KR20210106593A - Method, apparatus and computer program for determining cryptocurrency tax evasion using artificial intelligence - Google Patents

Abstract

Provided are a method, device, and computer program for determining whether or not of tax evading using artificial intelligence. In a method performed by a computing device, the method for determining whether or not of cryptocurrency tax evading using the artificial intelligence according to various embodiments of the present invention comprises: a step of identifying a cryptocurrency account whose use is not registered among a plurality of cryptocurrency accounts; a step of selecting a personal cryptocurrency account associated with a cryptocurrency account for which the use is not registered using a predetermined use for each of the plurality of cryptocurrency accounts according to the cryptocurrency transaction information; and a step of analyzing a cryptocurrency transaction history between the selected personal cryptocurrency account and the cryptocurrency account for which the use is not registered, and determining whether or not of tax evading for the owner of the personal cryptocurrency account based on the analysis result.

Description

Method, Apparatus and Computer Program for Determining Cryptocurrency Tax Evasion Using Artificial Intelligence

Various embodiments of the present invention relate to a method, apparatus, and computer program for determining whether or not to evade cryptocurrency tax using artificial intelligence.

As cryptocurrency (e.g., Bitcoin), which was used among a small number of users, gradually gained attention from the media and the general public, the number of users began to increase exponentially, which caused a sharp increase in the price and transaction volume of cryptocurrency. The bubble phenomenon occurred and had a profound impact on society.

Various industries using the cryptocurrency system are developing, but the evaluation of the impact it will have on society and the prospects for future development are greatly mixed, and the responses of each country are also showing a big difference. Countries that negatively evaluate the impact of cryptocurrencies are trying to alleviate the social shock caused by the introduction of new technologies by making the entire use of cryptocurrencies illegal or restricting the use of cryptocurrencies by financial institutions.

Analyzing the price and volume of cryptocurrency, the trading volume decreased due to a sharp price drop in early 2018, but the trading volume recovered rapidly in 2019, indicating that the global cryptocurrency market has matured one step after the bubble.

In addition, considering that cryptocurrency has been confirmed as an alternative investment asset in the financial market, and Brazil, Argentina, and Venezuela are actively using cryptocurrency as an alternative to fiat currency, the cryptocurrency trading market is expected to continue to grow in the future. do.

On the other hand, since cryptocurrencies are inherently decentralized and anonymous, they are highly likely to be abused as criminal means (eg, ICO fraud, money laundering and black market payment methods, etc.). In fact, it is estimated that the expected damage caused by the abused cryptocurrency in 2019 was about 5.2 trillion won, a 2.5-fold increase from the previous year.

Accordingly, government agencies and cryptocurrency-related organizations in each country are working to prevent and track cryptocurrency-related crimes in various ways, as well as create new regulations to prevent cryptocurrency crimes such as money laundering. Trying hard.

However, there is a problem that the subject to comply with the regulations is very broad, including governments and cryptocurrencies handling companies. In addition, although technology development should be done according to the trend of strengthening regulations, there is still a problem that there is a limit to crime prevention and tracking due to technical limitations. For example, in the prior art, accounts were tracked using a manual data collection method, but due to advanced money laundering technology, the amount of transactions that must be viewed during tracking increases, making it practically impossible to view all transaction volumes. In addition, in the case of the manual data collection method, only a limited number of accounts can be identified, and there is a problem that a huge cost is required for account tracking.

Korean Patent Publication No. 10-2019-0123952 (published on November 4, 2019)

The problem to be solved by the present invention is to determine and classify the use of each of a plurality of cryptocurrency accounts by using the cryptocurrency transaction information generated from a plurality of cryptocurrency accounts, so that a lot of information can be processed in a short time at a low cost. It is to provide a method, apparatus and computer program for determining whether cryptocurrency tax evasion using intelligence.

Another problem to be solved by the present invention is to determine whether an illegal act (eg, tax evasion) against the owner of a personal cryptocurrency account based on a transaction history between a predetermined personal cryptocurrency account and another cryptocurrency account according to cryptocurrency transaction information It is to provide a method, device, and computer program to determine whether cryptocurrency tax evasion using artificial intelligence that can do this.

The problems to be solved by the present invention are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

In a method performed by a computing device, the method for determining whether cryptocurrency tax evasion using artificial intelligence according to an embodiment of the present invention for solving the above-mentioned problems is performed, a cryptocurrency whose use is not registered among a plurality of cryptocurrency accounts Identifying an account, selecting a personal cryptocurrency account associated with a cryptocurrency account for which the use is not registered by using a predetermined use for each of the plurality of cryptocurrency accounts according to cryptocurrency transaction information, and the selected individual It may include analyzing the cryptocurrency transaction history between the cryptocurrency account and the cryptocurrency account for which the use is not registered, and determining whether to evade tax for the owner of the personal cryptocurrency account based on the analysis result.

In various embodiments, the determining of whether to evade tax includes determining the possibility of tax evasion based on whether there is a cryptocurrency transaction history that exceeds a reference amount between the selected personal cryptocurrency account and the cryptocurrency account for which the use is not registered may include the step of

In various embodiments, the determining of the possibility of tax evasion may include, if it is determined that there is a possibility of tax evasion, requesting explanatory data on the cryptocurrency transaction history exceeding the reference amount from the terminal of the owner, and the owner It may include the step of determining whether the tax evasion based on the explanatory data obtained from the terminal of the.

In various embodiments, the determining of whether to evade tax includes analyzing cryptocurrency transaction information of the selected personal cryptocurrency account to determine whether there is a history of cryptocurrency collection exceeding a reference amount from an exchange account among the plurality of cryptocurrency accounts If it is determined that there is a cryptocurrency collection history that exceeds the reference amount, determining whether or not to pay unearned income tax on the cryptocurrency collection history exceeding the reference amount, and based on whether or not the unearned income tax is paid and determining whether to evade tax on the owner.

In various embodiments, the determining of whether to evade tax includes analyzing cryptocurrency transaction information of the selected personal cryptocurrency account to determine whether there is a history of cryptocurrency collection from another personal cryptocurrency account, the cryptocurrency collection When it is determined that there is a history, it may include determining whether to pay capital gains tax for the cryptocurrency collection history and determining whether to evade tax to the owner based on whether the transfer income tax is paid.

In various embodiments, the determining of whether to evade tax includes determining whether there is a cryptocurrency transaction history between a cryptocurrency account determined to be an illegal account among the plurality of cryptocurrency accounts and the selected personal cryptocurrency account; Based on whether there is a cryptocurrency transaction history between the cryptocurrency account determined as the account and the selected personal cryptocurrency account, the method may include determining whether the owner is an illegal transaction.

In various embodiments, the step of selecting a personal cryptocurrency account associated with a cryptocurrency account for which the use is not registered may include visualizing cryptocurrency transaction information generated between the plurality of cryptocurrency accounts, and the visualized cryptocurrency transaction information and determining a use for each of the plurality of cryptocurrency accounts by analyzing the .

In various embodiments, the determining of the use for each of the plurality of cryptocurrency accounts may include, in the case where the number of the plurality of cryptocurrency accounts included in the visualized cryptocurrency transaction information is less than or equal to a first reference value, determining the use for each of the plurality of cryptocurrency accounts by analyzing the transaction pattern for each cryptocurrency account, and when the number of transactions according to the cryptocurrency transaction information is less than or equal to the second reference value, based on the owner of the cryptocurrency account Grouping at least one cryptocurrency account among the plurality of cryptocurrency accounts, and using the cryptocurrency transaction information generated in the grouped at least one cryptocurrency account, a pattern for the grouped at least one cryptocurrency account and determining a use for each of the plurality of cryptocurrency accounts by analyzing the .

An apparatus for determining whether or not cryptocurrency tax evasion using artificial intelligence according to another embodiment of the present invention for solving the above-described problems includes a memory for storing one or more instructions and a processor for executing the one or more instructions stored in the memory, and , by executing the one or more instructions, the processor may perform the method of determining whether to evade cryptocurrency tax using artificial intelligence according to an embodiment of the present invention.

A computer program according to another embodiment of the present invention for solving the above-described problems is combined with a computer that is hardware, so as to perform a method of determining whether or not cryptocurrency tax evasion using artificial intelligence according to an embodiment of the present invention. It may be stored in a computer-readable recording medium.

Other specific details of the invention are included in the detailed description and drawings.

According to various embodiments of the present invention, by determining and classifying the use of each of a plurality of cryptocurrency accounts using cryptocurrency transaction information generated from a plurality of cryptocurrency accounts, it is possible to process a lot of information in a short time at a low cost. There is an advantage.

In addition, there is an advantage that it is possible to determine whether an illegal act (eg, tax evasion) against the owner of a personal cryptocurrency account is based on a transaction history between a predetermined personal cryptocurrency account and another cryptocurrency account according to cryptocurrency transaction information.

Effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

1 is a diagram illustrating a system for determining whether or not to evade cryptocurrency tax using artificial intelligence according to an embodiment of the present invention.
2 is a hardware configuration diagram of an apparatus for determining whether tax evasion of cryptocurrency using artificial intelligence according to another embodiment of the present invention.
3 is a flowchart of a method for determining whether or not to evade cryptocurrency tax using artificial intelligence according to another embodiment of the present invention.
4 is a flowchart of a cryptocurrency account classification method using artificial intelligence performed by a cryptocurrency tax evasion determination device in various embodiments.
5 is a diagram illustrating visualized cryptocurrency transaction information in various embodiments.
6 is a diagram illustrating a configuration for determining the use of a cryptocurrency account using a graph-based semi-map learning model in various embodiments.
7 is a diagram illustrating a configuration for determining the use of a cryptocurrency account using an account address-based supervised learning model, in various embodiments.
8 is a diagram illustrating a configuration for determining the use of a cryptocurrency account using an owner-based semi-guided learning model, in various embodiments.
9 is a diagram illustrating a configuration for determining the use of a cryptocurrency account by using image-type cryptocurrency account information and keywords obtained from a website, in various embodiments.
10 is a flowchart of a method of determining whether or not income tax evasion is performed by the cryptocurrency tax evasion determination apparatus in various embodiments.
11 is a flowchart of a method of determining whether to evade capital gains tax performed by a cryptocurrency tax evasion determination apparatus in various embodiments.
12 is a flowchart of a method for determining whether an illegal transaction is performed by an apparatus for determining whether a cryptocurrency tax evasion is performed, according to various embodiments.

Advantages and features of the present invention and methods of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms, and only these embodiments allow the disclosure of the present invention to be complete, and those of ordinary skill in the art to which the present invention pertains. It is provided to fully understand the scope of the present invention to those skilled in the art, and the present invention is only defined by the scope of the claims.

The terminology used herein is for the purpose of describing the embodiments and is not intended to limit the present invention. As used herein, the singular also includes the plural unless specifically stated otherwise in the phrase. As used herein, “comprises” and/or “comprising” does not exclude the presence or addition of one or more other components in addition to the stated components. Like reference numerals refer to like elements throughout, and "and/or" includes each and every combination of one or more of the recited elements. Although "first", "second", etc. are used to describe various elements, these elements are not limited by these terms, of course. These terms are only used to distinguish one component from another. Accordingly, it goes without saying that the first component mentioned below may be the second component within the spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used herein will have the meaning commonly understood by those of ordinary skill in the art to which this invention belongs. In addition, terms defined in a commonly used dictionary are not to be interpreted ideally or excessively unless specifically defined explicitly.

As used herein, the term “unit” or “module” refers to a hardware component such as software, FPGA, or ASIC, and “unit” or “module” performs certain roles. However, “part” or “module” is not meant to be limited to software or hardware. A “unit” or “module” may be configured to reside on an addressable storage medium or to reproduce one or more processors. Thus, by way of example, “part” or “module” refers to components such as software components, object-oriented software components, class components and task components, processes, functions, properties, Includes procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. Components and functionality provided within “parts” or “modules” may be combined into a smaller number of components and “parts” or “modules” or as additional components and “parts” or “modules”. can be further separated.

Spatially relative terms "below", "beneath", "lower", "above", "upper", etc. It can be used to easily describe the correlation between a component and other components. A spatially relative term should be understood as a term that includes different directions of components during use or operation in addition to the directions shown in the drawings. For example, when a component shown in the drawing is turned over, a component described as “beneath” or “beneath” of another component may be placed “above” of the other component. can Accordingly, the exemplary term “below” may include both directions below and above. Components may also be oriented in other orientations, and thus spatially relative terms may be interpreted according to orientation.

In this specification, a computer means all types of hardware devices including at least one processor, and may be understood as encompassing software configurations operating in the corresponding hardware device according to embodiments. For example, a computer may be understood to include a smartphone, a tablet PC, a desktop, a notebook computer, and a user client and an application running on each device, but is not limited thereto.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Each step described in this specification is described as being performed by a computer, but the subject of each step is not limited thereto, and at least a portion of each step may be performed in different devices according to embodiments.

1 is a diagram illustrating a system for determining whether or not to evade cryptocurrency tax using artificial intelligence according to an embodiment of the present invention.

Referring to FIG. 1 , the cryptocurrency tax evasion determination system using artificial intelligence according to an embodiment of the present invention may include a cryptocurrency tax evasion determination device 100 , a user terminal 200 and an external server 300 . have.

Here, the cryptocurrency tax evasion determination system using artificial intelligence shown in FIG. 1 is according to an embodiment, and its components are not limited to the embodiment shown in FIG. 1, and may be added, changed or deleted as necessary. can be

In one embodiment, the cryptocurrency tax evasion determination device 100 collects cryptocurrency transaction information (eg, transaction) generated between a plurality of cryptocurrency accounts, and uses the collected cryptocurrency transaction information to obtain a plurality of You can determine the purpose of each cryptocurrency account (eg type of account, role).

In various embodiments, the cryptocurrency tax evasion determination device 100 collects cryptocurrency transaction information generated between a plurality of cryptocurrency accounts from an external server 300 (eg, a cryptocurrency transaction brokerage server) through the network 400 . and can visualize the collected cryptocurrency transaction information (eg, FIG. 4 ), and analyze the visualized cryptocurrency transaction information to determine the use of each of a plurality of cryptocurrency accounts. However, the present invention is not limited thereto.

In various embodiments, the cryptocurrency tax evasion determination device 100 analyzes the visualized cryptocurrency transaction information to determine the use of each of a plurality of cryptocurrency accounts, but according to the analysis result, individual accounts, exchanges It can be determined as any one of an account, a Miners account, a Mixers account, a Merchant account, a Services account, a Darkweb account, and a hedge funds account. However, the present invention is not limited thereto.

In one embodiment, the cryptocurrency tax evasion determination device 100 identifies a cryptocurrency account whose use is not registered among a plurality of cryptocurrency accounts, and uses for each of the plurality of cryptocurrency accounts determined in advance according to cryptocurrency transaction information. can be used to select a personal cryptocurrency account associated with a cryptocurrency account for which use is not registered, and the owner of the personal cryptocurrency account based on the cryptocurrency transaction history between the selected personal cryptocurrency account and the cryptocurrency account for which the use is not registered. can determine whether or not to evade tax.

In one embodiment, the user terminal 200 may be connected to the cryptocurrency tax evasion determination apparatus 100 through the network 400, and receives various types of information related to cryptocurrency tax evasion from the cryptocurrency tax evasion determination apparatus 100. can be provided For example, the user terminal 200 may include at least one of a smartphone, a tablet PC, a notebook computer, and a desktop having a display in at least a partial area of the user terminal 200, and determining whether to evade cryptocurrency tax through the display By outputting a user interface (UI) provided by the device 100 , various information provided from the cryptocurrency tax evasion determination device 100 may be output.

In various embodiments, the user terminal 200 may upload various explanatory data related to tax evasion through the UI provided from the cryptocurrency tax evasion determination apparatus 100 . However, the present invention is not limited thereto.

In one embodiment, the external server 300 may be connected to the cryptocurrency tax evasion determination apparatus 100 through the network 400, and the cryptocurrency tax evasion determination apparatus 100 is necessary for determining whether the owner is tax evasion. Various information (eg, cryptocurrency transaction information, information related to the use of each of a plurality of cryptocurrency accounts) may be provided. For example, the external server 300 may be a cryptocurrency transaction brokerage server that provides a service for brokering cryptocurrency transactions, and is generated by conducting transactions between cryptocurrency accounts through a service brokering cryptocurrency transactions. It is possible to store the cryptocurrency transaction information, and provide the stored cryptocurrency transaction information to the cryptocurrency tax evasion determination device 100 .

In various embodiments, the external server 300 receives various data from the cryptocurrency tax evasion determination device 100 (eg, information on the use determined for each of a plurality of cryptocurrency accounts, tax evasion information for each of a plurality of owners, and explanatory data) data, etc.) can be provided and stored. For example, the external server 300 may be a storage device separately provided outside the cryptocurrency tax evasion determination device 100 . However, the present invention is not limited thereto.

In various embodiments, the cryptocurrency tax evasion determination apparatus 100 may include a storage device (not shown) for storing various data generated by the cryptocurrency tax evasion determination apparatus 100 . For example, the cryptocurrency tax evasion determination apparatus 100 may systematically store and manage tens of billions of account information and transaction information using a storage device. For example, the cryptocurrency tax evasion determination apparatus 100 may store the visualized cryptocurrency transaction information, and may have a graph-only database (Graph DB) optimized for cryptocurrency fund tracking, and timely crime using this. You can tune the DB's analysis engine to a high-performance engine dedicated to graph information to track and provide real-time information. Hereinafter, a hardware configuration of the cryptocurrency tax evasion determination apparatus 100 will be described with reference to FIG. 2 .

2 is a hardware configuration diagram of an apparatus for determining whether tax evasion of cryptocurrency using artificial intelligence according to another embodiment of the present invention.

Referring to FIG. 2 , the cryptocurrency tax evasion determination apparatus 100 (hereinafter, “computing device 100”) according to another embodiment of the present invention may include a processor 110 and a memory 120 . In various embodiments, the computing device 100 may further include a network interface (or communication interface) (not shown), storage (not shown), and a bus (not shown).

In an embodiment, the processor 110 may control the overall operation of each component of the computing device 100 . The processor 110 may include a central processing unit (CPU), a micro processor unit (MPU), a micro controller unit (MCU), or any type of processor well known in the art.

In various embodiments, the processor 110 may perform an operation on at least one application or program for executing the method according to the embodiments of the present invention. In various embodiments, the processor 110 includes one or more cores (not shown) and a graphic processing unit (not shown) and/or a connection path (eg, a bus, etc.) for transmitting and receiving signals to and from other components. can do.

In various embodiments, the processor 110 temporarily and/or permanently stores a signal (or data) processed inside the processor 110 , a random access memory (RAM) and a read access memory (ROM). -Only Memory, not shown) may be further included. In addition, the processor 110 may be implemented in the form of a system on chip (SoC) including at least one of a graphic processing unit, a RAM, and a ROM.

In one embodiment, the processor 110 executes one or more instructions stored in the memory 120, so that the method to be described with reference to FIGS. 3 to 12 (eg, a method of determining whether cryptocurrency tax evasion using artificial intelligence) can be performed. For example, the processor 110 executes one or more instructions stored in the memory 120 to identify a cryptocurrency account whose use is not registered among a plurality of cryptocurrency accounts, a plurality of predetermined values according to cryptocurrency transaction information. Selecting a personal cryptocurrency account associated with a cryptocurrency account for which use is not registered using the use for each cryptocurrency account of It is possible to perform a method of determining whether or not to evade cryptocurrency tax using artificial intelligence, which includes analyzing and determining whether to evade tax for the owner of a personal cryptocurrency account based on the analysis result.

In one embodiment, memory 120 may store various data, commands, and/or information. The memory 120 may store programs (one or more instructions) for processing and controlling the processor 110 . Programs stored in the memory 120 may be divided into a plurality of modules according to functions.

In various embodiments, steps of a method or algorithm described in connection with an embodiment of the present invention may be implemented directly in hardware, as a software module executed by hardware, or by a combination thereof. A software module may contain random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any type of computer-readable recording medium well known in the art to which the present invention pertains.

The components of the present invention may be implemented as a program (or application) to be executed in combination with a computer, which is hardware, and stored in a medium. The components of the present invention may be implemented as software programming or software components, and similarly, embodiments may include various algorithms implemented as data structures, processes, routines, or combinations of other programming constructs, including C, C++ , Java, assembler, etc. may be implemented in a programming or scripting language. Functional aspects may be implemented in an algorithm running on one or more processors. Hereinafter, with reference to FIG. 3 , a method of determining whether to evade cryptocurrency tax using artificial intelligence performed by the computing device 100 will be described.

3 is a flowchart of a method for determining whether or not to evade cryptocurrency tax using artificial intelligence according to another embodiment of the present invention.

Referring to FIG. 3 , in step S110 , the computing device 100 may identify a cryptocurrency account whose usage is not registered among a plurality of cryptocurrency accounts. For example, the computing device 100 is a cryptocurrency account whose use is not registered in the process of opening a cryptocurrency account among a plurality of cryptocurrency accounts (eg, a cryptocurrency whose use is not registered in the process of opening a cryptocurrency account). After opening an account or cryptocurrency account, it is possible to identify a cryptocurrency account that has not undergone a separate reporting procedure to register its use). For example, the reporting procedure according to the disclosed embodiment may mean a procedure of obtaining transaction information through a cryptocurrency account and reporting the cryptocurrency account to the National Tax Service so that a corresponding tax can be imposed, but is limited thereto no.

In various embodiments, the computing device 100 selects a cryptocurrency account that is not suitable for the previously registered use based on the use registered in each of the plurality of cryptocurrency accounts and the cryptocurrency transaction information between the plurality of cryptocurrency accounts. can However, the present invention is not limited thereto.

In step S120, the computing device 100 may select a personal cryptocurrency account associated with the cryptocurrency account for which the use identified in step S110 is not registered. For example, the computing device 100 may select the personal cryptocurrency account of the owner associated with the cryptocurrency account for which the use is not registered by using the use for each of the plurality of cryptocurrency accounts determined in accordance with the cryptocurrency transaction information. have.

For example, the computing device 100 may monitor a transaction of an unidentified personal account, in which the attribute is determined to be a personal account among accounts for which use is not registered. When the non-identified personal account performs a transaction with a previously reported specific personal account, the computing device 100 may determine that there is a correlation between the previously reported corresponding personal account and the non-identified personal account. For example, both accounts may be accounts of the same person, and the non-identified personal account may be an account additionally held by the previously reported individual account holder, and may be used for tax evasion.

In various embodiments, the computing device 100, based on the cryptocurrency transaction information of the cryptocurrency account for which the use is not registered, is a According to the cryptocurrency account classification method (eg, the cryptocurrency account classification method described with reference to FIGS. 4 to 9 ), a cryptocurrency account determined as a personal cryptocurrency account may be selected. Hereinafter, a method of determining a use for each of a plurality of cryptocurrency accounts performed by the computing device 100 will be described with reference to FIGS. 4 to 9 .

4 is a flowchart of a cryptocurrency account classification method using artificial intelligence performed by a cryptocurrency tax evasion determination device in various embodiments.

Referring to FIG. 4 , in step S210 , the computing device 100 may collect cryptocurrency transaction information generated between a plurality of cryptocurrency accounts. For example, the computing device 100 generates cryptocurrency transaction information (eg, transaction) generated between a plurality of cryptocurrency accounts from the external server 300 (eg, a server that mediates cryptocurrency transactions between a plurality of cryptocurrency accounts). can be provided. However, the present invention is not limited thereto.

In step S220, the computing device 100 may visualize the cryptocurrency transaction information generated between the plurality of cryptocurrencies collected in step S110.

In various embodiments, the computing device 100 may visualize cryptocurrency transaction information generated between a plurality of cryptocurrencies in a graph form. However, the present invention is not limited thereto, and the computing device 100 may visualize cryptocurrency transaction information in various forms. Hereinafter, a configuration in which the computing device 100 visualizes cryptocurrency transaction information will be described with reference to FIG. 5 .

5 is a diagram illustrating visualized cryptocurrency transaction information in various embodiments.

Referring to FIG. 5 , in one embodiment, the computing device 100 may generate a plurality of nodes 10 corresponding to each of a plurality of cryptocurrency accounts. For example, the computing device 100 may generate one node corresponding to one cryptocurrency account.

In various embodiments, the computing device 100 may generate a node in the form of a square having a predetermined size, but is not limited thereto, and various forms (eg: round, oval, or rectangular).

In various embodiments, the computing device 100 generates a node corresponding to each of the plurality of cryptocurrency accounts, and a node corresponding to each of the plurality of cryptocurrency accounts based on the use of the cryptocurrency account determined through step S240 to be described later. properties can be determined. For example, the computing device 100 selects a node 11 corresponding to a cryptocurrency account (eg, a black market account, a fraudulent account, and a gambling account) used for crime and fraud based on the use of each of the plurality of cryptocurrency accounts. A first color (eg, red) may be set, and a node 12 corresponding to a cryptocurrency account associated with a criminal and fraudulent use account may be set as a second color (eg, yellow). Also, the computing device 100 may set the node 13 corresponding to the normally used cryptocurrency account (eg, an exchange account, a mining account, and a commerce account) to a third color (eg, white). Through this, a user who receives and monitors visualized cryptocurrency transaction information can more easily track and monitor cryptocurrency accounts used for crime and fraud. However, the present invention is not limited thereto.

In an embodiment, the computing device 100 may connect the sender's cryptocurrency account and the receiver's cryptocurrency account among nodes corresponding to a plurality of cryptocurrency accounts with an edge based on the cryptocurrency transaction information. For example, when it is determined that the remittance is made from the first cryptocurrency account to the second cryptocurrency account among the plurality of cryptocurrency accounts based on the cryptocurrency transaction information, the computing device 100 corresponds to the first cryptocurrency account. The node 11 and the node 12 corresponding to the second cryptocurrency account may be connected with a line.

In various embodiments, the computing device 100 connects a line (eg, a line in the form of an arrow) from the node of the sender's cryptocurrency account to the node of the receiver's cryptocurrency account, and the cryptocurrency is positioned adjacent to the connected line. Transaction quantity, number of transactions, and transaction time information according to transaction information can be output together. However, the present invention is not limited thereto.

According to an embodiment, the computing device 100 connects the node of the sender's cryptocurrency account and the node of the receiver's cryptocurrency account according to the transaction quantity, number of transactions, and transaction time information according to the cryptocurrency transaction information. can change the form of For example, the thickness of the line may change depending on the amount of cryptocurrency transaction (or transaction amount), and the shape of the line (eg, broken line, double line, etc.) may change depending on the number of cryptocurrency transactions, and the cryptocurrency transaction time or The length of the line may be changed according to the transaction frequency, but is not limited thereto.

The shape of the line connecting the nodes may be variously set so that at least some of the transaction quantity, number of transactions, and transaction time information according to the cryptocurrency transaction information can be visualized and read according to a preset rule.

The computing device 100 may extract various feature values based on the connection relationship between nodes, the characteristics of each node, and the shape of a line connecting each node using the pre-learned artificial intelligence model, and accordingly, The attributes of the corresponding accounts may be determined.

In an embodiment, the computing device 100 may determine the attribute of a transaction corresponding to each line by using a pre-learned artificial intelligence model. For example, when a node-to-node remittance is made, it may be a remittance for a cryptocurrency transaction for investment purposes, a remittance to pay for a product or service, asset management, tax evasion, or illegal transfer of funds. It may be a remittance for

In order to determine this, the computing device 100 may utilize not only information on the quantity, number, frequency, and time of each transaction, but also cryptocurrency price information at the time of the transaction. Unlike traditional currencies, cryptocurrency has a characteristic that its value can change significantly from moment to moment. Therefore, by utilizing the market price information at the time of the transaction of the cryptocurrency, the value of the amount actually transferred can be determined, and accordingly, the attribute of the transaction can be determined.

For example, if there are multiple remittances between different nodes and the value of the remittance calculated by reflecting the market price of cryptocurrency is constant, it can be determined that the price has been paid for a product or service with a specific value. . On the other hand, if a certain amount of cryptocurrency is being remitted despite fluctuations in the price of cryptocurrency, it can be determined that the remittance has occurred regardless of the actual value and has other purposes. However, the purpose of remittance may be evaluated differently depending on specific situation information, and the criteria for determination are not limited to the above example.

In addition, if a large number of transactions occur in a situation in which the cryptocurrency market price changes rapidly, it may be judged to be a transaction for the purpose of investment. Transactions between accounts, asset management, tax evasion, etc.)

According to an embodiment, as described above, a line connecting each node may be visualized according to a preset rule, and the computing device 100 uses a pre-learned artificial intelligence model to display a transaction attribute of each line. can be judged For example, the computing device 100 may extract various features from the visualized shape of each line, and estimate properties of a transaction corresponding thereto.

In the disclosed embodiment, the artificial intelligence model may be learned based on a deep learning model and training data including information on a visualized image and an answer (eg, account attribute, transaction attribute, etc.) corresponding to each image. However, the present invention is not limited thereto.

Referring back to FIG. 4 , in step S230 , the computing device 100 may analyze the cryptocurrency transaction information visualized in step S220 , and in step S240 , the computing device 100 is visualized through step S230 . Based on the analysis result of the cryptocurrency transaction information, it is possible to determine the use for each of the plurality of cryptocurrency accounts.

In various embodiments, the computing device 100 automatically extracts a feature value from the cryptocurrency transaction information visualized in a graph form in step S220 using a pre-trained artificial intelligence model (eg, a deep learning model). and the use of each of the plurality of cryptocurrency accounts can be determined using the extracted feature value. For example, the feature value may be in the overall form of a graph, and the computing device 100 determines which cryptocurrency account is located on the graph according to the overall shape of the cryptocurrency transaction information visualized in the graph form. It can be determined whether the account is performing a role. However, the present invention is not limited thereto.

In one embodiment, the pre-trained artificial intelligence model is based on the training data in which the properties of the cryptocurrency account corresponding to one or more nodes included in the visualized cryptocurrency transaction information and the visualized cryptocurrency transaction information in the form of a graph are labeled. can be learned As another example, the pre-trained artificial intelligence model clusters the attributes of accounts corresponding to one or more nodes from the cryptocurrency transaction information visualized in the form of a graph, and receives or automatically determines the attribute information of each clustered account. It is also possible to perform classification on the properties of .

In various embodiments, the computing device 100 uses a graph-based semi-map learning model based on the visualized state of the cryptocurrency transaction information (eg, the number of nodes, the number of lines connecting the nodes, etc.) The use of a cryptocurrency account can be determined by using any one of the determination method, the method of determining the use of a cryptocurrency account using an account address-based supervised learning model, and the method of determining the use of a cryptocurrency account using an owner-based semi-supervised learning model. have.

In various embodiments, the computing device 100 uses any one of a graph-based semi-supervised learning model, an account address-based supervised learning model, and an owner-based semi-supervised learning model based on the type of input data to generate a cryptocurrency account use can be determined. Hereinafter, it will be described with reference to FIGS. 6 to 8 .

6 is a diagram illustrating a configuration for determining the use of a cryptocurrency account using a graph-based semi-map learning model in various embodiments.

Referring to FIG. 6 , in various embodiments, the computing device 100 determines the use of a cryptocurrency account by using a graph-based semi-map learning model when the number of interconnected nodes in the visualized cryptocurrency transaction information is not large. can

The graph-based semi-supervised learning model is a model that can process tens of billions of cryptocurrency transaction information stored in graph format into meaningful information. : Deep learning analysis) may be a model that can determine the use of a cryptocurrency account. For example, the graph-based semi-supervised learning model in-depth analysis (e.g., clustering, classification) of the node corresponding to the cryptocurrency account and the characteristics of the line representing the cryptocurrency transaction information. It is possible to derive the necessary information in determining the use. In addition, the graph-based semi-supervised learning model may be a model to which semi-supervised learning is applied so that it can have higher accuracy using a small amount of correct answer data. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 uses a graph-based semi-map learning model when it is determined that the number of a plurality of nodes included in the visualized cryptocurrency transaction information exceeds a preset first reference value (eg : Using the visualized cryptocurrency transaction information as an input value), it is possible to determine the form in which a plurality of nodes are connected by a line (eg, the overall shape of the graph), and a cryptocurrency account based on the form in which a plurality of nodes are connected by a line use can be determined. For example, when the overall shape of the graph has the graph pattern of the exchange, the computing device 100 may determine the use of the corresponding cryptocurrency account as the exchange account. However, the present invention is not limited thereto.

7 is a diagram illustrating a configuration for determining the use of a cryptocurrency account using an account address-based supervised learning model, in various embodiments.

Referring to FIG. 7 , in the visualized cryptocurrency transaction information, when the number of interconnected nodes is not large, the computing device 100 may determine the use of the cryptocurrency account by using the account address-based supervised learning model.

The account address-based supervised learning model may be a model for identifying the use of each cryptocurrency account by analyzing a transaction pattern based on individual cryptocurrency accounts. The account address-based supervised learning model may be a model in which a cryptocurrency transaction pattern is learned using only a cryptocurrency account whose use is determined in advance through the above method and a cryptocurrency account with 100% certainty through manual operation.

In various embodiments, the computing device 100 performs account address-based supervised learning when the number of a plurality of nodes connected by lines is less than or equal to a first reference value and the number of lines for each of the plurality of nodes exceeds a second reference value. Using the model, it is possible to analyze the transaction pattern for each cryptocurrency account according to the transaction history for each of the plurality of cryptocurrency accounts, and determine the use of each of the plurality of cryptocurrency accounts based on the analyzed transaction pattern. For example, the computing device 100 may determine the use of the cryptocurrency account as an ICO account when the transaction pattern for the cryptocurrency account shows a wave shape, and determines the form in which the transaction pattern for the cryptocurrency account occurs frequently. If it is visible, the use of the cryptocurrency account can be determined as an exchange hot wallet account, and when the transaction pattern for the cryptocurrency account is in the form of a staircase, the use of the cryptocurrency account can be determined as a personal account and an exchange cold wallet account, If the deposit and withdrawal amounts are the same in the transaction pattern for the cryptocurrency account, the use of the cryptocurrency account can be determined as the exchange user wallet account. However, the present invention is not limited thereto.

8 is a diagram illustrating a configuration for determining the use of a cryptocurrency account using an owner-based semi-guided learning model, in various embodiments.

Referring to FIG. 8 , in various embodiments, when the number of transaction details between cryptocurrency accounts for determining a transaction pattern is a small number (eg, one), the computing device 100 uses an owner-based semi-guided learning model to encrypt You can decide the purpose of the monetary account.

The owner-based semi-supervised learning model is a technology that processes the reclassified cryptocurrency transaction information into meaningful information based on the owner of the cryptocurrency account. It may be a model that learned the owner's transaction pattern identified through Entity Heuristic Clustering. The owner-based semi-supervised learning model can be a model that has learned various data through semi-supervised learning with high accuracy with only a small amount of correct data, and can determine the use of a cryptocurrency account by performing semi-supervised deep learning analysis.

In various embodiments, when the number of the plurality of nodes connected by lines is less than or equal to the first reference value and the number of lines for each of the plurality of nodes is less than or equal to the second reference value, the computing device 100 generates an owner-based semi-supervised learning model. Grouping at least one cryptocurrency account among a plurality of cryptocurrency accounts based on the owner of the cryptocurrency account using A pattern for the currency account may be analyzed, and a use for each of the grouped at least one cryptocurrency account may be determined based on the grouped pattern (eg, FIG. 8 ) for the at least one cryptocurrency account. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 may collect image form of cryptocurrency account information and one or more keywords from an external website, and use the collected information to determine the use of the cryptocurrency account. Hereinafter, it will be described with reference to FIG.

9 is a diagram illustrating a configuration for determining the use of a cryptocurrency account by using image-type cryptocurrency account information and keywords obtained from a website, in various embodiments.

Referring to FIG. 9 , the computing device 100 may collect image form of cryptocurrency account information and one or more keywords from an external website, and analyze the image form of cryptocurrency account information to obtain a text form of cryptocurrency account. Information may be extracted, and one or more keywords may be analyzed to determine the use of a cryptocurrency account corresponding to the extracted text-type cryptocurrency account information.

In general, transactions using cryptocurrency value anonymity, so the address of the cryptocurrency account is often stored in the form of an image. In this case, the computing device 100 may search for the cryptocurrency account information in the form of an image, and extract the cryptocurrency account in the form of a text from the found cryptocurrency account information in the form of an image (eg, by using OCR character reading technology). .

In addition, the computing device 100 may extract one or more main keywords from a website on which the cryptocurrency account address is posted, and may determine a use for the cryptocurrency account extracted in text form according to the extracted keywords. For example, when the keywords extracted from the website on which the cryptocurrency account address is posted are Drugs and Weeds, the computing device 100 may determine the use of the cryptocurrency account extracted in text form as a black market account.

In various embodiments, the computing device 100 may collect information related to cryptocurrency from an illegal dark web site, and use it to determine the use of a cryptocurrency account.

In general, a dark web site refers to a web that requires the use of a specific program to access it, and is used for cybercriminals because the visitor or server cannot be identified in a normal way. In particular, various illegal crimes using cryptocurrency as a payment method are prevalent in the dark web. In order to monitor the cryptocurrency account performing such an illegal transaction, the computing device 100 uses pre-stored Darkweb access software (using Tor browser, software that accesses domains ending in *.onion). Access the dark web site, automatically collect information related to cryptocurrency from the dark web site at preset intervals, and determine the use of each of a plurality of cryptocurrency accounts based on the information related to cryptocurrency collected from the dark web site can For example, the computing device 100 may set a cryptocurrency account corresponding to a cryptocurrency account address obtained from a dark web site among a plurality of cryptocurrency accounts as a dark web account. However, the present invention is not limited thereto.

Referring back to FIG. 4 , in step S130 , the computing device 100 may analyze the cryptocurrency transaction history between the personal cryptocurrency account selected in step S120 and the cryptocurrency account whose usage is not registered. For example, the computing device 100 may determine whether there is a cryptocurrency transaction history exceeding a reference amount by analyzing the cryptocurrency transaction history between the selected personal cryptocurrency account and the cryptocurrency account for which the use is not registered.

In step S140, the computing device 100 determines whether or not to evade tax for the owner of the personal cryptocurrency account based on the cryptocurrency transaction history between the selected personal cryptocurrency account and the cryptocurrency account for which the use is not registered, analyzed through the step S130. can judge

In various embodiments, the computing device 100 may determine the possibility of tax evasion based on whether there is a cryptocurrency transaction history exceeding a reference amount between the personal cryptocurrency account and the cryptocurrency account for which the use is not registered. For example, the computing device 100 may determine that there is a possibility of tax evasion when there is a cryptocurrency transaction history exceeding the reference amount between the personal cryptocurrency account and the cryptocurrency account for which the use is not registered.

For example, a cryptocurrency account with no registered use may have the same owner as a personal cryptocurrency account, and a cryptocurrency account with no registered use may be used for tax evasion. The computing device 100 may determine whether or not to evade tax by analyzing the transaction record, and if the explanatory data is obtained after additionally requesting the explanatory data, it may be compared with the analyzed transaction record to determine whether to evade the tax.

In various embodiments, when it is determined that there is a possibility of tax evasion, the computing device 100 may request explanatory data about the cryptocurrency transaction history exceeding the reference amount from the owner's terminal (eg, the user terminal 200). . For example, the computing device 100 provides a UI to the owner's terminal to provide information related to the possibility of tax evasion for a specific cryptocurrency transaction of the owner, and various callings that can prove that the cryptocurrency transaction is not for tax evasion purposes Materials can be uploaded.

In various embodiments, the computing device 100 determines whether tax evasion for a cryptocurrency transaction history exceeding the reference amount between the personal cryptocurrency account and the cryptocurrency account for which the use is not registered, based on the explanatory data uploaded from the owner's terminal can be proven, and accordingly, it is possible to determine whether the owner is tax evasion or not.

In various embodiments, when the computing device 100 does not receive separate explanatory data from the owner's terminal, the cryptocurrency transaction history exceeding the reference amount between the personal cryptocurrency account and the cryptocurrency account for which the use is not registered is tax evasion. It can be determined that the transaction was created for a purpose. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 may determine whether to evade tax on the owner by determining the authenticity of the explanatory data uploaded from the owner's terminal. For example, the computing device 100 may obtain information about the tax paid by the owner from the National Tax Service server, and compare the information about the tax paid by the owner obtained from the National Tax Service server with the explanatory data uploaded from the owner terminal. can At this time, when the explanatory data uploaded from the owner's terminal and the owner's tax payment information obtained from the National Tax Service server are different, the computing device 100 is a password exceeding the standard amount between the personal cryptocurrency account and the cryptocurrency account for which the use is not registered. It can be determined that the currency transaction history is a transaction created for the purpose of tax evasion.

In various embodiments, when it is determined that there is tax evasion with respect to the owner or it is determined that there is a possibility of tax evasion, the computing device 100 analyzes the cryptocurrency transaction information of the personal cryptocurrency account to the owner, You can also check whether or not you have paid taxes. For example, the computing device 100 analyzes the cryptocurrency transaction information of the personal cryptocurrency account to the owner who is determined to have tax evasion or the owner who is determined to have tax evasion potential to conduct cryptocurrency transactions between the personal cryptocurrency account and the exchange account. It is determined whether there is a history, whether there is a history of cryptocurrency trading between individual cryptocurrency accounts, and whether there is a transaction history between cryptocurrency accounts determined to be illegal accounts, and accordingly, taxes on the owner (e.g., unearned income tax, capital gains tax, etc.) ) to determine whether payment has been made or whether there is an illegal transaction. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 may determine whether to evade tax (eg, non-payment of unearned income tax) for the owner of the personal cryptocurrency account based on cryptocurrency transaction information between the personal cryptocurrency account and the exchange account. Hereinafter, it will be described with reference to FIG. 10 .

10 is a flowchart of a method of determining whether or not income tax evasion is performed by the cryptocurrency tax evasion determination apparatus in various embodiments.

Referring to FIG. 10 , in step S310 , the computing device 100 analyzes the cryptocurrency transaction information of the personal cryptocurrency account to determine whether there is a cryptocurrency collection history exceeding the reference amount from the exchange account among a plurality of cryptocurrency accounts. can judge For example, the computing device 100 may include a cryptocurrency account whose use is registered as an exchange account or a cryptocurrency account whose use is determined as an exchange account according to a cryptocurrency account classification method (eg, step S130 in FIG. 3 ) and a personal cryptocurrency account. By analyzing the cryptocurrency transaction history of However, the present invention is not limited thereto.

In step S320, when it is determined that there is a history of depositing cryptocurrency exceeding the reference amount from the exchange account to the personal cryptocurrency account, the computing device 100 pays unearned income tax on the cryptocurrency collection history exceeding the reference amount can determine whether For example, the computing device 100 may provide a UI for outputting information related to a cryptocurrency collection history exceeding the reference amount to the terminal of the owner of the personal cryptocurrency account, and the corresponding UI from the owner's terminal through the provided UI Unearned income tax payment data for cryptocurrency collection history can be uploaded, and based on the uploaded unearned income tax payment data, it is possible to determine whether or not to pay unearned income tax.

In step S330, the computing device 100 may determine whether to evade tax for the owner based on the unearned income tax payment data uploaded from the terminal of the owner in step S320. For example, the computing device 100 may determine that there is no tax evasion related to unearned income tax when raw income tax payment data for the corresponding cryptocurrency collection history is uploaded from the owner's terminal. On the other hand, the computing device 100 may determine that there is tax evasion related to unearned income tax on the cryptocurrency collection history when it does not receive uploading of unearned income tax payment data for the cryptocurrency collection history from the owner's terminal. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 compares the raw income tax payment data for the cryptocurrency collection history obtained from the National Tax Service server with the raw income tax payment data for the cryptocurrency collection history from the owner's terminal, and from the owner's terminal It is possible to judge the authenticity of the uploaded unearned income tax payment data, and to judge whether the owner is tax evasion based on the authenticity determination result.

In various embodiments, the computing device 100 may determine whether to evade tax (eg, non-payment of capital gains tax) for the owner of the personal cryptocurrency account based on cryptocurrency transaction information between individual cryptocurrency accounts. Hereinafter, it will be described with reference to FIG. 11 .

11 is a flowchart of a method of determining whether to evade capital gains tax performed by a cryptocurrency tax evasion determination apparatus in various embodiments.

Referring to FIG. 11 , in step S410 , the computing device 100 analyzes the cryptocurrency transaction information of the first personal cryptocurrency account of the first owner and collects the cryptocurrency collection history from the second personal cryptocurrency account of the second owner. It can be determined whether there is

In step S420 , when it is determined that there is a cryptocurrency collection history in step S410 , the computing device 100 may determine whether to pay capital gains tax on the cryptocurrency collection history. For example, the computing device 100 may provide a UI for outputting information related to a cryptocurrency collection history from a second personal cryptocurrency account to the terminal of the first owner, and the terminal of the first owner through the provided UI You can upload the transfer tax payment data for the cryptocurrency collection history from the company, and determine whether to pay capital gains tax based on the uploaded transfer income tax payment data on the cryptocurrency collection history.

In step S430 , the computing device 100 may determine whether to evade tax for the first owner based on the transfer income tax payment data uploaded from the terminal of the first owner in step S420 . For example, the computing device 100 may determine that there is no capital gains tax-related tax evasion when data on the transfer income tax for the cryptocurrency collection history is uploaded from the terminal of the first owner. On the other hand, the computing device 100 may determine that there is tax evasion related to capital gains tax on the cryptocurrency collection history when it does not receive the transfer tax payment data for the cryptocurrency collection history from the first owner's terminal. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 compares the transfer income tax payment data for the cryptocurrency collection history obtained from the National Tax Service server with the transfer income tax payment data for the cryptocurrency collection history from the owner's terminal, from the owner's terminal It is possible to judge the authenticity of the uploaded unearned income tax payment data, and to judge whether the owner is tax evasion based on the authenticity determination result.

In various embodiments, when it is determined that there is tax evasion for the owner, the computing device 100 transmits information on a cryptocurrency transaction history corresponding to tax evasion and information guiding payment of tax on the cryptocurrency transaction to the individual. It can be provided to the terminal of the holder of the cryptocurrency account.

In various embodiments, the computing device 100 may determine whether an illegal transaction is performed with respect to the owner of the personal cryptocurrency account based on the cryptocurrency transaction history between the cryptocurrency account and the personal cryptocurrency account determined as an illegal account. Hereinafter, it will be described with reference to FIG. 12 .

12 is a flowchart of a method for determining whether an illegal transaction is performed by an apparatus for determining whether a cryptocurrency tax evasion is performed, according to various embodiments.

Referring to FIG. 12 , in step S510 , the computing device 100 may determine whether there is a cryptocurrency transaction history between a cryptocurrency account determined to be an illegal account among a plurality of cryptocurrency accounts and a personal cryptocurrency account. For example, the computing device 100 selects at least one cryptocurrency account determined to be an illegal account (eg, a black market account, a fraud account, a gambling account, etc.) based on cryptocurrency transaction information between a plurality of cryptocurrency accounts, By analyzing the cryptocurrency transaction history of at least one cryptocurrency account selected as an illegal account, it is possible to determine whether there is a cryptocurrency transaction between a personal cryptocurrency account and at least one cryptocurrency account selected as an illegal account.

In step S520 , the computing device 100 may determine whether the owner is an illegal transaction based on whether there is a cryptocurrency transaction history between the cryptocurrency account determined to be an illegal account and the personal cryptocurrency account. For example, when there is a cryptocurrency transaction history between a cryptocurrency account determined as an illegal account and a personal cryptocurrency account, the computing device 100 may determine that there is an illegal transaction for the owner of the personal cryptocurrency account. However, the present invention is not limited thereto.

The method of determining whether to evade cryptocurrency tax using the aforementioned artificial intelligence has been described with reference to the flowchart shown in the drawings. For a simple explanation, the method of determining whether or not cryptocurrency tax evasion using artificial intelligence has been described as a series of blocks, but the present invention is not limited to the order of the blocks, and some blocks are shown in an order different from that shown and operated in this specification may be performed or may be performed simultaneously. In addition, new blocks not described in this specification and drawings may be added, or some blocks may be deleted or changed.

In various embodiments, the computing device 100 tracks the money flow of cryptocurrency based on the cryptocurrency account attribute corresponding to each block obtained based on the above-described method, and thus the distribution of illegal funds or money laundering information can be obtained.

For example, money laundering technology in the cryptocurrency field is gradually developing, and as a result, transactions are divided into thousands or tens of thousands of transactions at one time, and some are sent to various exchanges in each country, and some transactions are passed through by opening a cannon account at the exchange. Mixing method via exchange through the method, and coin join method in which hundreds of recipients and senders are entered in a transaction are used.

As a result, it is practically impossible to view all transaction volumes using the manual data collection method, and there are difficulties in preventing and tracking crime. In the disclosed embodiment, a mixer account is found based on the above-described method for determining account attributes, and a flow of funds including the mixer account can be determined and tracked as an illegal flow of funds.

In addition, the computing device 100 according to the disclosed embodiment performs machine learning learning to determine its properties (eg, normal flow and illegal money flow) based on flow information of cryptocurrency funds, and the learned artificial intelligence model It is also possible to determine the attribute corresponding to the flow information of cryptocurrency funds using

For example, the flow information of cryptocurrency funds may be expressed as nodes and lines based on the above-described visualization method, but is not limited thereto. In addition, the flow information of the cryptocurrency funds may include attribute information of the cryptocurrency account corresponding to each node, but is not limited thereto. As another example, attribute information on at least some or all of the nodes may not be given.

The computing device 100 may determine the property of the money flow according to the flow information of the money by using the pre-learned artificial intelligence model. More specifically, the attribute of the money flow may include the attribute of an illegal money flow, such as money laundering, tax evasion, payment for illegal goods or services, and the like.

As mentioned above, although embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art to which the present invention pertains can realize that the present invention can be embodied in other specific forms without changing its technical spirit or essential features. you will be able to understand Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive.

100: Cryptocurrency tax evasion determination device (computing device)
200: user terminal
300 : external server
400: network

Claims (10)

A method performed by a computing device, comprising:
identifying a cryptocurrency account whose use is not registered among a plurality of cryptocurrency accounts;
selecting a personal cryptocurrency account associated with a cryptocurrency account in which the use is not registered by using a predetermined use for each of the plurality of cryptocurrency accounts according to cryptocurrency transaction information; and
Analyzing the cryptocurrency transaction history between the selected personal cryptocurrency account and the cryptocurrency account for which the use is not registered, and determining whether to evade tax for the owner of the personal cryptocurrency account based on the analysis result,
A method of determining whether cryptocurrency tax evasion using artificial intelligence. According to claim 1,
The step of determining whether the tax evasion is
Comprising the step of determining the possibility of tax evasion based on whether there is a cryptocurrency transaction history exceeding a reference amount between the selected personal cryptocurrency account and the cryptocurrency account for which the use is not registered,
A method of determining whether cryptocurrency tax evasion using artificial intelligence. 3. The method of claim 2,
The step of determining the possibility of tax evasion,
when it is determined that there is a possibility of tax evasion, requesting explanatory data on the cryptocurrency transaction history exceeding the reference amount from the terminal of the owner; and
Comprising the step of determining whether the tax evasion based on the explanatory data obtained from the terminal of the owner,
A method of determining whether cryptocurrency tax evasion using artificial intelligence. According to claim 1,
The step of determining whether the tax evasion is
analyzing the cryptocurrency transaction information of the selected personal cryptocurrency account to determine whether there is a cryptocurrency collection history exceeding a reference amount from an exchange account among the plurality of cryptocurrency accounts;
if it is determined that there is a history of cryptocurrency collection exceeding the reference amount, determining whether to pay unearned income tax for the cryptocurrency collection history exceeding the reference amount; and
Comprising the step of determining whether or not to evade the tax on the owner based on whether the unearned income tax is paid,
A method of determining whether cryptocurrency tax evasion using artificial intelligence. According to claim 1,
The step of determining whether the tax evasion is
analyzing the cryptocurrency transaction information of the selected personal cryptocurrency account to determine whether there is a history of cryptocurrency collection from another personal cryptocurrency account;
determining whether to pay capital gains tax on the cryptocurrency collection history when it is determined that there is a history of cryptocurrency collection; and
Comprising the step of determining whether to evade tax on the owner based on whether the capital gains tax is paid,
A method of determining whether cryptocurrency tax evasion using artificial intelligence. According to claim 1,
The step of determining whether the tax evasion is
determining whether there is a cryptocurrency transaction history between a cryptocurrency account determined to be an illegal account among the plurality of cryptocurrency accounts and the selected personal cryptocurrency account; and
Based on whether there is a cryptocurrency transaction history between the cryptocurrency account determined as the illegal account and the selected personal cryptocurrency account, determining whether or not there is an illegal transaction for the owner,
A method of determining whether cryptocurrency tax evasion using artificial intelligence. According to claim 1,
The step of selecting a personal cryptocurrency account associated with the cryptocurrency account for which the use is not registered comprises:
Visualizing the cryptocurrency transaction information generated between the plurality of cryptocurrency accounts, and analyzing the visualized cryptocurrency transaction information to determine a use for each of the plurality of cryptocurrency accounts,
A method of determining whether cryptocurrency tax evasion using artificial intelligence. 8. The method of claim 7,
Determining the use for each of the plurality of cryptocurrency accounts comprises:
When the number of the plurality of cryptocurrency accounts included in the visualized cryptocurrency transaction information is less than or equal to the first reference value, the use for each of the plurality of cryptocurrency accounts by analyzing the transaction pattern for each of the plurality of cryptocurrency accounts determining a; and
When the number of transactions according to the cryptocurrency transaction information is less than or equal to a second reference value, at least one cryptocurrency account among the plurality of cryptocurrency accounts is grouped based on the owner of the cryptocurrency account, and the grouped at least one cryptocurrency Analyzing a pattern for the grouped at least one cryptocurrency account using the cryptocurrency transaction information generated in the account to determine a use for each of the plurality of cryptocurrency accounts,
A method of determining whether cryptocurrency tax evasion using artificial intelligence. a memory storing one or more instructions; and
a processor executing the one or more instructions stored in the memory;
The processor by executing the one or more instructions,
An apparatus for performing the method of claim 1 . A computer program stored in a computer-readable recording medium in combination with a computer, which is hardware, to perform the method of claim 1.

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