Method, Device and Medium for Identifying Abnormal Users in Digital Currency Transactions Based on Abacus Metaphor

Abstract

The present invention discloses a method, device and medium for identifying abnormal users of digital currency transactions based on an abacus metaphor, the method comprising: obtaining all transaction records of users of a digital currency exchange within a trading period; drawing an abacus diagram according to the transaction records, including a horizontal axis and a number of vertical columns, the horizontal axis representing the transaction time, the vertical columns vertically running through the horizontal axis and corresponding to the transaction records one by one; the abacus beads whose vertical columns are located above the horizontal axis use their height to display the transaction amount; the abacus beads whose vertical columns are located below the horizontal axis use their color and position to represent the transaction currency and type respectively; the number of vertical columns, the vertical column spacing, the number of abacus bead colors and related statistical data in the abacus diagram are counted; it is determined whether each statistical data exceeds a corresponding preset threshold value, and if the number of statistical data exceeding the corresponding preset threshold value is greater than a preset value, the user is determined to be an abnormal user. The present invention can intuitively and effectively display the transaction sequence data of abnormal users and identify abnormal users.

Description

Technical Field

[0001] The present invention relates to the field of information visualization, and in particular to a method, a device and a medium for identifying abnormal users of digital currency transactions based on an abacus metaphor. Background Art

[0002] Digital currency exchanges generate a large amount of data on buying and selling coins every day. These data record the changes in user transactions over time. Analyzing these data can help detect potential abnormal users in a timely manner and support the exchange's safe operation capabilities.

[0003] The main features of digital currency exchanges include: 7*24 hours service, full network transactions, no strict real identity authentication, no clearing center to centrally process data and monitor transactions. This low-cost, fast, highly anonymous, decentralized trading model is prone to breed some violations. For example, use legal currency to purchase digital currency or directly recharge digital currency to the exchange's personal account to complete the entry of illegal funds, then disperse funds through currency-to-currency transactions between different currencies, and use the price difference between currencies to make profits to mix illegal funds and "legal" income. Finally, sell digital currency to obtain legal currency or directly transfer digital currency from the exchange to complete the exit of illegal funds and legalize illegal income. This operation and management mechanism of digital currency exchanges is completely different from traditional finance. Traditional anomaly detection methods are not suitable for detecting abnormal transactions of digital currencies. At present, there is almost no research on abnormal behavior detection of digital currency exchanges.

[0004] Traditional anomaly detection methods are usually unable to directly determine the type of anomaly, and further verification is required based on the experience of the supervisor through a lot of exploration. Visual analysis presents data in the form of graphics and images, and provides friendly interactive means to establish image communication between people and data. With the help of human visual processing capabilities, it builds a powerful psychological model and provides insights into the potential patterns in the data. As an important technology for analyzing and understanding large and complex data, it can effectively combine the characteristics of machines being strong in computing and humans being strong in cognition, deeply integrate computational intelligence with human wisdom, and provide effective guidance for decision-making actions in complex scenarios. Visualization methods such as scatter plots and line graphs are often used to display price fluctuations and related information in the digital currency trading market, but it is difficult to effectively display the complex trading behaviors of digital currency exchanges, and it is even more difficult to help supervisors explore users' trading patterns to judge and analyze abnormal users. Therefore, a more reasonable and effective visualization method is needed. Summary of the invention

[0005] The present invention provides a method, device and medium for identifying abnormal users of digital currency transactions based on an abacus metaphor, which can more intuitively and effectively display the transaction sequence data of abnormal users to identify abnormal user transaction behaviors.

[0006] To achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] A method for identifying abnormal users in digital currency transactions based on the abacus metaphor, comprising:

[0008] Step 1: Obtain all transaction records of users in a digital currency exchange during a transaction time period, denoted as transaction data;

[0009] Step 2: According to the transaction sequence, draw an abacus diagram of the digital currency transaction sequence based on the abacus metaphor; the abacus diagram includes a horizontal axis and several vertical columns, the horizontal axis represents the transaction time, and the vertical columns vertically penetrate the horizontal axis and correspond one by one to each transaction record in the transaction sequence; a bead is set above the horizontal axis on the vertical column, and the height of the bead on the vertical column is used to display the transaction amount; several beads are set below the horizontal axis on the vertical column, and the color of the beads is used to display the transaction currency, and the position of the beads is used to display the transaction type;

[0010] Step 3: Characterize the digital currency transaction characteristics of the user by counting the number of vertical columns, the spacing between vertical columns, the number of bead colors for displaying transaction currencies, and related statistical data in the abacus diagram;

[0011] Step 4: Determine whether each statistical data counted in Step 3 exceeds the corresponding preset threshold. If the number of statistical data exceeding the corresponding preset threshold is greater than σ, then determine that the user is an abnormal user; where σ is a preset abnormal user determination threshold.

[0012] Further, after obtaining the transaction sequence in Step 1, first preprocess all the transaction records therein, including unifying the amount unit and merging consecutive transaction records with the same transaction type, and then process the transaction sequence obtained by preprocessing in Step 2; where the same transaction type needs to meet the condition that the original currency and the exchanged new currency in the currency-to-currency transaction are the same.

[0013] Further, the abacus diagram includes three vertical column distribution modes: normal mode, equidistant mode, and intelligent mode;

[0014] The abacus diagram in the normal mode means: map the start and end transaction times within the transaction time period to the start and end points of the horizontal axis of the abacus diagram, and use the position of the vertical column on the horizontal axis to restore the distribution of the transaction records in the time dimension;

[0015] The abacus diagram in the equidistant mode means: map the start and end transaction times within the transaction time period to the start and end points of the horizontal axis of the abacus diagram, and set all the transaction records in the transaction sequence at equal intervals on the horizontal axis;

[0016] The intelligent mode abacus chart refers to: mapping the start and end trading times within a trading period to the starting and ending points of the horizontal axis of the abacus chart, setting all trading records in the trading sequence on the horizontal axis, and the setting method for adjacent two trading records is as follows: (1) statistically calculate the adjacent trading records with the smallest trading time interval and the adjacent trading records with the largest trading time interval, set a lower bound and an upper bound for the ratio of a linear scale, solve to obtain the ratio function of the linear scale, and then determine the initial ratio intervals for all adjacent trading records in the trading sequence by this linear scale; (2) then use a linear scale, adjust the ratio of the linear scale according to the visible distance between the starting and ending points of the abacus horizontal axis, and combine with the initial ratio intervals for all adjacent trading records in the trading sequence to map all trading records in the trading sequence to the horizontal axis of the abacus chart.

[0017] Further, the statistical data used to characterize the digital currency trading characteristics in step 3 includes: the number of vertical bars, the number of colors of the beads dyed, the maximum height difference among all the beads used to display the trading amount, and the maximum distance, minimum distance, and average distance between vertical bars for each vertical bar pattern.

[0018] Further, if the trading record represented by a vertical bar is obtained by merging multiple consecutive original trading records with the same trading type, the number of the original trading records before merging is also marked on the bead used to display the trading type.

[0019] Further, the statistical data used to characterize the digital currency trading characteristics in step 3 also includes: the largest number marked on all the beads used to display the trading type.

[0020] Further, the method for using the positions and dyeing of several beads below the horizontal axis to display the trading currency and trading type is as follows: the number of beads below the horizontal axis corresponds to the number of types of trading types, the position of each bead is fixed and each represents a trading type, and each trading currency is represented by a different color; only the bead corresponding to the trading type of the trading record represented by the vertical bar is dyed as a highlighted color, and the beads at the positions of the remaining trading types are defaulted to gray.

[0021] Further, for the bead dyed as a highlighted color, the information of all the original trading records included in this vertical bar can be linked and displayed, including the user ID, the trading amount before USDT unit conversion, the trading type, the trading currency, the trading time, and the trading address.

[0022] An electronic device includes a memory and a processor. When a computer program stored in the memory is executed by the processor, the processor implements the method for identifying abnormal users in digital currency trading based on the abacus metaphor described in any one of the above technical solutions.

[0023] A computer-readable storage medium, on which a computer program is stored, characterized in that when the computer program is executed by a processor, it implements the method for identifying abnormal users in digital currency transactions based on the abacus metaphor described in any one of the above technical solutions.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0025] The present invention statistically analyzes data that can characterize the digital currency transaction characteristics of users by drawing an abacus diagram, so as to identify whether users are abnormal according to the statistical data, providing an efficient monitoring method for the daily work of supervisors in digital currency exchanges. The abacus diagram in it uses the abacus as a metaphor, effectively realizing the visualization of multiple information channels such as transaction time, transaction amount, transaction type, transaction currency, and transaction quantity. Combined with three visualization options, it provides an efficient monitoring method for the daily work of supervisors in digital currency exchanges. At the same time, according to the visualization features and parameter design, abnormal user accounts are displayed in the user list. The supervisor can select a user in the abnormal user list, and then analyze and discover abnormal clues such as the abnormal reasons and transaction patterns of the abnormal user in the visualization view. The present invention greatly improves the work efficiency of the supervisor. Description of the Drawings

[0026] Figure 1 It is a flowchart of the method described in the embodiment of the present invention.

[0027] Figure 2 It is a data table after the original transactions are merged and processed in the embodiment of the present invention;

[0028] Figure 3 It is an abacus diagram when the abacus mode is selected as the normal mode in the embodiment of the present invention.

[0029] Figure 4 It is an abacus diagram when the abacus mode is selected as the equidistant mode in the embodiment of the present invention.

[0030] Figure 5 It is an abacus diagram when the abacus mode is selected as the intelligent mode in the embodiment of the present invention.

[0031] Figure 6 It is an abacus diagram when the abacus straight file is not drawn in the embodiment of the present invention.

[0032] Figure 7 It is an abacus diagram when the abacus beads are connected by lines in the embodiment of the present invention.

[0033] Figure 8 It is the original transaction record displayed when the highlighted colored abacus beads are clicked in the embodiment of the present invention.

[0034] Figure 9 It is the abnormal user list and user account input box displayed in the embodiment of the present invention. Detailed implementation manners

[0035] The embodiments of the present invention will be described in detail below. Based on the technical solutions of the present invention, the following provides detailed implementation manners and specific operation processes to further explain the technical solutions of the present invention.

[0036] This embodiment provides a method for identifying abnormal users in digital currency transactions based on the abacus metaphor. As Figure 1 shown, it includes the following steps:

[0037] Step 1: Obtain transaction data

[0038] In a digital currency exchange, each transaction of each user generates a corresponding set of transaction records. The transaction data of a user includes all transaction records {S start , S end} within a time period [t 1 , t 2 , S 3 , …, S i , …, S n}. Each transaction record contains features such as transaction serial number, transaction user, transaction time, transaction type, transaction amount, transaction currency, and transaction address. There are five types of transaction types, namely coin recharge transaction, coin withdrawal transaction, coin purchase transaction, coin sale transaction, and coin-coin transaction.

[0039] This embodiment selects a time span from April 23, 2018 to April 8, 2020, involving 30,000 users and a total of more than 10 million real transaction records.

[0040] Step 2: Process transaction data

[0041] Step 2.1): Unify the amount unit. In a digital currency exchange, each user can use any digital currency for transactions. After statistics, a total of 72 digital currencies are used for transactions in the transaction record data of this embodiment. To eliminate the dimensionality influence of the values of different currencies, all digital currency amounts are uniformly converted into amounts in USDT (USDT is widely used and representative) according to the exchange rate at the same moment.

[0042] Step 2.2: Transaction Consolidation. In a digital currency exchange, the number of transactions and the transaction frequency of each user are often greater than those in traditional trading venues (such as banks, etc.). It is often difficult for a single transaction to serve as a basis for determining whether a user's behavior is abnormal. Therefore, in this embodiment, the original transactions of the same transaction type that are continuous in time for a user (i.e., the five transaction types mentioned in Step 1) are consolidated (where the same coin-to-coin transaction type requires that both the original currency of the coin-to-coin transaction and the new currency exchanged in the coin-to-coin transaction are the same). After the original transaction records are consolidated, the final transaction data is obtained. Each transaction in the transaction data stores the quantity of the consolidated original transactions, and the coin-to-coin transaction data also stores the currency type of the new currency exchanged in the coin-to-coin transaction. More than 10 million original real transaction records are consolidated to obtain 997,209 transaction data, and this data set is abstracted into a tabular data. The fields include: user account, transaction amount (in USDT), original transaction amount, transaction time, transaction type, transaction currency, including the quantity of original transactions, and the new currency exchanged in the coin-to-coin transaction. The consolidated data is as Figure 2 shown, which is a partial example of the consolidated transaction data.

[0043] Step 3: Draw the abacus diagram

[0044] The drawn abacus diagram includes a horizontal axis and several vertical columns. The horizontal axis represents the transaction time, and the vertical columns vertically penetrate the horizontal axis and correspond one by one to each transaction record in the transaction sequence. A bead is set above the horizontal axis on the vertical column, and the height of the bead on the vertical column is used to display the transaction amount. Several beads are set below the horizontal axis on the vertical column, and the color of the beads is used to display the transaction type.

[0045] Specifically, this embodiment draws abacus diagrams in three vertical column distribution modes: normal mode, equidistant mode, and intelligent mode, which are introduced as follows:

[0046] (1) Abacus diagram in normal mode

[0047] The abacus diagram in normal mode means that the start and end transaction times within the transaction time period are mapped to the starting point and the ending point of the horizontal axis of the abacus diagram, and the position of the vertical column on the horizontal axis is used to restore the distribution of the transaction records in the time dimension, as Figure 3 shown. The drawing steps include:

[0048] ① Draw the coordinate axes of the abacus view. The abacus view is divided into two parts: the upper part mainly displays the transaction amount, and the lower part mainly displays the transaction type. The X-axes of the upper and lower parts are the same, representing time. The Y-axis of the upper part represents the transaction amount (in USDT). The abacus updates the transaction amount scale for each user to prevent the difference in transaction amounts between different users from affecting the readability of the view. The Y-axis of the lower part represents the transaction type, which is, from top to bottom, buy coins, recharge coins, coin-to-coin transaction, sell coins, and withdraw coins.

[0049] ②Draw the inner vertical columns of the abacus. Each vertical column in one column of the abacus represents a transaction after the merged transactions mentioned in Step 2. The distribution of the vertical columns is divided into three modes: normal mode, equidistant mode, and intelligent mode. In the normal mode, each bead of the vertical column is of a fixed size, and the interval between the vertical columns reflects the real transaction interval. Specifically, using a linear scale, the number of milliseconds of the time of the user's earliest transaction is used as the lower bound of the scale input, and the number of milliseconds of the time of the user's last transaction is used as the upper bound of the scale input, and it is mapped to the visible area of the abacus, maximizing the restoration of the distribution of transactions in the time dimension.

[0050] ③Draw the beads at the lower part of the abacus. Five beads are included in the lower part of each inner vertical column of the abacus, corresponding to the five transaction types mentioned in Step 1. We merge transactions according to the rule of merging the original transactions of the same transaction type that are consecutive in time for the user. The beads represent the specific transaction information after merging. The beads at the corresponding positions of the transaction types will be dyed in color, and each color represents the transaction currency type corresponding to a transaction. For transactions with the number of original transactions greater than 1, the merged original transaction amounts will be marked on the beads for the user to view and understand the relevant information.

[0051] ④Draw the beads at the upper part of the abacus. Only one bead is included in the upper part of each inner vertical column of the abacus, and the height of the bead represents the transaction amount in USDT. Since the space at the upper part of the abacus is limited and the vertical height of the circular bead is too large, which affects the user's perception of the height difference of the beads and makes it difficult to grasp the transaction amount represented by the height of the beads, the original circular bead is modified to be shown in the form of a short line segment.

[0052] (2) Abacus diagram in equidistant mode

[0053] The abacus diagram in equidistant mode means that: the start and end transaction times within the transaction time period are mapped to the starting point and ending point of the horizontal axis of the abacus diagram, and all transaction records in the transaction sequence are set at equal intervals on the horizontal axis, as Figure 4 shown.

[0054] The drawing of the abacus diagram in equidistant mode is different from that of the abacus diagram in normal mode in the second point of drawing the inner vertical columns of the abacus:

[0055] When analyzing users, in addition to analyzing transactions by connecting them in a time-centered logic, it is also an important perspective to simply arrange transactions to analyze the user's behavior pattern. Therefore, we designed the equidistant mode of the abacus. The interval between the vertical columns does not reflect the time difference, but all merged transactions are evenly placed in the visible area of the abacus. The interval between the vertical columns and the size of the beads are adjusted according to the actual number of transactions of the user. The specific method is as follows. Let the length of the visible area be L, the interval be M, the size of the beads be S, and the number of transactions be N, then there is

[0056] (3) Intelligent mode abacus diagram

[0057] The intelligent mode abacus chart refers to: mapping the start and end transaction times within the transaction time period to the start and end points of the horizontal axis of the abacus chart, setting all transaction records in the transaction sequence on the horizontal axis, and setting two adjacent transaction records in the following manner: (1) counting the adjacent transaction records with the smallest transaction time interval and the adjacent transaction records with the largest transaction time interval, setting the lower and upper bounds of a linear scale, solving the proportional function of the linear scale, and then using the linear scale to determine the initial proportional interval of all adjacent transaction records in the transaction sequence; (2) using another linear scale, adjusting the scale of the linear scale according to the visible distance between the start and end points of the horizontal axis of the abacus, and combining the initial proportional intervals of all adjacent transaction records in the transaction sequence, mapping all transaction records in the transaction sequence to the horizontal axis of the abacus chart, such as Figure 5 shown.

[0058] The difference between the drawing of the abacus diagram in the smart mode and the abacus diagram in the normal mode is that the second point draws the inner straight column of the abacus:

[0059] In the normal mode, a fixed bead size is used to restore the real time difference of the transaction. When the number of user transactions is too large or the time difference of user transactions is too small, the bead occlusion phenomenon is likely to occur. Therefore, this embodiment designs an intelligent mode to avoid the problem of bead occlusion while restoring the real time difference of the transaction as much as possible. The specific method is as follows:

[0060] In the abacus, the horizontal axis is the transaction time, and each column represents a transaction. First, use a linear scale, input as [the time interval between the two transactions that occurred most recently, the time interval between the two transactions that occurred most distantly], and assign a reasonable column interval distance to the minimum and maximum values, then the time interval between any two transactions will have a corresponding column interval distance.

[0061] Then use a scale, [minimum column spacing, maximum column spacing], and assign a reasonable visual area distance to the minimum and maximum values ​​according to the visual area of ​​the abacus. The minimum value must not be less than half of the diameter of the beads, so that all column spacings have corresponding visual area distances. In this way, all columns have corresponding positions in the visual area and do not visually block each other.

[0062] Step 4: Draw three visualization options

[0063] (1) Drawing numbers on the abacus beads: In the abacus diagram drawn in step 3 of this embodiment, each vertical column represents the merged transaction records. If the transaction record is the one merged in step 2.2, then this vertical column in the abacus diagram includes several original transaction records. In this embodiment, the number of original transaction records included in this vertical column is marked on the abacus beads below the horizontal axis, and a button for independently selecting whether to display the numbers or not is provided, allowing the user to decide whether to adopt this visualization option.

[0064] (2) Drawing the vertical columns of the abacus: The vertical columns in the abacus diagram, while reflecting the abacus elements, also very intuitively reflect the positions of the transaction records. However, in the case of too many transaction records, there will be too many and too dense vertical columns, which will instead affect the readability of the abacus diagram and cause greater interference to information acquisition. Therefore, this embodiment provides an option for independently selecting whether to draw the vertical columns of the abacus (i.e., the vertical columns for setting the abacus beads). When there are many transactions, the readability of the view is ensured, as Figure 6 shown.

[0065] (3) Drawing the connections between the abacus beads: During the analysis using the abacus, the colors of all the abacus beads below the horizontal axis change (i.e., the transaction currency changes), and the position changes of the highlighted abacus beads (i.e., the transaction type changes) are highlighted, so as to summarize the user's transaction pattern. To facilitate the user to track this change, horizontal connections between the abacus beads are designed in this embodiment, that is, the colored and highlighted abacus beads on each vertical column of the abacus are connected by line segments, and at the same time, the overall background of the abacus is made semi-transparent to highlight the connections between the abacus beads. The user can independently select whether to enable this visualization option. As Figure 7 shown.

[0066] Step 5: Drawing the transaction record view

[0067] Click on the colored and highlighted abacus beads within each vertical column, and the transaction record view will draw the information of all the original transactions included in the transaction corresponding to this abacus bead, including the user ID, transaction amount (the amount without converting the USDT unit), transaction type, transaction currency, transaction time, and transaction address (the address may be empty). As Figure 8 shown.

[0068] Step 6: Statistics of digital currency transaction characteristics

[0069] Statistical data in the abacus diagram: the number of vertical columns, the number of colors of the colored abacus beads, the maximum height difference among all the abacus beads used to display the transaction amount, the maximum distance, minimum distance, and average distance between the vertical columns in each vertical column mode, and the maximum number marked on all the abacus beads used to display the transaction type.

[0070] Step 7: Identifying abnormal users

[0071] Determine whether each of the statistical data counted in step 6 exceeds the corresponding preset threshold. If the number of statistical data exceeding the corresponding preset threshold is greater than σ, then determine that the user is an abnormal user; where σ is the preset abnormal user determination threshold.

[0072] The preset thresholds of the above-mentioned statistical data and the setting of the abnormal user determination threshold σ are all set based on expert experience. An abnormal user is a user who has abnormal trading behaviors (such as using system vulnerabilities to brush money, maliciously manipulating the market for profit, etc.).

[0073] More preferably, an abnormal user list and an account input box can be drawn, as Figure 9 shown. The abnormal user list is used to display the account list of abnormal users, facilitating the supervisor to click on the user account or enter the user account in the blank box to view its corresponding visual view.

[0074] The present invention also provides an electronic device, including a memory and a processor. A computer program is stored in the memory. When the computer program is executed by the processor, the processor implements the method for identifying abnormal users in digital currency transactions based on the abacus metaphor described in the above embodiments.

[0075] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for identifying abnormal users in digital currency transactions based on the abacus metaphor described in the above embodiments is implemented.

[0076] The above embodiments are the preferred embodiments of the present application. Those of ordinary skill in the art can also make various transformations or improvements based on this. Without departing from the overall concept of the present application, these transformations or improvements should all fall within the scope of protection required by the present application.

Claims

1. A method for identifying abnormal users in digital currency transactions based on the abacus metaphor, characterized in that, it includes: Step 1, obtain all transaction records of users in a digital currency exchange during the trading period, denoted as a transaction sequence; Step 2, according to the transaction sequence, draw an abacus diagram of the digital currency transaction sequence based on the abacus metaphor; the abacus diagram includes a horizontal axis and several vertical columns, the horizontal axis represents the trading time, and the vertical columns vertically penetrate the horizontal axis and correspond one by one to each transaction record in the transaction sequence; a counting bead is set above the horizontal axis on the vertical column, and the height of the counting bead on the vertical column is used to display the transaction amount; several counting beads are set below the horizontal axis on the vertical column, and the color of the counting beads is used to display the transaction currency, and the position of the counting beads is used to display the transaction type; Step 3, characterize the digital currency trading characteristics of users by counting the number of vertical columns, the spacing between vertical columns, the number of colors of counting beads used to display transaction currencies, and related statistical data in the abacus diagram; Step 4, determine whether each statistical data counted in Step 3 exceeds the corresponding preset threshold. If the number of statistical data exceeding the corresponding preset threshold is greater than σ, then determine that the user is an abnormal user; where σ is a preset abnormal user determination threshold.

2. The method according to claim 1, characterized in that, after obtaining the transaction sequence in Step 1, first preprocess all the transaction records therein, including unifying the amount unit and merging consecutive transaction records with the same transaction type, and then Step 2 processes the transaction sequence obtained by preprocessing; where the same transaction type needs to meet the condition that the original currency and the exchanged new currency in the currency-to-currency transaction are the same.

3. The method according to claim 1, characterized in that, the abacus diagram includes three straight column distribution modes: normal mode, equidistant mode and intelligent mode; The abacus diagram in the normal mode means: map the start and end trading times during the trading period to the start and end points of the horizontal axis of the abacus diagram, and use the position of the vertical column on the horizontal axis to restore the distribution of transaction records in the time dimension; The abacus diagram in the equidistant mode means: map the start and end trading times during the trading period to the start and end points of the horizontal axis of the abacus diagram, and set all the transaction records in the transaction sequence at equal intervals on the horizontal axis; The abacus diagram in the intelligent mode means: map the start and end trading times during the trading period to the start and end points of the horizontal axis of the abacus diagram, and set all the transaction records in the transaction sequence on the horizontal axis, and the setting method of two adjacent transaction records is: (1) count the adjacent transaction records with the smallest trading time interval and the adjacent transaction records with the largest trading time interval, set a lower bound and an upper bound of the ratio of a linear scale, solve to obtain the ratio function of the linear scale, and then determine the initial ratio interval of all adjacent transaction records in the transaction sequence from this linear scale; (2) Then use a linear scale to adjust the ratio of the linear scale according to the visible distance between the start and end points of the abacus horizontal axis, and combine the initial ratio intervals of all adjacent transaction records in the transaction sequence to map all the transaction records in the transaction sequence to the horizontal axis of the abacus diagram.

4. The method according to claim 3, characterized in that, The statistical data used to characterize the digital currency transaction characteristics in step 3 include: the number of vertical bars, the number of abacus bead colors dyed, the maximum height difference among all abacus beads used to display the transaction amount, and the maximum distance, minimum distance, and average distance of vertical bars in each vertical bar pattern.

5. The method according to claim 4, wherein, if the transaction record represented by the vertical bar is obtained by merging multiple consecutive original transaction records with the same transaction type, the number of original transaction records before merging is also marked on the abacus bead used to display the transaction type.

6. The method according to claim 5, wherein, the statistical data used to characterize the digital currency transaction characteristics in step 3 further includes: the maximum number marked on all abacus beads used to display the transaction type.

7. The method according to claim 1, wherein, the method of using the positions and dyeing of several abacus beads below the horizontal axis to display the transaction currency and transaction type is: the number of abacus beads below the horizontal axis corresponds to the number of types of transaction types, the position of each abacus bead is fixed and represents a transaction type respectively, and each transaction currency is represented by a different color; only the abacus bead corresponding to the transaction type of the transaction record represented by the vertical bar is dyed as a highlighted color, and the abacus beads at the positions of the remaining transaction types are defaulted to gray.

8. The method according to claim 7, wherein, the abacus bead dyed as a highlighted color can be linked to display the information of all original transaction records included in the vertical bar, including user ID, transaction amount before USDT unit conversion, transaction type, transaction currency, transaction time, and transaction address.

9. An electronic device, including a memory and a processor, and a computer program is stored in the memory, wherein, when the computer program is executed by the processor, the processor is enabled to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, wherein, when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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