CN115660837B - Knowledge graph-based virtual currency address portrait construction method and device - Google Patents
Knowledge graph-based virtual currency address portrait construction method and device Download PDFInfo
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Abstract
The invention discloses a virtual currency address imaging method and device based on a knowledge graph. The method is suitable for the common virtual currency address image problem. The method for constructing the address portrait mainly comprises the steps of constructing structured data based on a knowledge graph, combining the thought of the address portrait, processing virtual currency address data, firstly storing related virtual currency addresses by using a neo4j graph relational database, then analyzing the properties of each address to construct the address portrait, secondly displaying the data among the addresses by a visualization technology, finally extracting the properties among the acquired addresses, and determining the portrait method of each address by utilizing the relationship condition among the addresses. The method can effectively improve the virtual currency crime tracing efficiency and has better practicability.
Description
Technical Field
The invention belongs to the field of knowledge graphs and blockchains, and particularly relates to a virtual currency address portrait construction method and device based on the knowledge graphs.
Background
In the face of address tracing, it is generally chosen to trace the address directly. The development of the existence of each address is obtained by the relation among the discovered addresses, so that the tracing accuracy is improved, and more visual display is provided for address analysis by combining a visualization technology.
Knowledge Graph (knowledgegraph) is a structured semantic Knowledge base used to symbolically describe concepts and their interrelationships in the physical world. The basic composition unit is an entity-relation-entity triplet, and the entities and related attribute-value pairs thereof are mutually connected through the relation to form a net-shaped knowledge structure.
Virtual currency, also commonly referred to as digital currency, i.e., non-authentic currency, and the reference to virtual currency herein generally refers to digital virtual currency such as bitcoin, ethernet, rap, etc., also referred to as cryptocurrency, which is digital currency generated by the rules of the cryptoalgorithm.
When tracing a virtual currency crime, existing papers are mainly clustered based on account establishment so as to infer identity information of each account, but under-inference conditions may exist for different accounts of the same user. Traditional methods for virtual currency tracing rely mainly on simple speculation of currency addresses, but neglect the relationship between addresses.
Disclosure of Invention
The invention aims to: aiming at the problems pointed out in the background art, the invention provides a knowledge-graph-based virtual currency address portrait construction method and device, wherein attributes among different addresses are extracted through a knowledge-graph-based method establishment rule, address portraits are established, then the relation among the addresses is intuitively displayed through a visualization technology, and then the attributes of the addresses are displayed to realize the effect of quick and accurate tracing.
The technical scheme is as follows: the invention provides a virtual currency address image construction method based on a knowledge graph, which comprises the following steps:
step 1: the operation bit coin node client side synchronizes bit coin transaction block data D1;
step 2: importing the bitcoin transaction block data D1 into a neo4j graph relational database to form graph relational data G1;
step 3: acquiring attributes among the address data of the bitcoin according to the acquired data G1 based on the related knowledge of the knowledge graph, wherein the attributes comprise transaction times, address transaction transfer-in and transfer-out data, address financial conditions, address circles, address security, money laundering indexes and abnormal values;
step 4: analyzing address financial conditions by using address transaction transfer-in and transfer-out data, determining whether the address is a special address according to the transaction times, acquiring an address circle according to the address transaction conditions, analyzing and obtaining an address financial value by using existing transaction data, analyzing and obtaining a money laundering index, and establishing an analysis rule to construct a bit coin address image A1;
step 5: and optimizing the address portrait display by using a visual analysis technology.
Further, the specific method of the step 2 is as follows:
step 2.1: reading a local block data blk.dat file;
step 2.2: and importing the data in blk.dat into a neo4j graph relational database by using a Cypher query to form graph relational data G1.
Further, the address data of the bitcoin and the attributes of the addresses form a topological relation of fixed points and edges, and an ultra-large knowledge graph is formed between all the addresses and the attributes thereof.
Further, the specific method in the step 4 is as follows:
step 4.1: acquiring transfer number of each address in transaction dataData i1= { I 1 ，I 2 ，...，I N Data O1 = { O 1 ，O 2 ，...，O n }；
Step 4.2: obtaining address financial status income status by analyzing transfer data I1, and for each piece of data I in the transfer data i If Ii.vin.address exists, it is denoted as vin i Total revenue case vini= = { vin 1 ，vin 2 ，...，vin n Judging the next piece of data if not;
step 4.3: analyzing the data O1 to obtain address financial status expenditure status, and for each piece of data O i If Oi.vout.address exists, it is denoted as vout i Total expense condition vouti= = { vout 1 ，vout 2 ，...，Vout n Judging the next piece of data if not;
step 4.4: determining the financial value of the address according to the acquired income and expense data
Step 4.5: analyzing the transfer-in and transfer-out data I1 and O1 to obtain address income transaction number CI=count (I1), expenditure transaction number CO=count (O1) and total transaction number CA=CI+CO;
step 4.6: the address ring C1 of the bitcoin address data is obtained through analyzing the transfer-in and transfer-out data I1, O1 and the financial state vin and vout:
judging each piece of data for transaction data I1 and O1: firstly, judging transfer data, enabling the transaction address to be address1, and enabling address 2=i at the same time i If address2 does not exist, judging the next transaction data; if address2 exists, judging the transaction amount I of the address2 i Vin value, if transaction amount I i If the value is greater than 0 and less than 1, the transaction data I1 and O1 of address2 and address1 are used to transfer to step 4.7 to obtain the transaction number TG between the two transaction addresses i And judge TG i If not less than 2, if TG i 2 or more, adding address2 into the CIa; if TG i Less than2, address2 is not added to CIa; if the transaction amount I i When the value is greater than or equal to 1, adding address2 into the CIa; and the same thing can obtain the COa, and finally the address circle C1= { CIa, COa };
step 4.7: determining the number of transactions between two addresses address1 and address2, and circularly determining I in the address1 transaction data i Vin. If address equals address2, if equal TG i Increasing 1, judging O in address1 transaction data i Vout. If address equals address2, if equal TC o Increment 1, return tc=tg i +TC o ；
Step 4.8: and (3) analyzing according to the financial value R1 and the transaction times CA to obtain a money laundering index X:
step 4.9: obtaining the portrait characteristic value of the current address according to the steps, and finally obtaining each portrait characteristic value A1, wherein the portrait characteristic of the current address is A j ＝{I1，O1，vinI、voutI、R1、CI、CO、CA、C1、X}，A1＝{A 0 、A 1 、…、A n And j is greater than or equal to 0 and less than or equal to n.
Further, the specific method in the step 5 is as follows:
step 5.1: establishing an optimized display graphical interface;
step 5.2: analyzing and displaying the address portrait by utilizing the contact diagram according to the address portrait data;
step 5.3: and constructing a safety monitoring interface to display abnormal conditions.
The invention also discloses a virtual currency address portrait construction device based on the knowledge graph, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the computer program executes the steps of the virtual currency address portrait construction method based on the knowledge graph when being loaded to the processor.
The beneficial effects are that:
1. the method of the invention uses the existing neo4j graph relational database as data storage, and utilizes the knowledge graph method to extract the attribute of the address portrait, so as to extract the address features more comprehensively and obtain more accurate address portrait.
2. The invention uses the existing data to simplify and build the address portrait, saves time and energy, uses the data transferred in and out to analyze the financial state, obtains whether the address is a special address according to the transaction times, obtains the address circle condition according to the address transaction state, and uses the existing transaction data to analyze the address financial value. And the money laundering index is obtained through analysis, so that the virtual currency crime tracing efficiency is effectively saved.
Drawings
FIG. 1 is a general flow chart of the present invention;
FIG. 2 is a flow chart of a synchronous bitcoin transaction block data;
FIG. 3 is a diagram of creating an analysis rule to create a token address image;
FIG. 4 is a flow chart of creating an analysis rule to construct a token address image;
FIG. 5 is a flow chart for visual analysis technique optimization address portrait display.
Detailed Description
The present invention is further illustrated below in conjunction with specific embodiments, it being understood that these embodiments are meant to be illustrative of the invention only and not limiting the scope of the invention, and that modifications of the invention, which are equivalent to those skilled in the art to which the invention pertains, will fall within the scope of the invention as defined in the claims appended hereto.
The invention discloses a knowledge-graph-based virtual currency address portrait construction method, which specifically comprises the following steps of:
step 1: the operation bit coin node client side synchronizes bit coin transaction block data D1;
step 1.1: downloading and installing bit coin core software;
step 1.2: the bitcoin-related tile data is synchronized to local D1 based on the bitcoin kernel software.
Step 2: importing the bitcoin transaction block data D1 into a neo4j graph relational database to form graph relational data G1;
step 2.1: reading a local block data blk.dat file;
step 2.2: and importing the data in blk.dat into a neo4j graph relational database by using a Cypher query to form graph relational data G1.
Step 3: and acquiring attributes among the bitcoin address data based on the related knowledge of the knowledge graph according to the acquired data G1. Attributes include number of transactions, address transaction in-out data, address financial status, address circle, address security, money laundering index, outliers. The address data of the bitcoin and the attributes of the addresses form a topological relation of fixed points and edges, and knowledge maps are formed among all the addresses and the attributes thereof.
Step 4: the address financial state is analyzed by utilizing address transaction transfer-in and transfer-out data, whether the address is a special address is determined according to the transaction times, an address circle is acquired according to the address transaction state, the address financial value is obtained by utilizing the analysis of the existing transaction data, the money laundering index is obtained by the analysis, and an analysis rule is established to construct a bit coin address image A1.
Step 4.1: acquiring transfer data I1= { I of each address in transaction data 1 ，I 2 ，...，I n Data O1 = { O 1 ，O 2 ，...，O n }。
Step 4.2: obtaining the income condition of the address financial condition through analyzing the transfer data I1, and recording the income condition as vin if Ii.vin.address exists for each piece of data Ii in the data i Total revenue case vini= = { vin 1 ，vin 2 ，...，vin n And if not, judging the next piece of data.
Step 4.3: analyzing the output data O1 to obtain the expense status of the address financial status, and marking each piece of data Oi in the data as yout if oi.vout.address exists i Total expense condition vouti= = { vout 1 ，vout 2 ，...，vout n And if not, judging the next piece of data.
Step 4.4: acquiring the financial resources of the address according to the acquired income and expense dataValue of
Step 4.5: the address income transaction number CI=count (I1) and the expenditure transaction number CO=count (O1) and the total transaction number CA=CI+CO are obtained through analysis of the transfer-in and transfer-out data I1 and O1.
Step 4.6: the address ring C1 of the bitcoin address data is obtained through analyzing the transfer-in and transfer-out data I1, O1 and the financial state vin and vout:
for transaction data I1, O1, each piece of data is judged: firstly, judging transfer data, enabling the transaction address to be address1, and enabling address 2=i at the same time i If address2 does not exist, judging the next transaction data; if address2 exists, judging the transaction amount I of the address2 i Vin. If the transaction amount I i If the value is greater than 0 and less than 1, the transaction data I1 and O1 of address2 and address1 are used to transfer to step 4.7 to obtain the transaction number TG between the two transaction addresses i And judge TG i If not less than 2, if TG i 2 or more, adding address2 into the CIa; if TG i Less than 2, address2 is not added to CIa; if the transaction amount I i And adding address2 into the CIa if the value is greater than or equal to 1. And in the same way, COa can be obtained, and finally, the address circle c1= { CIa, COa } of the address can be obtained.
Step 4.7: judging the number of transactions between the two addresses address1 and address 2:
loop judging I in address1 trade data i Vin. If address equals address2, if equal TG i Increasing 1, judging O in address1 transaction data i Vout. If address equals address2, if equal TC o Increment 1, return tc=tg i +TC o 。
Step 4.8: and (3) analyzing according to the financial value R1 and the transaction times CA to obtain a money laundering index X:
1) When the number of CA transactions is excessive, i.e., CA > =10, and the financial value R1 is excessive, i.e., r1 > =10, i.e.
2) When CA < 10 and R1 < 10, the calculation formula is x=0;
3) In the case where CA > =10 and R1 < 10, the calculation formula is
4) In the case where CA < 10 and r1 > =10, the calculation formula is
Namely:
step 4.9: obtaining the portrait characteristic value of the current address according to the steps, and finally obtaining each portrait characteristic value A1, wherein the portrait characteristic of the current address is A j ＝{I1，O1，vinI、voutI、R1、CI、CO、CA、C1、X}，A1＝{A 0 、A 1 、…、A n And j is greater than or equal to 0 and less than or equal to n.
Step 5: and optimizing the address portrait display by using a visual analysis technology.
Step 5.1: establishing an optimized display graphical interface;
step 5.2: analyzing and displaying the address portrait by utilizing the contact diagram according to the address portrait data;
step 5.3: and constructing a safety monitoring interface to display abnormal conditions.
The following table illustrates the relevant variables in this application:
the invention can be combined with a computer system to form a virtual currency address portrait construction device based on a knowledge graph, and the device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, and the method for constructing the virtual currency address portrait based on the knowledge graph is realized when the computer program is loaded to the processor.
The foregoing embodiments are merely illustrative of the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the present invention and to implement the same, not to limit the scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention should be included in the scope of the present invention.
Claims (5)
1. The method for constructing the virtual currency address image based on the knowledge graph is characterized by comprising the following steps of:
step 1: the operation bit coin node client side synchronizes bit coin transaction block data D1;
step 2: importing the bitcoin transaction block data D1 into a neo4j graph relational database to form graph relational data G1;
step 3: acquiring attributes among the bitcoin address data based on the related knowledge of the knowledge graph according to the acquired graph relation data G1, wherein the attributes comprise transaction times, address transaction transfer-in and transfer-out data, address financial conditions, address circles, address security, money laundering indexes and abnormal values;
step 4: analyzing address financial conditions by using address transaction transfer-in and transfer-out data, determining whether the address is a special address according to the transaction times, acquiring an address circle according to the address transaction conditions, analyzing and obtaining an address financial value by using existing transaction data, analyzing and obtaining a money laundering index, and establishing an analysis rule to construct a bit coin address image A1;
step 4.1: acquiring transfer data I1= { I of each bit coin address in transaction data 1 ,I 2 ,…,I n Data O1 = { O 1 ,O 2 ,…,O n }；
Step 4.2: obtaining address financial status income status by analyzing transfer data I1, and for each piece of data I in the transfer data i If Ii.vin.address exists, it is denoted as vin i Total revenue case vini= = { vin 1 ,vin 2 ,…,vin n Judging the next piece of data if not;
step 4.3: analyzing the data O1 to obtain address financial status expenditure status, and for each piece of data O i If Oi.vout.address exists, it is denoted as vout i Total expense condition vouti= = { vout 1 ,vout 2 ,…,vout n Judging the next piece of data if not;
step 4.4: according to the vin already obtained i Total income condition, vout i The total expense condition obtains the address financial value of the current bit coin address
Step 4.5: analyzing the transfer-in and transfer-out data I1 and O1 to obtain address income transaction number CI=count (I1), expenditure transaction number CO=count (O1) and total transaction number CA=CI+CO;
step 4.6: the current bit coin address data address ring C1 is obtained through the analysis of the transfer-in and transfer-out data I1, O1 and the financial state vin, vout:
for the in-and-out data I1, O1, each piece of data is judged: firstly, judging transfer data, making the current transaction bit coin address be address1, at the same time making address 2=i i If address2 does not exist, judging the next transaction data; if address2 exists, judging the transaction amount I of the address2 i Vin value, if transaction amount I i If the value is greater than 0 and less than 1, the data I1 and O1 of address2 and address1 are used to obtain the number TC of transactions between two transaction addresses in step 4.7 i And judge TC i Whether or not to be more than 2, if TC i 2 or more, adding address2 into the CIa; if TC i Less than 2, address2 is not added to CIa; if trade is madeAmount of money I i When the value is greater than or equal to 1, adding address2 into the CIa; and the same thing can obtain the COa, and finally the address circle C1= { CIa, COa };
step 4.7: determining the number of transactions between two addresses address1 and address2, and circularly determining I in the address1 transaction data i Vin. Address is equal to address2, if equal TC i Increasing 1, judging O in address1 transaction data i Vout. If address equals address2, if equal TC o Increment 1, return tc=tc i +TC o TC is the number of transactions, TC o Judging the number of times of multi-time transactions with the address for transferring out the data;
step 4.8: and (3) analyzing according to the financial value R1 and the total transaction number CA to obtain a money laundering index X:
step 4.9: obtaining the portrait characteristic value of the current bit coin address according to the steps, and finally obtaining the characteristic value of the bit coin address image A1 of each portrait, wherein the portrait characteristic value of the current bit coin address is A j ＝{I1，O1，vinI、voutI、R1、CI、CO、CA、C1、X}，A1＝{A 0 、A 1 、···、A n J is greater than or equal to 0 and less than or equal to n;
step 5: the visual analysis technology is utilized to optimize the display of the bitcoin address image A1.
2. The knowledge-based virtual currency address image construction method according to claim 1, wherein the specific method in the step 2 is as follows:
step 2.1: reading a local block data blk.dat file;
step 2.2: and importing the data in blk.dat into a neo4j graph relational database by using a Cypher query to form graph relational data G1.
3. The method for constructing virtual currency address image based on knowledge graph according to claim 1, wherein the topological relation between fixed point and edge is formed between the bit currency address data and the attributes of the bit currency address data, and the knowledge graph is formed between all the addresses and the attributes thereof.
4. The knowledge-based virtual currency address image construction method according to claim 1, wherein the specific method in the step 5 is as follows:
step 5.1: establishing an optimized display graphical interface;
step 5.2: analyzing and displaying the address image of the bit coin by utilizing the contact diagram according to the address image data of the bit coin;
step 5.3: and constructing a safety monitoring interface to display abnormal conditions.
5. A knowledge-based virtual currency address image construction apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the computer program when loaded into the processor performs the steps of the knowledge-based virtual currency address image construction method as claimed in any one of claims 1-4.
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| KR102487663B1 (en) * | 2020-05-12 | 2023-01-12 | 대한민국 | Automatic tracking method and system for virtual currency |
| CN114819965B (en) * | 2021-01-21 | 2023-10-20 | 成都链安科技有限公司 | Block chain virtual currency monitoring system |
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| CN111444232A (en) * | 2020-01-03 | 2020-07-24 | 上海宓猿信息技术有限公司 | Method for mining digital currency exchange address and storage medium |
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