CN108777686A - A kind of recognition methods and system for the transaction of block chain dust - Google Patents
A kind of recognition methods and system for the transaction of block chain dust Download PDFInfo
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- CN108777686A CN108777686A CN201810568702.8A CN201810568702A CN108777686A CN 108777686 A CN108777686 A CN 108777686A CN 201810568702 A CN201810568702 A CN 201810568702A CN 108777686 A CN108777686 A CN 108777686A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/04—Payment circuits
- G06Q20/06—Private payment circuits, e.g. involving electronic currency used among participants of a common payment scheme
- G06Q20/065—Private payment circuits, e.g. involving electronic currency used among participants of a common payment scheme using e-cash
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/382—Payment protocols; Details thereof insuring higher security of transaction
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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Abstract
The present invention disclose it is a kind of for block chain dust transaction recognition methods and system.The recognition methods includes：According to historical trading rule in block chain, transaction feature is obtained；According to the block information and Transaction Information in the block chain, block chain Trading Model is established；According to the Trading Model, segment model when creation analysis；According to segment model when the transaction analysis, data correlation degree parser model is built；According to the data correlation degree parser model and the transaction feature, judge whether current transaction is dust transaction.Method or system using the present invention, it can efficiently identify and take precautions against dust transaction attack, to reduce the influence that arm's length dealing is brought when dust is attacked in block chain, shortens processing time of the transaction in block chain, increase the trading processing rate and treating capacity of block chain.
Description
Technical field
The present invention relates to dust transaction identification fields, more particularly to a kind of recognition methods for the transaction of block chain dust
And system.
Background technology
Block chain is divided into publicly-owned chain, alliance's chain, privately owned chain in application range；The most typically application of publicly-owned chain is exactly to compare
Special coin, in the world in addition to the country that some countries forbid bit coin to dig mine and transaction, the computer of every other region
As long as be mounted with that the client of bitcoin softwares can easily access block chain network, and participate in bit coin digging mine and
Transaction.Its proof of work common recognition algorithm (POW) is to ensure each internodal data unanimously and synchronous important means, the friendship of bit coin
After the distributed confirmation for easily obtaining the most of node for participating in digging mine in the whole network, transaction just success.This is resulted in block chain
Trade confirmation need longer time, trade fair delay.Its merchandise average acknowledging time from 27.24 minutes of 2016 to
133.24 minutes in 2017, then by 959.38 minutes of 2018 (cut-off 2 months 2018 No. 2), the trade confirmation time was just
It is being continuously increased, as the dummy payments tool in global range, this is differed with another whole world means of payment Visa
It is very remote, about 24000 business can be handled its each second of VisaNet, 1,500,000,000 transactions can be handled daily.While block chain
Handling capacity of merchandising is also smaller, and the transaction of bit coin is packaged by byte, each transaction data minimum is 546 bytes,
Before bit coin bifurcated, block only has 1MB or so, each block that 500 transactions about can be confirmed, after its bifurcated,
Block is increased to 2MB, increases block capacity to increase the quantity of single block trade confirmation.This far can not adapt to a kind of whole world
Change the transactions demand of ideal money.
Moreover, dust occurs in block chain hands over pregnable possibility also increasing, and dust is attacked serious shadow
Ring the arm's length dealing of block chain.When dust attack occurring in block chain, mainly there is following harm：
1. increasing the acknowledging time of arm's length dealing：With increasing for transaction, stores in block chain network and largely wait for
The transaction of confirmation, and the processing capacity of block chain is limited, the acknowledging time that can thus increase licit traffic in block chain increases,
Arm's length dealing cannot slowly confirm.
2. occupying unnecessary block space：Block chain is as distributed network database, each block, each friendship
It easily is all required for being stored in the storage of each miner after validation, it is empty to occupy more storages for a large amount of dust transaction
Between.
3. a pair network results in blockage：Block chain network operates in p2p networks, under normal trading situation, each
The miner for participating in block chain needs with 8 neighbouring nodes connect entirely to carry out information exchange, and transaction is obtaining some area
Block can be propagated after confirming in p2p networks, and the frequency that these information are forwarded between each node is higher.And dust attack is occurring
When, a large amount of dust transaction data package carries out mad propagation in p2p networks, and larger burden is carried out to Netowrk tape, is seriously affected
The propagation of arm's length dealing in a network.
For the smaller feature of the transaction limit merchandised involved in dust attack, in bit coin core client in 0.8.2
Increase txFees fields in version, for limiting the acknowledging time of transaction, increase the availability of system, but the setting of the field compared with
For fixed value, it can not change with the upgrading of bit coin client, account of the history that can not be according to transaction and practical feelings
Condition carries out dynamic automatically adjustment, cannot effectively adapt to the business development needs of block chain.
For the relatively low feature of tranaction costs involved in dust attack, bit coin core client is handed over when being traded
Easy expense can be manually entered by transaction initiator.Transaction initiator can fill in higher tranaction costs, can also be friendship
Easy expense extends this as 0.How much block chain client is ranked up after receiving transaction according to tranaction costs, transaction procedure take compared with
More transaction meeting priority processing, the less transaction of tranaction costs in processing are then arranged in trading pit always, these low transaction
If the transaction of expense cannot be handled timely, and often it is long when be trapped in normal trading pit, trading pit can be occupied
Most of capacity and space, cause normally merchandise cannot or seldom enter trading pit, influence normally to merchandise.Therefore bit
The existing tranaction costs treatment mechanism of coin cannot carry out the effective early warning and prevention attacked dust.
The dust number of transaction that occurs big feature when simultaneously for dust attack, this with conventional security attack means such as
Denial of Service (DOS) attacks, Distributed Denial-of-Service (DDoS) attacks are similar.But safety
Field mainly uses fire wall, router, intrusion detection device for the risk prevention instruments of traditional dos attack, DDOS attack
Deng filtering the IP network level for being all based on transmission packet by the filtering of such as source address, destination address filtering, routing iinformation
It is identified and filters, and dust attack belongs to block chain application layer data information attack, is to belong to normal net in transport layer
Network data packet, traditional DDOS safeguard procedures, which can not attack the dust for being happened at application, effectively to be judged.
It can be seen that existing correlation technique or measure can not effectively take precautions against the dust attack for block chain.
Invention content
The object of the present invention is to provide a kind of recognition methods for the transaction of block chain dust and systems, to effectively know
It is not attacked with strick precaution dust transaction.
To achieve the above object, the present invention provides following schemes：
A kind of recognition methods for the transaction of block chain dust, the recognition methods include：
According to historical trading rule in block chain, transaction feature is obtained；
According to the block information and Transaction Information in the block chain, block chain Trading Model is established；
According to the Trading Model, segment model when creation analysis；
According to segment model when the transaction analysis, data correlation degree parser model is built；
According to the data correlation degree parser model and the transaction feature, judge whether current transaction is that dust is handed over
Easily.
Optionally, described according to the Trading Model, segment model when creation analysis specifically includes：
Data conversion is carried out to historical trading according to the Trading Model, the data in block chain are resolved into pattern number
According to, according to the transaction time of origin of the model data, segment model when creation analysis.
Optionally, described that data correlation degree parser model is built according to segment model when the transaction analysis, it is specific to wrap
It includes：
According to the transaction that each transaction analysis period dimension is occurred in segment model when the transaction analysis, to turnover
Degree, tranaction costs, dust number of transaction carry out periodogram analysis, and probability distribution or supporting vector are used to the analysis result
The method of machine or neural network analysis sets up data correlation degree parser model.
Optionally, the method further includes：
According to the data correlation degree parser model and the dust transaction feature, judge whether current transaction is powder
Dirt is merchandised, and the first judging result is obtained；
If first judging result indicates that current transaction is dust transaction, the dust transaction in dust trading pit is judged
Whether it is more than given threshold, obtains the second judging result；
If first judging result indicates that current transaction is not dust transaction, current transaction is put into arm's length dealing pond
It is traded；
If second judging result indicates that the dust transaction in dust trading pit is more than given threshold, current hand over is abandoned
Easily；
If second judging result indicates that the dust transaction in dust trading pit is less than given threshold, will currently hand over
It is easily put into dust trading pit, and judges whether the dust number of transaction in dust trading pit reaches processing threshold value, obtain third
Judging result；
It, will be described if the third judging result indicates that the dust number of transaction in dust trading pit reaches processing threshold value
Dust transaction is put into arm's length dealing pond and is traded；
If the third judging result indicates that the dust number of transaction in dust trading pit not up to handles threshold value, continue
Dust transaction in monitoring dust trading pit is until the dust number of transaction in dust trading pit reaches processing threshold value.
To achieve the above object, the present invention also provides following schemes：
A kind of identifying system for the transaction of block chain dust, the identifying system include：
Transaction feature acquisition module, for according to historical trading rule in block chain, obtaining transaction feature；
Trading Model acquisition module, for establishing block chain Trading Model；
Segment model acquisition module when analysis, for according to the Trading Model, segment model when creation analysis；
Parser model acquisition module, for according to segment model when the transaction analysis, structure data correlation degree analysis
Algorithm model；
Dust transaction judgment module, it is special for being merchandised according to the data correlation degree parser model and the dust
Sign judges whether current transaction is dust transaction.
Optionally, segment model acquisition module when the analysis, specifically includes：
Resolution unit, for carrying out data conversion to historical trading according to the Trading Model, by the data in block chain
Model data is resolved to, the transaction time of origin of model data is obtained；
Construction unit, for according to the transaction time of origin of the model data, segment model when creation analysis.
Optionally, the parser model acquisition module, specifically includes：
Analytic unit, for according to the friendship that each transaction analysis period dimension is occurred in segment model when the transaction analysis
Easily, periodogram analysis is carried out to transaction limit, tranaction costs, dust number of transaction；
Associative cell, for according to the analysis result using probability distribution or support vector machines or neural network analysis
Method sets up data correlation degree parser model.
Optionally, the system also includes：
First judging unit judges to work as according to the data correlation degree parser model and the dust transaction feature
Whether preceding transaction is dust transaction, obtains the first judging result；
Second judgment unit judges dust if indicating that current transaction is dust transaction for first judging result
Whether the dust transaction in trading pit is more than given threshold, obtains the second judging result；
First transaction unit will be current if indicating that current transaction is not dust transaction for first judging result
Transaction is put into arm's length dealing pond and is traded；
Discarding unit, if indicating that the dust transaction in dust trading pit is more than setting threshold for second judging result
Value then abandons current transaction；
Third judging unit is set if indicating that the dust transaction in dust trading pit is less than for second judging result
Determine threshold value, then current transaction is put into dust trading pit, and judge whether the dust number of transaction in dust trading pit reaches
Threshold value is handled, third judging result is obtained；
Second transaction unit, if indicating that the dust number of transaction in dust trading pit reaches for the third judging result
Threshold value is handled, then dust transaction is put into arm's length dealing pond is traded；
Monitoring unit, if indicating that the dust number of transaction in dust trading pit is not up to located for the third judging result
Threshold value is managed, then continues to monitor the dust transaction in dust trading pit until the dust number of transaction in dust trading pit reaches processing
Threshold value.
According to specific embodiment provided by the invention, the invention discloses following technique effects：
The present invention disclose it is a kind of for block chain dust transaction recognition methods and system.The recognition methods includes：It obtains
Take dust transaction feature；Establish block chain Trading Model；According to the Trading Model, segment model when creation analysis；According to described
Segment model when transaction analysis builds data correlation degree parser model；According to the data correlation degree parser model and
The dust transaction feature judges whether current transaction is dust transaction.Method or system using the present invention, can be effectively
Identification and strick precaution dust transaction attack are shortened and are handed over to reduce the influence that arm's length dealing is brought when dust is attacked in block chain
Processing time easily in block chain increases the trading processing rate and treating capacity of block chain.
Description of the drawings
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the present invention
Example, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the recognition methods flow chart that the embodiment of the present invention is directed to the transaction of block chain dust；
Fig. 2 is the identifying system structure chart that the embodiment of the present invention is directed to the transaction of block chain dust.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of recognition methods for the transaction of block chain dust and systems, to effectively know
It is not attacked with strick precaution dust transaction.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, below in conjunction with the accompanying drawings and specific real
Applying mode, the present invention is described in further detail.
Fig. 1 is the recognition methods flow chart that the embodiment of the present invention is directed to the transaction of block chain dust.As shown in Figure 1, a kind of needle
Recognition methods to the transaction of block chain dust, the recognition methods include：
Step 101：According to historical trading rule in block chain, transaction feature is obtained；
Step 102：According to the block information and Transaction Information in the block chain, block chain Trading Model is established；
Step 103：According to the Trading Model, segment model when creation analysis, specifically, according to the Trading Model to going through
History transaction carries out data conversion, and the data in block chain are resolved to model data, is occurred according to the transaction of the model data
Time, segment model when creation analysis；
Step 104：According to segment model when the transaction analysis, data correlation degree parser model is built, specifically, root
According to the transaction that each transaction analysis period dimension is occurred in segment model when the transaction analysis, to transaction limit, tranaction costs,
Dust number of transaction carries out periodogram analysis, to the analysis result using probability distribution or support vector machines or neural network
The method of analysis sets up data correlation degree parser model；
Step 105：According to the data correlation degree parser model and the transaction feature, whether current transaction is judged
It merchandises for dust.
The present invention disclose it is a kind of for block chain dust transaction recognition methods and system.The recognition methods includes：It obtains
Take transaction feature；Establish block chain Trading Model；According to the Trading Model, segment model when creation analysis；According to the transaction
Segment model when analysis builds data correlation degree parser model；According to the data correlation degree parser model and described
Transaction feature judges whether current transaction is dust transaction.Method using the present invention can efficiently identify and take precautions against dust
Transaction attack shortens transaction in block chain to reduce the influence that arm's length dealing is brought when dust is attacked in block chain
Processing time increases the trading processing rate and treating capacity of block chain.
The method further includes：
According to the data correlation degree parser model, judge whether current transaction is dust transaction, obtains first and sentences
Disconnected result；
If first judging result indicates that current transaction is dust transaction, the dust transaction in dust trading pit is judged
Whether it is more than given threshold, obtains the second judging result；
If first judging result indicates that current transaction is not dust transaction, current transaction is put into arm's length dealing pond
It is traded；
If second judging result indicates that the dust transaction in dust trading pit is more than given threshold, current hand over is abandoned
Easily；
If second judging result indicates that the dust transaction in dust trading pit is less than given threshold, will currently hand over
It is easily put into dust trading pit, and judges whether the dust number of transaction in dust trading pit reaches processing threshold value, obtain third
Judging result；
It, will be described if the third judging result indicates that the dust number of transaction in dust trading pit reaches processing threshold value
Dust transaction is put into arm's length dealing pond and is traded；
If the third judging result indicates that the dust number of transaction in dust trading pit not up to handles threshold value, continue
Dust transaction in monitoring dust trading pit is until the dust number of transaction in dust trading pit reaches processing threshold value.
Fig. 2 is the identifying system structure chart that the embodiment of the present invention is directed to the transaction of block chain dust.As shown in Fig. 2, a kind of needle
To the identifying system of block chain dust transaction, the identifying system includes：
Transaction feature acquisition module 201, for according to historical trading rule in block chain, obtaining transaction feature；
Trading Model acquisition module 202, for establishing block chain Trading Model；
Segment model acquisition module 203 when analysis, for according to the Trading Model, segment model when creation analysis；
Parser model acquisition module 204, for according to segment model when the transaction analysis, structure data correlation degree point
Analyse algorithm model；
Dust transaction judgment module 205, for being merchandised according to the data correlation degree parser model and the dust
Feature judges whether current transaction is dust transaction.
Segment model acquisition module 203, specifically includes when the analysis：
Resolution unit, for carrying out data conversion to historical trading according to the Trading Model, by the data in block chain
Model data is resolved to, the transaction time of origin of model data is obtained；
Construction unit, for according to the transaction time of origin of the model data, segment model when creation analysis.
The parser model acquisition module 204, specifically includes：
Analytic unit, for according to the friendship that each transaction analysis period dimension is occurred in segment model when the transaction analysis
Easily, periodogram analysis is carried out to transaction limit, tranaction costs, dust number of transaction；
Associative cell, for according to the analysis result using probability distribution or support vector machines or neural network analysis
Method sets up data correlation degree parser model.
The system also includes：
First judging unit judges whether current transaction is that dust is handed over according to the data correlation degree parser model
Easily, the first judging result is obtained；
Second judgment unit judges dust if indicating that current transaction is dust transaction for first judging result
Whether the dust transaction in trading pit is more than given threshold, obtains the second judging result；
First transaction unit will be current if indicating that current transaction is not dust transaction for first judging result
Transaction is put into arm's length dealing pond and is traded；
Discarding unit, if indicating that the dust transaction in dust trading pit is more than setting threshold for second judging result
Value then abandons current transaction；
Third judging unit is set if indicating that the dust transaction in dust trading pit is less than for second judging result
Determine threshold value, then current transaction is put into dust trading pit, and judge whether the dust number of transaction in dust trading pit reaches
Threshold value is handled, third judging result is obtained；
Second transaction unit, if indicating that the dust number of transaction in dust trading pit reaches for the third judging result
Threshold value is handled, then dust transaction is put into arm's length dealing pond is traded；
Monitoring unit, if indicating that the dust number of transaction in dust trading pit is not up to located for the third judging result
Threshold value is managed, then continues to monitor the dust transaction in dust trading pit until the dust number of transaction in dust trading pit reaches processing
Threshold value.
The present invention use based on the transaction in existing block chain is analyzed and study obtain dust attack recognition calculate
Method, and by increased newly in block chain dust attack trading pit and dust attack trading pit to arm's length dealing pond transaction interpreter
System, while it is big to increase transaction limit, tranaction costs, dust attack recognition probability value, dust attack trading pit in this process
Small, dust attack trading pit recognizer and treatment mechanism constantly adjust to threshold values such as arm's length dealing pond conversion values and
It adapts to, dust transaction attack can be efficiently identified and take precautions against by reaching, to reduce in block chain arm's length dealing when dust is attacked
The influence brought shortens processing time of the transaction in block chain, increases the trading processing rate and treating capacity of block chain.
Framework is constant, and interface is unified, and plug type update, the existing block arrived involved in the present invention can be carried out to algorithm
Chain transaction data learning algorithm and dust recognizer can pass through pluggable software module interface mentality of designing, you can
To use Bayesian model, the data learning algorithms such as support vector machines, cluster, neural network can also be used to be learnt, it can
Easily according to the learning law of machine learning circle, to be updated and replace to recognizer, it is constant to reach a frame, calculates
Method function module can constantly be adjusted according to using effect.
Existing block chain framework is improved, increases dust trading pit and dust trading pit in the present invention to arm's length dealing
The treatment mechanism in pond, the impact brought that can effectively merchandise to dust is into row buffering and avoids.
Flexibly threshold values setting rule, the related threshold involved in the present invention can carry out certainly according to the continuous study of transaction
Dynamic adjustment, these parameters not only can also can automatically be learnt according to transaction, can also be subject in block chain outer
Portion's environment can better adapt to area if the problems such as policy, security risk is manually adjusted by the combination of both means
Block chain plays good effect to which dust attack is identified and taken precautions against for block chain.
By to the present invention relates to recognizer threshold values etc. show that proposed by the invention is directed to by analysis of experiments
The identification of block chain dust attack and prevention method can efficiently identify and take precautions against dust attack, be transported to the high efficiency of block chain
Row brings good effect.
The present invention is with the following functions：
1) learning algorithm management：Mainly to the historical trading rule the algorithm such as bayesian algorithm, branch skill that are related to of study to
Amount machine scheduling algorithm is managed, and passes through the shape for carrying out modeling analysis to historical trading, forming block chain dust transaction identification algorithm
At；
2) threshold values management：To the present invention relates to algorithm for example dust transaction turnover, dust tranaction costs, dust attack
Identification probability value, dust attack trading pit size, dust attack trading pit are managed to threshold values such as arm's length dealing pond conversion values,
These threshold values can be automatically adjusted by learning algorithm in management process, it can also be according to external environment, such as policy
When unpredictable situation of merchandising caused by risk, laws and regulations, technological innovation etc., by being set manually to these threshold values manually
It sets；Threshold values management is by combining threshold values modified module of merchandising to be adjusted the core threshold values of dust attack recognition algorithm；
3) transaction verification：Transaction in block chain is verified, judge whether occur dust attack, to judging result into
Row is handled respectively；
4) dust trading pit management：Dust trading pit in block chain is managed, if attacked in dust, dust is handed over
When Yi Chi is not up to the threshold values set, dust can be merchandised and first be put into dust trading pit, otherwise dust transaction is abandoned
Processing；
5) transaction cell monitoring：Pond (UTXO) is confirmed to the transaction of block chain to be monitored, judges the transaction in trading pit
Whether the threshold values of setting is reached, it is without any processing if the transaction in trading pit is on the threshold values of setting, continue to handing over
Yi Chi is managed；And if the transaction in trading pit under the threshold values of setting, triggers dust trading pit and merchandises to UTXO
Pond is traded conversion, i.e., the transaction in dust trading pit is moved into UTXO trading pits is normally handled；Transaction cell monitoring
Function is finger daemon in realization, is constantly periodically monitored to trading pit；
6) transaction study：The present invention relates to software systems initialized when, transaction learning functionality module will be right
The All Activity being had occurred and that in block chain carries out data rule study according to Trading Model, exchange hour segment model etc.；And
After learning for the first time to historical trading data, transaction study module can be to the transaction that or is just occurring in block chain
It practises, feedback modification is carried out to algorithm and threshold values by learning dynamics, reach for block chain dust attack self-adapting estimation and prevent
Model core mechanism.
Each embodiment is described by the way of progressive in this specification, the highlights of each of the examples are with other
The difference of embodiment, just to refer each other for identical similar portion between each embodiment.For system disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so description is fairly simple, related place is said referring to method part
It is bright.
Principle and implementation of the present invention are described for specific case used herein, and above example is said
The bright method and its core concept for being merely used to help understand the present invention；Meanwhile for those of ordinary skill in the art, foundation
The thought of the present invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (8)
1. a kind of recognition methods for the transaction of block chain dust, which is characterized in that the recognition methods includes：
According to historical trading rule in block chain, transaction feature is obtained；
According to the block information and Transaction Information in the block chain, block chain Trading Model is established；
According to the Trading Model, segment model when creation analysis；
According to segment model when the transaction analysis, data correlation degree parser model is built；
According to the data correlation degree parser model and the transaction feature, judge whether current transaction is dust transaction.
2. the recognition methods according to claim 1 for the transaction of block chain dust, which is characterized in that described in the basis
Trading Model, segment model when creation analysis, specifically includes：
Data conversion is carried out to historical trading according to the Trading Model, the data in block chain are resolved into model data, root
According to the transaction time of origin of the model data, segment model when creation analysis.
3. the recognition methods according to claim 1 for the transaction of block chain dust, which is characterized in that described in the basis
Segment model when transaction analysis builds data correlation degree parser model, specifically includes：
According to the transaction that each transaction analysis period dimension is occurred in segment model when the transaction analysis, to transaction limit, hand over
Easy expense, dust number of transaction carry out periodogram analysis, to the analysis result using probability distribution or support vector machines or
The method of neural network analysis sets up data correlation degree parser model.
4. the recognition methods according to claim 1 for the transaction of block chain dust, which is characterized in that the method is also wrapped
It includes：
According to the data correlation degree parser model and the dust transaction feature, judge whether current transaction is that dust is handed over
Easily, the first judging result is obtained；
If first judging result indicates that current transaction is dust transaction, judge whether the dust in dust trading pit merchandises
More than given threshold, the second judging result is obtained；
If first judging result indicates that current transaction is not dust transaction, current transaction, which is put into arm's length dealing pond, to be carried out
Transaction；
If second judging result indicates that the dust transaction in dust trading pit is more than given threshold, current transaction is abandoned；
If second judging result indicates that the dust transaction in dust trading pit is less than given threshold, current transaction is put
Enter in dust trading pit, and judge whether the dust number of transaction in dust trading pit reaches processing threshold value, obtains third and judge
As a result；
If the third judging result indicates that the dust number of transaction in dust trading pit reaches processing threshold value, by the dust
Transaction is put into arm's length dealing pond and is traded；
If the third judging result indicates that the dust number of transaction in dust trading pit not up to handles threshold value, continue to monitor
Dust transaction in dust trading pit is until the dust number of transaction in dust trading pit reaches processing threshold value.
5. a kind of identifying system for the transaction of block chain dust, which is characterized in that the identifying system includes：
Transaction feature acquisition module, for according to historical trading rule in block chain, obtaining transaction feature；
Trading Model acquisition module, for establishing block chain Trading Model；
Segment model acquisition module when analysis, for according to the Trading Model, segment model when creation analysis；
Parser model acquisition module, for according to segment model when the transaction analysis, building data correlation degree parser
Model；
Dust transaction judgment module, for according to the data correlation degree parser model and the dust transaction feature, sentencing
Whether disconnected current transaction is dust transaction.
6. the identifying system according to claim 5 for the transaction of block chain dust, which is characterized in that the analysis period
Model acquisition module, specifically includes：
Resolution unit parses the data in block chain for carrying out data conversion to historical trading according to the Trading Model
For model data, the transaction time of origin of model data is obtained；
Construction unit, for according to the transaction time of origin of the model data, segment model when creation analysis.
7. the identifying system according to claim 5 for the transaction of block chain dust, which is characterized in that the parser
Model acquisition module, specifically includes：
Analytic unit, for according to the transaction that each transaction analysis period dimension is occurred in segment model when the transaction analysis,
Periodogram analysis is carried out to transaction limit, tranaction costs, dust number of transaction；
Associative cell, the method for using probability distribution or support vector machines or neural network analysis according to the analysis result
Set up data correlation degree parser model.
8. the identifying system according to claim 5 for the transaction of block chain dust, which is characterized in that the system is also wrapped
It includes：
First judging unit judges current hand over according to the data correlation degree parser model and the dust transaction feature
Whether it is easily dust transaction, obtains the first judging result；
Second judgment unit judges that dust is merchandised if indicating that current transaction is dust transaction for first judging result
Whether the dust transaction in pond is more than given threshold, obtains the second judging result；
First transaction unit will currently merchandise if indicating that current transaction is not dust transaction for first judging result
Arm's length dealing pond is put into be traded；
Discarding unit, if indicating that the dust transaction in dust trading pit is more than given threshold for second judging result,
Abandon current transaction；
Third judging unit, if indicating that the dust transaction in dust trading pit is less than setting threshold for second judging result
Current transaction is then put into dust trading pit, and judges whether the dust number of transaction in dust trading pit reaches processing by value
Threshold value obtains third judging result；
Second transaction unit, if indicating that the dust number of transaction in dust trading pit reaches processing for the third judging result
Dust transaction is then put into arm's length dealing pond and is traded by threshold value；
Monitoring unit, if indicating that the dust number of transaction in dust trading pit not up to handles threshold for the third judging result
Value then continues to monitor the dust transaction in dust trading pit until the dust number of transaction in dust trading pit reaches processing threshold
Value.
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