KR20210122941A - Method, apparatus and computer program for deciding intrinsic value of cryptocurrency using artificial intelligence - Google Patents

Abstract

Provided are a method, device, and computer program for determining an intrinsic value of cryptocurrency using artificial intelligence. According to various embodiments of the present invention, the method, performed by a computing device, for determining an intrinsic value of cryptocurrency includes the steps of: determining properties of each of the plurality of cryptocurrency accounts; analyzing cryptocurrency transaction information generated between the plurality of cryptocurrency accounts based on the determined properties of each of the cryptocurrency accounts; and determining an intrinsic value of cryptocurrency using the determined properties of each of the cryptocurrency accounts and an analysis result of the cryptocurrency transaction information.

Description

Method, device and computer program for determining the intrinsic value of cryptocurrency using artificial intelligence

Various embodiments of the present invention relate to a method, apparatus, and computer program for determining the intrinsic value of cryptocurrency 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. It is expected.

On the other hand, since a universal standard for what characteristics cryptocurrencies have is not presented, investors often make erroneous judgments and, in the end, often suffer huge losses. In addition, cryptocurrencies traded on exchanges are frequently delisted.

Accordingly, the demand for technology to evaluate the intrinsic value of individual cryptocurrencies and to compare them with each other is increasing. There is a limit to being systematic and non-objective.

Korean Patent Publication No. 10-2020-0007271 (2020.01.22)

The problem to be solved by the present invention is to use artificial intelligence to determine the properties of each of a plurality of cryptocurrency accounts having anonymity, and to determine the intrinsic value of the cryptocurrency by analyzing the properties of each cryptocurrency account and the history of cryptocurrency transactions. It is to provide a method, device and computer program for determining the intrinsic value of cryptocurrency.

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 the method performed by a computing device, the method for determining the intrinsic value of cryptocurrency using artificial intelligence according to an embodiment of the present invention for solving the above problems, the method comprising: determining the properties of each of a plurality of cryptocurrency accounts , analyzing the cryptocurrency transaction information generated between the plurality of cryptocurrency accounts based on the determined attributes of each of the plurality of cryptocurrency accounts, and analyzing the determined attributes of each of the plurality of cryptocurrency accounts and the cryptocurrency transaction information It may include the step of judging the intrinsic value of the cryptocurrency by using the result.

In various embodiments, the analyzing of the cryptocurrency transaction information includes: based on the determined attributes of each of the plurality of cryptocurrency accounts, the place of use, purpose of use, use value and payment method of the cryptocurrency from the cryptocurrency transaction information and extracting related information, wherein the determining of the intrinsic value of the cryptocurrency includes determining whether the cryptocurrency is actually used by using the extracted information, and determining whether the determined cryptocurrency is actually used. Accordingly, it may include calculating the intrinsic value of the cryptocurrency.

In various embodiments, the determining of the properties of each of the plurality of cryptocurrency accounts includes determining the owner of each of the cryptocurrency accounts, and the determining of the intrinsic value of the cryptocurrency includes: Determining the stability of the cryptocurrency according to whether there is an owner with a hash rate of more than half among all the nodes of the blockchain, and determining the intrinsic value of the cryptocurrency based on the determined stability of the cryptocurrency may include steps.

In various embodiments, the step of determining the intrinsic value of the cryptocurrency may include, when a preset condition is satisfied, using the analysis result of the properties of each of the plurality of first cryptocurrency accounts and the first cryptocurrency transaction information, the first Determining the intrinsic value of the cryptocurrency, and when the preset condition is not satisfied, based on the relationship information between the first cryptocurrency and the second cryptocurrency having a predetermined size of the intrinsic value of the first cryptocurrency It may include determining an intrinsic value.

In various embodiments, the determining of the properties of each of the plurality of cryptocurrency accounts includes visualizing the cryptocurrency transaction information and analyzing the visualized cryptocurrency transaction information to determine the attributes of each of the plurality of cryptocurrency accounts may include the step of

In various embodiments, the step of analyzing the visualized cryptocurrency transaction information to determine the properties of each of the plurality of cryptocurrency accounts includes generating a plurality of nodes corresponding to each of the plurality of cryptocurrency accounts, and the cryptocurrency According to the transaction information, connecting the sender's cryptocurrency account and the receiver's cryptocurrency account with a line, and determining the form in which the plurality of nodes are connected by the line using the previously learned first model, It may include determining an attribute of each of the plurality of cryptocurrency accounts based on the

In various embodiments, the determining of the properties of each of the plurality of cryptocurrency accounts based on the determined form may include, when the number of the plurality of nodes connected by the line is less than or equal to the first reference value, the previously learned second model and analyzing a transaction pattern for each of the plurality of cryptocurrency accounts using , and determining an attribute of each of the plurality of cryptocurrency accounts based on the analyzed transaction pattern.

In various embodiments, the determining of the attribute of each of the plurality of cryptocurrency accounts based on the determined form may include, when the number of lines for each of the plurality of nodes is less than or equal to a 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 an attribute for each of the grouped at least one cryptocurrency account based on the pattern for the grouped at least one cryptocurrency account.

An apparatus for determining the intrinsic value of cryptocurrency using artificial intelligence according to another embodiment of the present invention for solving the above-mentioned problems, 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 for determining the intrinsic value of cryptocurrency 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, and can perform the method for determining the intrinsic value of cryptocurrency using artificial intelligence according to an embodiment of the present invention. 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, the properties of each of a plurality of cryptocurrency accounts are determined based on the transaction history between the plurality of cryptocurrency accounts, and the results of analyzing the attributes of each of the plurality of cryptocurrency accounts and cryptocurrency transaction information are analyzed. By judging the intrinsic value of cryptocurrencies using the

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 the intrinsic value of cryptocurrency using artificial intelligence according to an embodiment of the present invention.
2 is a hardware configuration diagram of an apparatus for determining the intrinsic value of cryptocurrency according to another embodiment of the present invention.
3 is a flowchart of a method for determining the intrinsic value of cryptocurrency using artificial intelligence according to another embodiment of the present invention.
4 is a flowchart of a method for determining attributes of a cryptocurrency account, in various embodiments.
5 is a diagram illustrating cryptocurrency transaction information visualized according to a method for determining attributes of a cryptocurrency account, in various embodiments.
6 is a diagram illustrating a configuration for determining the properties of a cryptocurrency account using a graph-based semi-map learning model in various embodiments.
7 is a diagram illustrating a configuration for determining an attribute of a cryptocurrency account using an account address-based supervised learning model, in various embodiments.
8 is a diagram illustrating a configuration for determining an attribute 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 properties of a cryptocurrency account by using image-type cryptocurrency account information and keywords obtained from a website, in 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 the intrinsic value of cryptocurrency using artificial intelligence according to an embodiment of the present invention.

Referring to FIG. 1 , the system for determining the intrinsic value of cryptocurrency using artificial intelligence according to an embodiment of the present invention includes an apparatus 100 for determining the intrinsic value of cryptocurrency, a user terminal 200 and an external server 300 . can do.

Here, the system for determining the intrinsic value of cryptocurrency 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 may be deleted.

In one embodiment, the device 100 for determining the intrinsic value of cryptocurrency collects cryptocurrency transaction information (eg, a transaction) generated between a plurality of cryptocurrency accounts, and uses the collected cryptocurrency transaction information to multiple You can determine the properties of each cryptocurrency account (eg account type, role).

In various embodiments, the device 100 for determining the intrinsic value of cryptocurrency receives 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 . can be collected, the collected cryptocurrency transaction information can be visualized (eg, FIG. 5 ), and the properties of each of a plurality of cryptocurrency accounts can be determined by analyzing the visualized cryptocurrency transaction information. However, the present invention is not limited thereto.

In various embodiments, the device 100 for determining the intrinsic value of cryptocurrency analyzes the visualized cryptocurrency transaction information to determine the properties of each of a plurality of cryptocurrency accounts, but according to the analysis result, individual accounts, exchanges ) account, Miners account, Mixers account, Merchant account, Services account, Darkweb account, and hedge funds account. However, the present invention is not limited thereto.

In an embodiment, the apparatus 100 for determining the intrinsic value of cryptocurrency may analyze cryptocurrency transaction information generated between a plurality of cryptocurrency accounts by using the properties of each of the plurality of cryptocurrency accounts, and a plurality of cryptocurrency accounts The intrinsic value of cryptocurrency can be determined using the analysis results of each attribute and cryptocurrency transaction information. For example, the device 100 for determining the intrinsic value of cryptocurrency uses various data related to cryptocurrency as learning data and uses an artificial intelligence model that has been pre-trained to determine the properties of each of a plurality of cryptocurrency accounts and cryptocurrency transaction information. By analyzing the analysis results, it is possible to determine the intrinsic value of cryptocurrency. However, the present invention is not limited thereto.

In various embodiments, the apparatus 100 for determining the intrinsic value of cryptocurrency may provide various information related to cryptocurrency generated by analyzing cryptocurrency transaction information to the user terminal 200 . For example, the cryptocurrency intrinsic value determination device 100 may generate attribute information of a cryptocurrency account created by analyzing cryptocurrency transaction information, intrinsic value information of cryptocurrency, and price volatility prediction information of cryptocurrency, , may be provided to the user terminal 200 through a user interface (UI). However, the present invention is not limited thereto.

In an embodiment, the user terminal 200 may connect the network 400 to the device 100 for determining the intrinsic value of cryptocurrency, and from the device 100 for determining the intrinsic value of cryptocurrency, various information related to cryptocurrency (eg, : Attribute information of cryptocurrency account, intrinsic value information of cryptocurrency, and price volatility prediction information of cryptocurrency) can be provided and printed. For example, the user terminal 200 may include at least one of a smartphone, a tablet PC, a laptop computer, and a desktop equipped with a display on at least a portion of the user terminal 200, and the intrinsic value of cryptocurrency is determined through the display Various information related to the cryptocurrency provided from the device 100 may be output. However, the present invention is not limited thereto.

In one embodiment, the external server 300 may be connected to the intrinsic value determination apparatus 100 of the cryptocurrency through the network 400, and the intrinsic value determination apparatus 100 of the cryptocurrency determines the intrinsic value of the cryptocurrency We can provide you with all the information you need in the process. For example, the external server 300 may be a server that provides a service for brokering cryptocurrency transactions, and stores cryptocurrency transaction information between cryptocurrency accounts generated through a service for brokering cryptocurrency transactions, The stored cryptocurrency transaction information may be provided to the intrinsic value determination device 100 of the cryptocurrency. However, the present invention is not limited thereto.

In various embodiments, the external server 300 receives various information related to cryptocurrency from the device 100 for determining the intrinsic value of cryptocurrency (eg, attribute information of a cryptocurrency account, intrinsic value information of cryptocurrency, and price volatility of cryptocurrency) prediction information) can be provided and stored. For example, the external server 300 may be a storage device separately provided outside the device 100 for determining the intrinsic value of cryptocurrency. However, the present invention is not limited thereto.

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

2 is a hardware configuration diagram of an apparatus for determining the intrinsic value of cryptocurrency according to another embodiment of the present invention.

Referring to FIG. 2 , an apparatus 100 for determining the intrinsic value of cryptocurrency according to another embodiment of the present invention (hereinafter, “computing device 100”) 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 in relation to FIGS. 3 to 9 (a method of determining the intrinsic value of cryptocurrency using artificial intelligence) can be done

For example, the processor 110 executes one or more instructions stored in the memory 120, thereby determining an attribute of each of a plurality of cryptocurrency accounts, and a plurality of cryptograms based on the determined attribute of each of the plurality of cryptocurrency accounts. Analyzing cryptocurrency transaction information generated between money accounts and using artificial intelligence to determine the intrinsic value of cryptocurrency using the determined attributes of each of the plurality of cryptocurrency accounts and the analysis result of cryptocurrency transaction information A method of determining the intrinsic value of cryptocurrency can be performed. However, the present invention is not limited thereto.

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, a method of determining the intrinsic value of cryptocurrency using artificial intelligence performed by the computing device 100 will be described with reference to FIG. 3 .

3 is a flowchart of a method for determining the intrinsic value of cryptocurrency using artificial intelligence according to another embodiment of the present invention.

Referring to FIG. 3 , in step S110 , the computing device 100 may determine a property of each of a plurality of cryptocurrency accounts. For example, the computing device 100 may determine the properties of each of the plurality of cryptocurrency accounts by analyzing cryptocurrency transaction information generated between the plurality of cryptocurrency accounts using an artificial intelligence model. Hereinafter, a cryptocurrency account classification method performed by the computing device 100 will be described with reference to FIGS. 4 to 9 .

4 is a flowchart of a method for determining attributes of a cryptocurrency account, 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, it will be described with reference to FIG. 5 .

5 is a diagram illustrating cryptocurrency transaction information visualized according to a method for determining attributes of a cryptocurrency account, in various embodiments.

Referring to FIG. 5 , in various embodiments, 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 property 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 fraud account, and a gambling account) used for crime and fraud based on the properties 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.

In various embodiments, the computing device 100 connects the node of the sender's cryptocurrency account with 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.

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

In various embodiments, 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 a pre-learned artificial intelligence model, Accordingly, the attribute of the account corresponding to each node can 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 the computing device 100 remits multiple times between different nodes, and the value of the remittance calculated by reflecting the market price of cryptocurrency is constant, it pays for a product or service having a specific value can be judged to have been On the other hand, if a certain amount of cryptocurrency is being remitted despite fluctuations in the price of cryptocurrency, the computing device 100 may determine that the remittance has occurred regardless of the actual value and has other purposes.

Here, the purpose of the remittance may be evaluated differently according to specific situation information, and the criterion for the determination is 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.)

In various embodiments, the computing device 100 may visualize a line connecting each node according to a preset rule, and may determine the property of a transaction represented by each line using a pre-learned artificial intelligence model. have. 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.

Here, the artificial intelligence model may be learned based on a deep learning model and training data that includes information about a visualized image and an answer (eg, account attribute, transaction attribute, etc.) corresponding to each image. not limited

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 an attribute 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). It is possible to determine the properties of each of a plurality of cryptocurrency accounts by using the extracted feature values. 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 various embodiments, the computing device 100 is based on the visualized state of the cryptocurrency transaction information (eg, the number of nodes, the number of lines connecting the nodes, etc.), and the properties of the cryptocurrency account using the graph-based semi-map learning model. The property of a cryptocurrency account can be determined using any one of a determination method, a method for determining the properties of a cryptocurrency account using an account address-based supervised learning model, and a method for determining properties of a cryptocurrency account using an owner-based semi-supervised learning model have.

In various embodiments, the computing device 100 uses any one learning model 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 using a cryptocurrency account properties can be determined. Hereinafter, it will be described with reference to FIGS. 6 to 9 .

6 is a diagram illustrating a configuration for determining the properties 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 compares the number of a plurality of nodes included in the visualized cryptocurrency transaction information with a preset first reference value so that the number of the plurality of nodes is a preset first value. 1 It is determined whether or not the reference value is exceeded, and 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, the encryption is performed using a graph-based semi-map learning model. An attribute for each of a plurality of cryptocurrency accounts may be determined by using a method for determining the attribute of a currency account. For example, when the number of interconnected nodes in the visualized cryptocurrency transaction information is not large, the computing device 100 may determine the properties of the cryptocurrency account by using a graph-based semi-map learning model.

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 properties 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 attribute. 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 properties 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 property 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 properties of a cryptocurrency account using an account address-based supervised learning model, in various embodiments.

Referring to FIG. 7 , in various embodiments, the computing device 100 compares the number of a plurality of nodes included in the visualized cryptocurrency transaction information with a preset first reference value so that the number of the plurality of nodes is a preset first reference value. When it is determined that the value is equal to or less than one reference value, it may be determined whether the number of lines for each of the plurality of nodes exceeds the second reference value by comparing the number of lines for each of the plurality of nodes with the second reference value.

Thereafter, the computing device 100 determines that the number of the plurality of nodes is equal to or less than a preset first reference value, and when it is determined that the number of lines for each of the plurality of nodes exceeds the second reference value, the account address-based map It is possible to determine the properties of each of the plurality of crypto-currency accounts by using the method of determining the properties of the crypto-currency accounts using the learning model. For example, in the visualized cryptocurrency transaction information, when the number of interconnected nodes is not large, the computing device 100 may determine the attributes 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 properties 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 attributes are 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, a transaction pattern for each cryptocurrency account can be analyzed according to the transaction history for each cryptocurrency account, and properties of each of the plurality of cryptocurrency accounts can be determined based on the analyzed transaction pattern. For example, when the transaction pattern for the cryptocurrency account shows a wave shape, the computing device 100 may determine the property of the cryptocurrency account as an ICO account, and the form in which the transaction pattern for the cryptocurrency account occurs frequently If it is visible, the property 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 property of the cryptocurrency account can be determined as a personal account and an exchange cold wallet account, If the deposit and withdrawal amounts show the same form in the transaction pattern for the cryptocurrency account, the attribute 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 an attribute of a cryptocurrency account using an owner-based semi-guided learning model, according to various embodiments.

Referring to FIG. 8 , in various embodiments, the computing device 100 compares the number of a plurality of nodes included in the visualized cryptocurrency transaction information with a preset first reference value so that the number of the plurality of nodes is a preset first reference value. When it is determined that it is less than or equal to 1 reference value and the number of lines for each of the plurality of nodes is determined to be less than or equal to the second reference value, a plurality of cryptocurrency accounts using a method of determining the properties of a cryptocurrency account using an owner-based semi-guided learning model You can determine the properties for each. For example, when the computing device 100 has a small number (eg, one) of transaction details between cryptocurrency accounts for determining the transaction pattern, the computing device 100 uses the owner-based semi-map learning model to obtain cryptocurrency You can determine the properties of the 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 properties 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 performs an owner-based semi-supervisory 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 an attribute for each of the grouped at least one cryptocurrency account may be determined based on the pattern for the grouped at least one cryptocurrency account. However, the present invention is not limited thereto.

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

Referring to FIG. 9 , 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 analyze the image form of cryptocurrency account information to obtain text The form of cryptocurrency account information may be extracted, and one or more keywords may be analyzed to determine the attributes of the cryptocurrency account corresponding to the extracted text form of the 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 the properties of the extracted cryptocurrency account in the form of text 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 attribute 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 attributes 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 website, automatically collect cryptocurrency-related information from the dark website every preset cycle, and determine the properties of each of a plurality of cryptocurrency accounts based on the cryptocurrency-related information collected from the dark website 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. 3 , in step S120 , the computing device 100 generates between the plurality of cryptocurrency accounts based on the properties (eg, owner, use, role, etc.) of each of the plurality of cryptocurrency accounts determined in step S110. You can analyze cryptocurrency transaction information.

In various embodiments, the computing device 100 analyzes a plurality of cryptocurrency transaction information based on the properties of each cryptocurrency account, so that the use of the cryptocurrency from the cryptocurrency transaction information, the purpose of use, the use value, and the payment method are related. information can be extracted.

For example, the computing device 100 analyzes the transaction history of the cryptocurrency to determine that the cryptocurrency has been remitted from the first cryptocurrency account to the second cryptocurrency account, and the property of the second cryptocurrency account selects a specific item. If it is determined that the seller's account is selling, it is determined that the cryptocurrency transferred to the second cryptocurrency account is remitted to the seller that sells the specific item, and the purpose of using the cryptocurrency is to purchase the specific item. can judge

Also, the computing device 100 may determine the use value of the remitted cryptocurrency by comparing the size of the remitted cryptocurrency with the spot price of a specific item. For example, when the size of the remitted cryptocurrency is 0.2 and the spot price of a specific item is 1.3 million won, the computing device 100 may determine that the use value of the 0.2-sized cryptocurrency is 1.3 million won. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 may calculate a hash rate for each of the plurality of owners based on the owner information of each of the plurality of cryptocurrency accounts determined in step S110, and each calculated owner You can evaluate the stability of cryptocurrencies based on the hash rate for For example, the computing device 100 may evaluate the stability (eg, rating, score, etc.) of cryptocurrency according to whether there is an owner with a hash rate of more than half of all nodes of the block chain among a plurality of owners. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 groups at least one cryptocurrency account among a plurality of cryptocurrency accounts based on the owner of each cryptocurrency account, and the grouped at least one cryptocurrency account is a blockchain of cryptocurrency. It can be determined whether a hash rate of more than half of all nodes is possessed. For example, based on the owner information of each of the plurality of cryptocurrency accounts, the first cryptocurrency account group may be created by grouping the cryptocurrency accounts of owners belonging to the same company into one, and the first cryptocurrency account group has a majority It can be determined whether or not the hash rate is maintained. However, the present invention is not limited thereto.

In step S130, the computing device 100 may determine the intrinsic value of the cryptocurrency by using the properties of each of the plurality of cryptocurrency accounts determined in step S110 and the analysis result of the cryptocurrency transaction information generated in step S120.

In various embodiments, the computing device 100 extracts information related to the place of use of the cryptocurrency, the purpose of use, the value of use, and the payment method from the cryptocurrency transaction information based on the attributes of each of the plurality of cryptocurrency accounts, and the extracted information can be used to determine whether the cryptocurrency is actually used, and the intrinsic value of the cryptocurrency can be calculated according to whether the determined cryptocurrency is actually used.

First, the computing device 100 may determine whether the cryptocurrency is actually used by using information related to the place of use of the cryptocurrency, the purpose of use, the value of use, and the payment method.

In various embodiments, the computing device 100 may determine that the cryptocurrency is actually used only when all information related to the place of use, purpose of use, value of use, and payment method of the cryptocurrency is identified, and the place of use, purpose of use, If any of the information related to the use value and the payment method is not identified, it may be determined that the cryptocurrency has not been actually used.

In various embodiments, the computing device 100 may receive actual usage verification data (eg, purchase receipt, etc.) for the transaction history from the user terminal 200 or the external server 300, and the received actual usage verification Using the data, it is possible to determine whether the cryptocurrency is actually used or not. However, the present invention is not limited thereto.

Thereafter, when it is determined that the cryptocurrency is actually used, the computing device 100 determines the intrinsic value of the cryptocurrency by using at least one of information related to the identified cryptocurrency's usage, purpose, use value, and payment method. can do. For example, the computing device 100 determines that the cryptocurrency of the first size has been transferred from the first cryptocurrency account to the seller account selling the first product, and the cryptocurrency transaction is for purchasing the first product. If it is determined that it is, the intrinsic value of the cryptocurrency may be determined using the spot price (eg, KRW, yen, dollar, etc.) of the first product, the exchange rate, and the first size.

In various embodiments, the computing device 100 may determine the intrinsic value of a cryptocurrency of a preset unit size using a ratio between the spot price of the first item and the size of the remitted cryptocurrency (eg, the first size). have. For example, when the size of the remitted cryptocurrency is 0.2 and the spot price of the first item is 1 million won, the intrinsic value of the cryptocurrency of a preset unit size (eg, 1) may be calculated as 5 million won. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 may determine a representative value of the intrinsic values of the plurality of cryptocurrencies calculated by analyzing the plurality of cryptocurrencies transaction information as the intrinsic value of the cryptocurrencies. For example, the computing device 100 analyzes the first intrinsic value calculated by analyzing the first cryptocurrency transaction information, the second intrinsic value calculated by analyzing the second cryptocurrency transaction information, and the third cryptocurrency transaction information The average value of the calculated third intrinsic value can be determined as the intrinsic value of the cryptocurrency. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 determines the average value of the intrinsic value of a plurality of cryptocurrencies as the intrinsic value of the cryptocurrency, but represents the intrinsic value of the cryptocurrency whose deviation from the average exceeds a preset reference deviation Values can be excluded from calculation.

In various embodiments, the computing device 100 determines the stability of the cryptocurrency according to whether there is an owner with a hash rate of more than half among all nodes of the blockchain of the cryptocurrency, and based on the determined stability of the cryptocurrency, the cryptocurrency can determine the intrinsic value of

51% attack gains by securing a hash rate that exceeds more than half of all nodes in the blockchain (e.g., over 51%) and then manipulating transaction information (e.g., intentionally modifying or excluding the order of transactions) It means a hacking attack to get

In general, in the case of cryptocurrency, all users form a network while managing and verifying each other's transaction details. Blocks can be created and propagated at speed, which can be manipulated to accept forged or modulated data. Such risk factors may lower the stability and reliability of cryptocurrencies, and thus may cause a decline in the intrinsic value of cryptocurrencies.

In consideration of this, the computing device 100 determines the stability of cryptocurrency depending on whether there is an owner with a hash rate of more than half among all nodes of the cryptocurrency blockchain, that is, whether the cryptocurrency is likely to be attacked by 51%. can be determined, and the intrinsic value of the cryptocurrency can be determined according to the determined stability.

In various embodiments, the hash rate for a plurality of cryptocurrency account owners is analyzed, and a stability score that is inversely proportional to the hash rate value of the owner having the highest hash rate among the plurality of owners is calculated, and using the calculated stability score You can judge the intrinsic value of cryptocurrency.

In various embodiments, the computing device 100 uses the intrinsic value of the cryptocurrency calculated according to the actual use of the cryptocurrency and the intrinsic value of the cryptocurrency calculated according to the stability score of the cryptocurrency to the intrinsic value of the final cryptocurrency. can be decided For example, the computing device 100 uses the average of the intrinsic value of the cryptocurrency calculated according to the actual use of the cryptocurrency and the intrinsic value of the cryptocurrency calculated according to the stability score of the cryptocurrency as the intrinsic value of the final cryptocurrency. can decide However, without being limited thereto, the computing device 100 may correct the intrinsic value of the cryptocurrency calculated according to the stability score of the cryptocurrency by using the intrinsic value of the cryptocurrency calculated depending on whether or not it is actually used, or the stability score of the cryptocurrency The intrinsic value of the final cryptocurrency can be determined by correcting the intrinsic value of the calculated cryptocurrency according to actual use using the intrinsic value of the cryptocurrency calculated according to

In various embodiments, when a preset condition is not satisfied, the computing device 100 determines the intrinsic value of the first cryptocurrency based on relationship information between the first cryptocurrency and the second cryptocurrency having an intrinsic value of a predetermined size. can be judged

First, when the intrinsic value of the first cryptocurrency is not calculated by using the attributes of each of the plurality of first cryptocurrency accounts and the analysis result of the first cryptocurrency transaction information, the computing device 100 determines whether the intrinsic value of the first cryptocurrency is not calculated When the deviation between the intrinsic values of cryptocurrencies exceeds the reference deviation, it may be determined that the preset condition is not satisfied.

Then, when it is determined that the preset condition is not satisfied, the computing device 100 uses relationship information between the second cryptocurrency for which the intrinsic value of the cryptocurrency is determined and the first cryptocurrency for which the intrinsic value is not determined. 1 You can judge the intrinsic value of cryptocurrency. For example, the computing device 100 considers the exchange rate between the first cryptocurrency and the second cryptocurrency having an intrinsic value of a predetermined size and the transaction contract between the first cryptocurrency and the second cryptocurrency. can determine the intrinsic value of However, the present invention is not limited thereto.

In various embodiments, the computing device 100 corrects the intrinsic value of the determined cryptocurrency based on the stability of the cryptocurrency by using at least one of information related to the place of use, the purpose of use, the use value, and the payment method of the cryptocurrency. can do. For example, the computing device 100 corrects the intrinsic value of the cryptocurrency by adding the correction value according to whether or not there is an owner with a hash rate of more than half among all nodes of the cryptocurrency block chain to the intrinsic value of the cryptocurrency. If there is an owner with a higher hash rate, it can be corrected so that the intrinsic value of the cryptocurrency becomes smaller. However, the present invention is not limited thereto.

In various embodiments, if the computing device 100 does not have an owner who has a hash rate of more than half among all nodes of the cryptocurrency blockchain, based on the hash rate value of the owner who has the highest hash rate among a plurality of owners, the cryptocurrency It is possible to determine the correction value to be reflected in the intrinsic value of . For example, the computing device 100 determines the correction value so that the intrinsic value of the cryptocurrency decreases as the size of the hash rate value increases, and reflects the determined correction value in the intrinsic value of the cryptocurrency. If there is an owner with a relatively low hash rate, it can be corrected so that the intrinsic value of the cryptocurrency is smaller than if there is an owner with a relatively low hash rate. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 may correct the intrinsic value of the cryptocurrency based on the number of owners having a hash rate equal to or greater than a reference value among a plurality of owners. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 may determine the flow amount (or transaction volume) of the cryptocurrency by analyzing a plurality of cryptocurrency transaction information, and correct the intrinsic value of the cryptocurrency according to the determined flow amount of the cryptocurrency. can For example, the computing device 100 determines the correction value to increase the intrinsic value of the cryptocurrency in proportion to the increase in the flow of cryptocurrency, and reflects the determined correction value in the intrinsic value of the cryptocurrency by reflecting the intrinsic value of the cryptocurrency. can be corrected. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 may correct the intrinsic value of cryptocurrency by analyzing keywords related to cryptocurrency. For example, the computing device 100 collects various types of information related to cryptocurrency from the external server 300 (eg, social data related to cryptocurrency, news articles, etc.) More than one keyword can be extracted.

Thereafter, the computing device 100 may determine a correction value based on the extracted attributes of one or more keywords, and may correct the intrinsic value of the cryptocurrency by reflecting the determined correction value in the intrinsic value of the cryptocurrency. For example, the computing device 100 determines a first correction value to increase the intrinsic value of cryptocurrency according to the number of keywords having positive attributes, and determines the intrinsic value of cryptocurrency according to the number of keywords having negative attributes. The intrinsic value of the cryptocurrency can be corrected by determining a second correction value that causes the value to decrease, and reflecting the determined first correction value and the second correction value to the intrinsic value of the cryptocurrency. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 analyzes a plurality of cryptocurrency transaction information to calculate the number of cryptocurrency transactions for each use and purpose of use, and based on the calculated number of cryptocurrency transactions for each destination and purpose of use, Intrinsic value can be corrected. For example, the computing device 100 has a different correction value for a first cryptocurrency with a large number of cases used to purchase a specific item and a second cryptocurrency with a large number of cases used for an investment purpose (eg, remittance to a hedge fund, etc.) By setting and assigning the intrinsic value, the intrinsic value of the cryptocurrency can be calculated differently depending on the place and purpose where the cryptocurrency is used. However, the present invention is not limited thereto.

In various embodiments, the computing device 100 analyzes a plurality of transaction information and determines the intrinsic value of the cryptocurrency using the extracted information, but the date (eg, date) of the cryptocurrency transaction included in the plurality of transaction information, respectively. , time, etc.) can be used to correct the intrinsic value of cryptocurrency.

According to an embodiment, the computing device 100 may calculate or correct the intrinsic value of the cryptocurrency based on the ratio of the real transaction volume made by the cryptocurrency to the total real transaction volume in a specific country or area to be investigated. For example, if 10% of real transactions made in a specific country were made with cryptocurrency, it can be determined that the cryptocurrency has an intrinsic value equivalent to the currency value of that country. That is, the intrinsic value of the cryptocurrency may be evaluated differently depending on the currency value of the country where the cryptocurrency is used in the real economy, but is not limited thereto.

The method for determining the intrinsic value of cryptocurrency using the aforementioned artificial intelligence has been described with reference to the flowchart shown in the drawings. For a simple explanation, the method for determining the intrinsic value of cryptocurrency 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 different from those shown and operated in this specification. It may be performed in sequence 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.

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 intrinsic value judgment device (or computing device)
200: user terminal
300 : external server
400: network

Claims (10)

A method performed by a computing device, comprising:
determining an attribute of each of the plurality of cryptocurrency accounts;
analyzing cryptocurrency transaction information generated between the plurality of cryptocurrency accounts based on the determined attributes of each of the plurality of cryptocurrency accounts; and
Comprising the step of determining the intrinsic value of the cryptocurrency by using the determined attributes of each of the plurality of cryptocurrency accounts and the analysis result of the cryptocurrency transaction information,
A method of determining the intrinsic value of cryptocurrency using artificial intelligence. According to claim 1,
The step of analyzing the cryptocurrency transaction information includes:
and extracting information related to the use place, purpose of use, use value and payment method of the cryptocurrency from the cryptocurrency transaction information on the basis of the determined attributes of each of the plurality of cryptocurrency accounts,
The step of determining the intrinsic value of the cryptocurrency is,
Determining whether the cryptocurrency is actually used by using the extracted information, and calculating the intrinsic value of the cryptocurrency according to whether the determined cryptocurrency is actually used.
A method of determining the intrinsic value of cryptocurrency using artificial intelligence. According to claim 1,
Determining the properties of each of the plurality of cryptocurrency accounts comprises:
determining the owner of each cryptocurrency account;
The step of determining the intrinsic value of the cryptocurrency is,
The stability of the cryptocurrency is determined according to whether there is an owner who has a hash rate of more than half among all the nodes of the blockchain of the cryptocurrency, and the intrinsic value of the cryptocurrency based on the determined stability of the cryptocurrency comprising the step of determining
A method of determining the intrinsic value of cryptocurrency using artificial intelligence. According to claim 1,
The step of determining the intrinsic value of the cryptocurrency is,
determining the intrinsic value of the first cryptocurrency by using the attributes of each of the plurality of first cryptocurrency accounts and the analysis result of the first cryptocurrency transaction information when a preset condition is satisfied; and
When the preset condition is not satisfied, determining the intrinsic value of the first cryptocurrency based on relationship information between the first cryptocurrency and a second cryptocurrency having an intrinsic value of a predetermined size;
A method of determining the intrinsic value of cryptocurrency using artificial intelligence. According to claim 1,
Determining the properties of each of the plurality of cryptocurrency accounts comprises:
Visualizing the cryptocurrency transaction information and analyzing the visualized cryptocurrency transaction information to determine the properties of each of the plurality of cryptocurrency accounts,
A method of determining the intrinsic value of cryptocurrency using artificial intelligence. 6. The method of claim 5,
The step of analyzing the visualized cryptocurrency transaction information to determine the properties of each of the plurality of cryptocurrency accounts,
generating a plurality of nodes corresponding to each of the plurality of cryptocurrency accounts, and connecting the sender's cryptocurrency account and the receiver's cryptocurrency account with a line according to the cryptocurrency transaction information; and
Determining a form in which the plurality of nodes are connected by the line using a pre-learned first model, and determining a property of each of a plurality of cryptocurrency accounts based on the determined form,
A method of determining the intrinsic value of cryptocurrency using artificial intelligence. 7. The method of claim 6,
Determining the properties of each of a plurality of cryptocurrency accounts based on the determined form comprises:
When the number of the plurality of nodes connected by the line is less than or equal to the first reference value, a transaction pattern for each of the plurality of cryptocurrency accounts is analyzed using a previously learned second model, and based on the analyzed transaction pattern determining an attribute of each of the plurality of cryptocurrency accounts;
A method of determining the intrinsic value of cryptocurrency using artificial intelligence. 8. The method of claim 7,
Determining the properties of each of a plurality of cryptocurrency accounts based on the determined form comprises:
When the number of lines for each of the plurality of nodes 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 A pattern for the grouped at least one cryptocurrency account is analyzed using the cryptocurrency transaction information generated in the account, and the grouped at least one cryptocurrency based on the grouped pattern for the at least one cryptocurrency account determining an attribute for each monetary account;
A method of determining the intrinsic value of cryptocurrency 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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