danger Claims Resolution whether there is fraud.Specifically, can establish another risk evaluation model, as shown in formula 3:
Q2=w1*q+w2*d+w3*N (formula 3)
Wherein, Q2 is the risk of fraud under this embodiment；Q is the first assessment parameter, i.e., above-mentioned to be based only upon vehicle driving
The risk of fraud that feature is determined；D is the second assessment parameter, i.e. phase between history driving feature vector and Accident Characteristic vector
Like degree；N is vehicle frequency of occurrence；W1, w2, w3 are preset weight.In addition, similarly, developer can by test come
W1, w2, w3 are fitted, the disclosure does not do actual value specifically limited.
No matter Q1 or Q2, the disclosure can also be arranged assessment threshold value and determine whether there is fraud.Specifically, needle
The case where being Q1 to risk of fraud, first threshold can be set, when Q1 is greater than the first threshold, can determine that vehicle insurance Claims Resolution is deposited
In fraud.In addition, the case where being Q2 for risk of fraud, can be set second threshold, when Q2 is greater than the second threshold,
It can determine that there are frauds for vehicle insurance Claims Resolution.Wherein, first threshold and second threshold can be manually set by developer, this
Disclosure does not do actual value specifically limited.
According to some embodiments of the present disclosure, determining vehicle insurance Claims Resolution there are in the case where fraud, server can
To send a warning message to vehicle insurance platform, it is the behavior of insurance fraud with the behavior for prompting this vehicle insurance of vehicle insurance platform to settle a claim, and then subtract
The loss of few vehicle insurance company.
The realization fraud in block chain network of the illustrative embodiments of the disclosure is determined below with reference to Fig. 2
System be illustrated.
With reference to Fig. 2, the system of the illustrative embodiments of the disclosure realizing fraud in block chain network and determining
May include block chain network building subsystem 210, data format definition subsystem 220, information of vehicles storage subsystem 230,
Fraud determines subsystem 240 and System Performance Analysis subsystem 250.
Specifically, block chain network building subsystem 210 for block chain node building, update and maintenance mechanism and
Building, update and the maintenance of block chain network.Such as can be using base, insurance company operating agency as minimum node, and it is based on one
The participations of a or multiple insurance pool/companies constructs block chain network.
Data format definition subsystem 220 can store letter involved in the disclosure according to data structure predetermined
Breath, to guarantee the high efficiency of information storage and information processing.Wherein, the information of vehicles of input can be for example including vehicle insurance contract item
Money information, vehicle traveling information, vehicle maintenance maintenance record information, driver history in violation of rules and regulations levy by record information, driver personal
Letter information, speed, the accident driven when the image before accident occurs, place where the accident occurred point, traffic injury time, accident occur are sent out
Raw reason etc..In addition, the information of input can also include help to further confirm that related vehicle insurance settle a claim the anti-picture cheated and/
Or the information such as video, the public-key cryptography of related personnel and signature.Output can be associated documents material involved in the disclosure
The risk of storage links, the anti-fraud of automatic identification vehicle insurance Claims Resolution (such as deliberately open in water, deliberately collide) etc. and to dependent part
Door issues prompting, public-key cryptography (account address) of relevant information visitor etc..
Specifically, data structure predetermined can be as shown in table 1:
Table 1
In the data structure shown in table 1, since information of vehicles material and other materials would generally include some images, text
The bigger information of data volumes such as shelves, therefore in order to improve storage efficiency and solve the problems, such as that block information is excessive, in the present invention
Embodiment in, the bigger material such as image can be stored in the form of a link within a block, this link value be exactly
Cryptographic Hash that material is encrypted by hash function, such as SHA1 etc., it is this that pointer chain is obtained by hash function
The mode connect can guarantee that content can not distort.And actual material can both be stored in the local storage device of block chain node
In, and can be stored in a manner of cloud storage.Meanwhile the high reliability in order to guarantee material storage, redundancy encoding can be used
Mode material is stored, for example using RS coding (i.e. Reed-Solomon codes is a kind of channel of forward error correction
Coding, effective to the multinomial as caused by correction over-sampling data) or LDPC (Low Density Parity Check
Code, low density parity check code) mode etc. of coding carries out redundancy encoding processing to material.
Information of vehicles storage subsystem 230 is for storing information of vehicles.Specifically, each information of vehicles can be by above-mentioned
The format of table 1 is uploaded in block chain network, so that information of vehicles storage subsystem 230 is stored.
Fraud determines that subsystem 240 can use above-mentioned fraud and determine that method determines whether vehicle insurance Claims Resolution deposits
In fraud, details are not described herein.
System Performance Analysis subsystem 250 can be used for assessing above-mentioned fraud and determine method, and then assess vehicle insurance reason
The timeliness, validity and accuracy of anti-fraud management are paid for, effectively realizes that vehicle insurance Claims Resolution is anti-in block chain network will pass through
Fraud management, to peomote effective popularization of the block chain technical application in terms of vehicle insurance settles a claim anti-fraud management.
It should be noted that although describing each step of method in the disclosure in the accompanying drawings with particular order, this is simultaneously
Undesired or hint must execute these steps in this particular order, or have to carry out the ability of step shown in whole
Realize desired result.Additional or alternative, it is convenient to omit multiple steps are merged into a step and executed by certain steps,
And/or a step is decomposed into execution of multiple steps etc..
Further, a kind of fraud determining device based on block chain is additionally provided in this example embodiment.
Fig. 3 diagrammatically illustrates the fraud determining device based on block chain of the illustrative embodiments of the disclosure
Block diagram.With reference to Fig. 3, the fraud determining device 3 based on block chain according to an exemplary embodiment of the present disclosure can be with
Including information storage module 31, characteristic determination module 33 and fraud judgment module 35.
Specifically, information storage module 31 can be used for through block chain network memory of driving accident information；Wherein, described
Driving accident information includes the image before driving accident occurs；Characteristic determination module 33 can be used for depositing the block chain network
Image before the driving accident of storage occurs is identified, to determine the vehicle operation characteristic before the generation of driving accident；Fraud
Judgment module 35 can be used for being determined vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.
According to the fraud determining device based on block chain of disclosure illustrative embodiments, on the one hand, based on this
Disclosed scheme can effectively determine out vehicle insurance Claims Resolution with the presence or absence of fraud.If there is fraud, then can incite somebody to action
Alarm is issued in time, to take measures, avoids losing；On the other hand, the disclosure in block chain network by storing
Accident information is driven, making it possible to guarantee by block chain network to drive accident information can not distort, and can be based on area
Block chain network stores to realize the traceable processing for driving accident information, and then can effectively ensure to drive the peace of accident information
It is complete shared；In another aspect, the disclosure can based on stored in block chain network sail accident information determine vehicle insurance Claims Resolution whether
There are frauds, peomote effective popularization of the block chain technology in terms of vehicle insurance settles a claim anti-fraud management.
According to an exemplary embodiment of the present disclosure, the block chain network is stored with vehicle historical information；Wherein, fraud row
It can be configured as judgment module 35 in conjunction with the vehicle historical information and the driving accident information, according to the vehicle
Travelling characteristic determines vehicle insurance Claims Resolution with the presence or absence of fraud.
According to an exemplary embodiment of the present disclosure, fraud judgment module 35 can be configured as according to the vehicle
Historical information determines that history is driven a vehicle feature vector；Accident Characteristic vector is determined according to the driving accident information；Described in determination
The similarity that history is driven a vehicle between feature vector and the Accident Characteristic vector；In conjunction with the similarity according to the vehicle driving
Feature determines vehicle insurance Claims Resolution with the presence or absence of fraud.
According to an exemplary embodiment of the present disclosure, fraud judgment module 35 can be configured as according to the vehicle
Travelling characteristic determines the first assessment parameter for assessing fraud；Using the similarity as being used to assess fraud
Second assessment parameter；Determine that vehicle insurance Claims Resolution is according to the weighted results of the first assessment parameter and the second assessment parameter
It is no that there are frauds.
According to an exemplary embodiment of the present disclosure, fraud judgment module 35 can be configured as according to the vehicle
Travelling characteristic determines the first assessment parameter for assessing fraud；Using the similarity as being used to assess fraud
Second assessment parameter；Determine that vehicle is in danger number as the third for assessing fraud from the vehicle historical information
Assess parameter；Weighted results according to the first assessment parameter, the second assessment parameter and third assessment parameter are true
Vehicle insurance Claims Resolution is determined with the presence or absence of fraud.
According to an exemplary embodiment of the present disclosure, with reference to Fig. 4, information storage module 31 may include image storage unit
401。
Specifically, image storage unit 401 can be used for the automobile data recorder and/or road monitoring camera by vehicle
The image before driving accident occurs is obtained, and the image before driving accident generation is stored to the block chain network.
According to an exemplary embodiment of the present disclosure, with reference to Fig. 5, fraud determining device 5 is determined compared to fraud
Device 3 can also include alarm sending module 51.
Specifically, if alarm sending module 51 can be used for vehicle insurance Claims Resolution, there are frauds, send out to vehicle insurance platform
Send warning information.
Since each functional module and the above method of the program analysis of running performance device of embodiment of the present invention are invented
It is identical in embodiment, therefore details are not described herein.
In an exemplary embodiment of the disclosure, a kind of computer readable storage medium is additionally provided, energy is stored thereon with
Enough realize the program product of this specification above method.In some possible embodiments, various aspects of the invention may be used also
In the form of being embodied as a kind of program product comprising program code, when described program product is run on the terminal device, institute
Program code is stated for executing the terminal device described in above-mentioned " illustrative methods " part of this specification according to this hair
The step of bright various illustrative embodiments.
Refering to what is shown in Fig. 6, describing the program product for realizing the above method of embodiment according to the present invention
600, can using portable compact disc read only memory (CD-ROM) and including program code, and can in terminal device,
Such as it is run on PC.However, program product of the invention is without being limited thereto, in this document, readable storage medium storing program for executing can be with
To be any include or the tangible medium of storage program, the program can be commanded execution system, device or device use or
It is in connection.
Described program product can be using any combination of one or more readable mediums.Readable medium can be readable letter
Number medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example can be but be not limited to electricity, magnetic, optical, electromagnetic, infrared ray or
System, device or the device of semiconductor, or any above combination.The more specific example of readable storage medium storing program for executing is (non exhaustive
List) include: electrical connection with one or more conducting wires, portable disc, hard disk, random access memory (RAM), read-only
Memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read only memory
(CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
Computer-readable signal media may include in a base band or as carrier wave a part propagate data-signal,
In carry readable program code.The data-signal of this propagation can take various forms, including but not limited to electromagnetic signal,
Optical signal or above-mentioned any appropriate combination.Readable signal medium can also be any readable Jie other than readable storage medium storing program for executing
Matter, the readable medium can send, propagate or transmit for by instruction execution system, device or device use or and its
The program of combined use.
The program code for including on readable medium can transmit with any suitable medium, including but not limited to wirelessly, have
Line, optical cable, RF etc. or above-mentioned any appropriate combination.
The program for executing operation of the present invention can be write with any combination of one or more programming languages
Code, described program design language include object oriented program language-Java, C++ etc., further include conventional
Procedural programming language-such as " C " language or similar programming language.Program code can be fully in user
It calculates and executes in equipment, partly executes on a user device, being executed as an independent software package, partially in user's calculating
Upper side point is executed on a remote computing or is executed in remote computing device or server completely.It is being related to far
Journey calculates in the situation of equipment, and remote computing device can pass through the network of any kind, including local area network (LAN) or wide area network
(WAN), it is connected to user calculating equipment, or, it may be connected to external computing device (such as utilize ISP
To be connected by internet).
In an exemplary embodiment of the disclosure, a kind of electronic equipment that can be realized the above method is additionally provided.
Person of ordinary skill in the field it is understood that various aspects of the invention can be implemented as system, method or
Program product.Therefore, various aspects of the invention can be embodied in the following forms, it may be assumed that complete hardware embodiment, complete
The embodiment combined in terms of full Software Implementation (including firmware, microcode etc.) or hardware and software, can unite here
Referred to as circuit, " module " or " system ".
The electronic equipment 700 of this embodiment according to the present invention is described referring to Fig. 7.The electronics that Fig. 7 is shown
Equipment 700 is only an example, should not function to the embodiment of the present invention and use scope bring any restrictions.
As shown in fig. 7, electronic equipment 700 is showed in the form of universal computing device.The component of electronic equipment 700 can wrap
It includes but is not limited to: at least one above-mentioned processing unit 710, at least one above-mentioned storage unit 720, the different system components of connection
The bus 730 of (including storage unit 720 and processing unit 710), display unit 740.
Wherein, the storage unit is stored with program code, and said program code can be held by the processing unit 710
Row, so that various according to the present invention described in the execution of the processing unit 710 above-mentioned " illustrative methods " part of this specification
The step of illustrative embodiments.For example, the processing unit 710 can execute step S12 as shown in fig. 1: passing through area
Block chain network memory of driving accident information；Wherein, the accident information that drives includes the image before driving accident occurs；Step
S14: the image before the driving accident of block chain network storage occurs identifies, before determining that driving accident occurs
Vehicle operation characteristic；Step S16: determine vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.
Storage unit 720 may include the readable medium of volatile memory cell form, such as Random Access Storage Unit
(RAM) 7201 and/or cache memory unit 7202, it can further include read-only memory unit (ROM) 7203.
Storage unit 720 can also include program/utility with one group of (at least one) program module 7205
7204, such program module 7205 includes but is not limited to: operating system, one or more application program, other program moulds
It may include the realization of network environment in block and program data, each of these examples or certain combination.
Bus 730 can be to indicate one of a few class bus structures or a variety of, including storage unit bus or storage
Cell controller, peripheral bus, graphics acceleration port, processing unit use any bus structures in a variety of bus structures
Local bus.
Electronic equipment 700 can also be with one or more external equipments 800 (such as keyboard, sensing equipment, bluetooth equipment
Deng) communication, can also be enabled a user to one or more equipment interact with the electronic equipment 700 communicate, and/or with make
Any equipment (such as the router, modulation /demodulation that the electronic equipment 700 can be communicated with one or more of the other calculating equipment
Device etc.) communication.This communication can be carried out by input/output (I/O) interface 750.Also, electronic equipment 700 can be with
By network adapter 760 and one or more network (such as local area network (LAN), wide area network (WAN) and/or public network,
Such as internet) communication.As shown, network adapter 760 is communicated by bus 730 with other modules of electronic equipment 700.
It should be understood that although not shown in the drawings, other hardware and/or software module can not used in conjunction with electronic equipment 700, including but not
Be limited to: microcode, device driver, redundant processing unit, external disk drive array, RAID system, tape drive and
Data backup storage system etc..
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example described herein is implemented
Mode can also be realized by software realization in such a way that software is in conjunction with necessary hardware.Therefore, according to the disclosure
The technical solution of embodiment can be embodied in the form of software products, which can store non-volatile at one
Property storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in or network on, including some instructions are so that a calculating
Equipment (can be personal computer, server, terminal installation or network equipment etc.) is executed according to disclosure embodiment
Method.
In addition, above-mentioned attached drawing is only the schematic theory of processing included by method according to an exemplary embodiment of the present invention
It is bright, rather than limit purpose.It can be readily appreciated that the time that above-mentioned processing shown in the drawings did not indicated or limited these processing is suitable
Sequence.In addition, be also easy to understand, these processing, which can be, for example either synchronously or asynchronously to be executed in multiple modules.
It should be noted that although being referred to several modules or list for acting the equipment executed in the above detailed description
Member, but this division is not enforceable.In fact, according to embodiment of the present disclosure, it is above-described two or more
Module or the feature and function of unit can embody in a module or unit.Conversely, an above-described mould
The feature and function of block or unit can be to be embodied by multiple modules or unit with further division.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to its of the disclosure
His embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Adaptive change follow the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure or
Conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by claim
It points out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by the attached claims.
Claims (10)
1. a kind of fraud based on block chain determines method, which is characterized in that the fraud determines that method includes:
Pass through block chain network memory of driving accident information；Wherein, the driving accident information includes before driving accident occurs
Image；
Image before the driving accident of block chain network storage occurs identifies, before determining that driving accident occurs
Vehicle operation characteristic；
Determine vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.
2. the fraud according to claim 1 based on block chain determines method, which is characterized in that the block link network
Network is stored with vehicle historical information；Wherein, determine vehicle insurance Claims Resolution with the presence or absence of fraud packet according to the vehicle operation characteristic
It includes:
In conjunction with the vehicle historical information and the driving accident information, determine that vehicle insurance Claims Resolution is according to the vehicle operation characteristic
It is no that there are frauds.
3. the fraud according to claim 2 based on block chain determines method, which is characterized in that in conjunction with the vehicle
Historical information and the driving accident information determine vehicle insurance Claims Resolution with the presence or absence of fraud packet according to the vehicle operation characteristic
It includes:
History driving feature vector is determined according to the vehicle historical information；
Accident Characteristic vector is determined according to the driving accident information；
Determine the similarity between the history driving feature vector and the Accident Characteristic vector；
Determine vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic in conjunction with the similarity.
4. the fraud according to claim 3 based on block chain determines method, which is characterized in that in conjunction with described similar
Degree determines that vehicle insurance Claims Resolution includes: with the presence or absence of fraud according to the vehicle operation characteristic
The first assessment parameter for assessing fraud is determined according to the vehicle operation characteristic；
Using the similarity as the second assessment parameter for being used to assess fraud；
Determine vehicle insurance Claims Resolution with the presence or absence of fraud according to the weighted results of the first assessment parameter and the second assessment parameter
Behavior.
5. the fraud according to claim 3 based on block chain determines method, which is characterized in that in conjunction with described similar
Degree determines that vehicle insurance Claims Resolution includes: with the presence or absence of fraud according to the vehicle operation characteristic
The first assessment parameter for assessing fraud is determined according to the vehicle operation characteristic；
Using the similarity as the second assessment parameter for being used to assess fraud；
Determine that vehicle is in danger number as the third for assessing fraud and assesses parameter from the vehicle historical information；
Vehicle insurance is determined according to the weighted results of the first assessment parameter, the second assessment parameter and third assessment parameter
Claims Resolution whether there is fraud.
6. the fraud according to claim 1 based on block chain determines method, which is characterized in that pass through block link network
Network memory of driving accident information includes:
The image before driving accident occurs is obtained by the automobile data recorder and/or road monitoring camera of vehicle, and will be described
Image before driving accident occurs is stored to the block chain network.
7. the fraud according to any one of claim 1 to 6 based on block chain determines method, which is characterized in that
The fraud determines method further include:
If there are frauds for vehicle insurance Claims Resolution, send a warning message to vehicle insurance platform.
8. a kind of fraud determining device based on block chain, which is characterized in that the fraud determining device includes:
Information storage module, for passing through block chain network memory of driving accident information；Wherein, the driving accident information includes
Image before the generation of driving accident；
Characteristic determination module, the image before the driving accident for storing to the block chain network occurs identifies, with true
Surely the vehicle operation characteristic before accident occurs is driven；
Fraud judgment module, for determining vehicle insurance Claims Resolution with the presence or absence of fraud according to the vehicle operation characteristic.
9. a kind of storage medium, is stored thereon with computer program, which is characterized in that the computer program is executed by processor
Fraud described in Shi Shixian any one of claims 1 to 7 based on block chain determines method.
10. a kind of electronic equipment characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to come described in any one of perform claim requirement 1 to 7 via the execution executable instruction
The fraud based on block chain determine method.
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| CN201811504282.3A CN109658260A (en) | 2018-12-10 | 2018-12-10 | Method and device, medium and electronic equipment are determined based on the fraud of block chain |
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|---|---|---|---|
| CN201811504282.3A CN109658260A (en) | 2018-12-10 | 2018-12-10 | Method and device, medium and electronic equipment are determined based on the fraud of block chain |
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