Blockchain cryptocurrency fund flow searching method and control system
By generating materialized views and combining breadth-first and depth-first search, a tree-like fund flow graph is constructed, which solves the problem of difficult feature address location in blockchain cryptocurrency fund flow analysis and achieves fast and efficient fund flow analysis.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING ZHONGKE LIANYUAN TECH CO LTD
- Filing Date
- 2023-04-27
- Publication Date
- 2026-07-07
AI Technical Summary
In the analysis of cryptocurrency fund flows in the blockchain, it is difficult to quickly locate and display addresses with obvious characteristics and their transaction paths.
By generating materialized views, setting query conditions, and combining breadth-first search and depth-first search, a tree-like fund relationship graph is constructed to achieve fast retrieval of characteristic addresses.
It improves the efficiency and accuracy of fund flow analysis, reduces server computing pressure, and enables rapid location of characteristic addresses and transaction paths.
Smart Images
Figure CN116521946B_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of blockchain technology, and in particular to a method and control system for tracing the flow of funds in blockchain cryptocurrencies. Background Technology
[0002] Blockchain, as a novel decentralized protocol, can securely store and transmit transaction data, and is characterized by security, transparency, and immutability. Transaction tracing in blockchain cryptocurrencies primarily aims to track the flow of funds, which is achieved by combining data visualization technology to load and display data in a hierarchical format. For example, using a visual tree diagram can effectively help analysts intuitively visualize transaction paths, improving analytical efficiency.
[0003] In the process of analyzing the flow of funds in blockchain cryptocurrencies, it is difficult to quickly locate and display addresses with obvious characteristics. Determining whether a specific address exists in the transaction path usually requires manual identification layer by layer. Summary of the Invention
[0004] To address the aforementioned issues, this application proposes a method and control system for tracing the flow of funds in blockchain cryptocurrency.
[0005] This application proposes a method for tracing the flow of funds in blockchain cryptocurrency, including the following steps:
[0006] Obtain transaction detail data, preprocess the transaction detail data, and generate a materialized view;
[0007] The search criteria for the preset query address are used to obtain the query address from the materialized view.
[0008] Traverse the query addresses to obtain a first result graph, save the target addresses in the first result graph, and perform a search from the target addresses sequentially using breadth-first search and depth-first search to obtain a list of target paths.
[0009] As an optional implementation of this application, optionally, transaction detail data information is obtained, the transaction detail data information is preprocessed, and a materialized view is generated, including:
[0010] Obtain transaction details data;
[0011] Use each field in the transaction details data as a search condition data item;
[0012] Based on the search criteria data items, a corresponding materialized view is created and stored in the database.
[0013] As an optional implementation of this application, optionally, pre-setting search conditions for the query address and obtaining the query address from the materialized view according to the search conditions includes:
[0014] The search criteria are preset based on the selection of the search condition data items;
[0015] Based on the search criteria, a query is performed on the materialized view to obtain the query address.
[0016] As an optional implementation of this application, the search criteria may optionally include:
[0017] Set the query direction;
[0018] Set the analysis hierarchy;
[0019] Set the total transaction amount;
[0020] Set the selected search target.
[0021] As an optional implementation of this application, optionally, the query address is traversed to obtain a first result graph, the target address in the first result graph is saved, and a target path list is obtained by sequentially searching through breadth-first search and depth-first search from the target address, including:
[0022] Traverse n layers from the query address to obtain the first result graph, and save the target address in the first result graph;
[0023] Using breadth-first search, after performing a breadth-first search from the target address to the origin in the first result graph, a second result graph is obtained;
[0024] The corresponding path list is obtained by performing a depth-first search on the second result graph using the lowest amount.
[0025] The minimum value of each path edge in the path list is used as the weight for sorting, and paths with a number of points that meet the preset number of points are compressed and cached.
[0026] As an optional implementation of this application, the preset number of points may be 1000.
[0027] As an optional implementation of this application, optionally, after traversing the query address to obtain a first result graph, saving the target address in the first result graph, and sequentially searching from the target address using breadth-first search and depth-first search to obtain a target path list, the method further includes:
[0028] Based on the data structure requirements of the tree diagram, the address information in the path list is restructured to construct a tree-structured fund association diagram.
[0029] As an optional implementation of this application, the data structure of the tree diagram is optionally required to create an object, wherein the key of the object includes address, children, direction, and pid.
[0030] As an optional implementation of this application, the tree-like fund relationship diagram may optionally include:
[0031] The nodes list is used to collect all the nodes in the tree-like self-association graph;
[0032] The edges list is used to collect the edges that connect the nodes.
[0033] In another aspect, this application provides a control system, comprising:
[0034] processor;
[0035] Memory used to store processor-executable instructions;
[0036] The processor is configured to implement any of the above-described methods for locating the flow of funds in a blockchain cryptocurrency when executing the executable instructions.
[0037] Technical effects of the present invention:
[0038] This application pre-generates a materialized view based on the obtained transaction detail data, ensuring efficiency during the query process. By pre-setting search conditions for the query address, the query address is obtained from the constructed materialized view. Further, by traversing the query address, a first result image is obtained, and the target address is saved. Furthermore, the target path is searched sequentially using breadth-first search and depth-first search. The combination of breadth-first and depth-first search effectively improves search efficiency, fulfilling the requirement for rapid retrieval of feature addresses. This achieves superior data search speed and accuracy while reducing server computational burden.
[0039] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description
[0040] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this disclosure together with the specification and serve to explain the principles of this disclosure.
[0041] Figure 1 The diagram illustrates the implementation process of the blockchain cryptocurrency fund flow tracking method of the present invention.
[0042] Figure 2 The diagram illustrates the blockchain cryptocurrency fund flow tracking method of the present invention. Detailed Implementation
[0043] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.
[0044] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.
[0045] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.
[0046] Example 1
[0047] like Figure 1 and Figure 2 As shown, this application proposes a method for tracing the flow of funds in blockchain cryptocurrency, comprising the following steps:
[0048] S100: Obtain transaction detail data information, preprocess the transaction detail data information, and generate a materialized view;
[0049] S200: Preset the search conditions for the query address, and obtain the query address from the materialized view according to the search conditions;
[0050] S300. Traverse the query address to obtain a first result graph, save the target address in the first result graph, and search sequentially from the target address using breadth-first search and depth-first search to obtain a target path list.
[0051] In this embodiment, a materialized view is pre-generated based on the acquired transaction detail data to ensure efficiency during the query process. By pre-setting search conditions for the query address, the query address is obtained from the constructed materialized view. Further, by traversing the query address, a first result image is obtained, and the target address is saved. Furthermore, the target path is searched sequentially using breadth-first search and depth-first search. This combination of breadth-first and depth-first search effectively improves search efficiency, fulfilling the requirement for rapid retrieval of feature addresses.
[0052] As an optional implementation of this application, optionally, transaction detail data information is obtained, the transaction detail data information is preprocessed, and a materialized view is generated, including:
[0053] Obtain transaction details data;
[0054] Use each field in the transaction details data as a search condition data item;
[0055] Based on the search criteria data items, a corresponding materialized view is created and stored in the database.
[0056] In this embodiment, a materialized view is pre-generated based on the search criteria data items. Specifically, each field in the obtained transaction detail data is used as the search criteria data item. It should be noted that the transaction details are obtained from the blockchain. The fields in the blockchain transaction detail data include the transaction sender address (from), transaction receiver address (to), asset transaction value (value), transaction success timestamp (timestamp), and transaction hash value, etc. Each field included in the transaction detail data is used as a search criteria data item to pre-generate a matching materialized view, and the materialized view is stored for reuse during the search process.
[0057] As an optional implementation of this application, optionally, pre-setting search conditions for the query address and obtaining the query address from the materialized view according to the search conditions includes:
[0058] The search criteria are preset based on the selection of the search condition data items;
[0059] Based on the search criteria, a query is performed on the materialized view to obtain the query address.
[0060] Furthermore, the search criteria include:
[0061] Set the query direction;
[0062] Set the analysis hierarchy;
[0063] Set the total transaction amount;
[0064] Set the selected search target.
[0065] In this embodiment, pre-set search conditions for addresses required during the query process, specifically including setting the query direction, setting the analysis level, setting the total transaction amount, and selecting the search target. Setting the query direction limits the direction of fund flow to "forward" or "backward"; setting the analysis level and the total transaction amount limits the number of query levels and valuable addresses, respectively, thus defining the data range for the query; further, selecting the search target involves setting "address features" and custom addresses to determine the target. It should be noted that address features are set by matching address tags with the target address information to determine the search target. The query address is obtained in the constructed materialized view using the pre-set search conditions. Based on the transaction characteristics, the entity to which the address belongs, and the specified target address information, the target address of the transaction path can be quickly obtained, achieving the goal of quickly acquiring the information nodes of interest and drawing a fund flow map to shorten the analysis time.
[0066] As an optional implementation of this application, optionally, the query addresses are traversed to obtain a first result graph, and then a list of target addresses is obtained by sequentially performing breadth-first search and depth-first search, including:
[0067] Traverse n layers from the query address to obtain the first result graph, and save the target address in the first result graph;
[0068] Using breadth-first search, after performing a breadth-first search from the target address to the origin in the first result graph, a second result graph is obtained;
[0069] The corresponding path list is obtained by performing a depth-first search on the second result graph using the lowest amount.
[0070] The minimum value of each path edge in the path list is used as the weight for sorting, and paths with a number of points that meet the preset number of points are compressed and cached.
[0071] Furthermore, the preset number of points is 1000.
[0072] In this embodiment, after traversing n layers from the query address, a first result graph GraphA is obtained, and the address features in the first result graph are saved as target addresses. A breadth-first search is performed on the first result graph from the target address back to the origin to obtain a second result graph. A depth-first search is then performed on the second result graph GraphB using the minimum amount to obtain a list of all paths. The minimum value of each path edge is used as the path weight for sorting. The number of path points and paths meeting a preset number of points are saved for compression and caching. For example, a 5-layer layer-order traversal is performed with the query address root as the origin to obtain the first result graph, and the exchange address in the first result graph is saved as the target address. A breadth-first search is performed on the first result graph using the exchange address until the search results cover the query address root, obtaining the second result graph. A depth-first search is then performed on the second result graph using the minimum amount to obtain a list of all paths. The minimum value of each path edge is used as the path weight for sorting, and paths with a top number of points equal to 1000 are saved for compression and caching. By combining breadth-first search and depth-first search, the data search speed and accuracy can be improved, while saving server computational pressure.
[0073] As an optional implementation of this application, optionally, after traversing the query address to obtain a first result graph, and sequentially performing a breadth-first search and a depth-first search to obtain a list of target paths, the method further includes:
[0074] S400. Based on the data structure requirements of the tree diagram, restructure the address information in the path list to construct a tree-structured fund association diagram.
[0075] Furthermore, as an optional implementation of this application, the data structure of the tree diagram is optionally required to create an object, wherein the key of the object includes address, children, direction, and pid.
[0076] Furthermore, as an optional embodiment of this application, the tree-like fund relationship diagram may optionally include:
[0077] The nodes list is used to aggregate all the nodes in the tree-like capital relationship diagram;
[0078] The edges list is used to collect the edges that connect the nodes.
[0079] In this embodiment, according to the data structure requirements of the tree diagram, the address information in the path list is restructured. Specifically, an object is created, where the object includes the following keys: address, children, direction, and pid. The address is the address that triggers the query, the children are the list of child nodes found, the direction is the transaction direction at the origin, and the pid is the ID of the parent node of the starting address. Based on this, the obtained address information is added to the front-end tree diagram for easy reuse and lookup in the future. It should also be noted that the data structure of the constructed tree-like fund relationship graph includes a `nodes` list and an `egdes` list. Both the `nodes` and `egdes` lists represent relevant information for the view set. Specifically, the `nodes` list is used to aggregate the various nodes in the tree-like fund relationship graph, while the `edges` list connects adjacent nodes. In other words, the `nodes` list constitutes the basic unit of the view set, and the `edges` list represents the relationships between the nodes. Furthermore, the child objects of the `nodes` list contain `{id, children}`, where `id` is the unique ID of the node, and `children` is the list of the node's children. The child objects of the `edges` list contain `{startNode, endNode}`, representing information about two related nodes, where `startNode` is the start node and `endNode` is the end node. The constructed tree-like fund relationship graph achieves the purpose of visualizing fund relationships.
[0080] It should be noted that although the above description is provided as an example, those skilled in the art will understand that this disclosure is not limited thereto. In fact, users can flexibly configure the settings according to actual application scenarios, as long as the technical functions of this application can be achieved by following the above technical methods.
[0081] Example 2
[0082] Furthermore, in another aspect, this application also provides a control system, including:
[0083] processor;
[0084] Memory used to store processor-executable instructions;
[0085] The processor is configured to implement any of the above-described methods for locating the flow of funds in a blockchain cryptocurrency when executing the executable instructions.
[0086] This disclosure discloses an embodiment of a system including a processor and a memory for storing processor-executable instructions. The processor is configured to implement any of the preceding methods for locating the flow of funds in a blockchain cryptocurrency.
[0087] It should be noted here that the number of processors can be one or more. Furthermore, the control system in this embodiment may also include input devices and output devices. The processors, memory, input devices, and output devices can be connected via a bus or other means, without specific limitations herein.
[0088] As a computer-readable storage medium, the memory can be used to store software programs, computer-executable programs, and various modules, such as the program or module corresponding to the blockchain cryptocurrency fund flow tracking method in this embodiment of the disclosure. The processor executes various functional applications and data processing of the control system by running the software programs or modules stored in the memory.
[0089] Input devices can be used to receive input digital numbers or signals. These signals can be key signals related to user settings and function control of the device / terminal / server. Output devices can include display devices such as screens.
[0090] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.
Claims
1. A method for tracing the flow of funds in blockchain cryptocurrency, characterized in that, Includes the following steps: Obtain transaction detail data, preprocess the transaction detail data, and generate a materialized view; Obtain transaction details data; Each field in the transaction details data is used as a retrieval condition data item. The fields include at least the transaction sender address, transaction receiver address, asset transaction value, transaction success timestamp, and transaction hash value. Based on the search criteria data items, a corresponding materialized view is created and stored in the database; The search criteria for the preset query address are used to obtain the query address from the materialized view. Traverse n layers from the query address to obtain the first result graph, and save the target address in the first result graph; Using breadth-first search, after performing a breadth-first search from the target address to the origin in the first result graph, a second result graph is obtained; The corresponding path list is obtained by performing a depth-first search on the second result graph using the lowest amount. The minimum value of each path edge in the path list is used as the weight to sort the paths, and paths with a number of points that meet the preset number of points are compressed and cached to obtain the target path list.
2. The blockchain cryptocurrency fund flow tracking method according to claim 1, characterized in that, The search criteria for the preset query address are used to obtain the query address from the materialized view, including: The search criteria are preset based on the selection of the search condition data items; Based on the search criteria, a query is performed on the materialized view to obtain the query address.
3. The blockchain cryptocurrency fund flow tracking method according to claim 2, characterized in that, The search criteria include: Set the query direction; Set the analysis hierarchy; Set the total transaction amount; Set the selected search target.
4. The blockchain cryptocurrency fund flow tracking method according to claim 1, characterized in that, The preset number of points is 1000.
5. The blockchain cryptocurrency fund flow tracking method according to claim 1, characterized in that, Traverse the query addresses to obtain a first result graph, save the target addresses in the first result graph, and then perform a search sequentially from the target addresses using breadth-first search and depth-first search to obtain a list of target paths. The process also includes: Based on the data structure requirements of the tree diagram, the address information in the path list is restructured to construct a tree-structured fund association diagram.
6. The blockchain cryptocurrency fund flow tracking method according to claim 5, characterized in that, The data structure requirement for the tree diagram is to create an object, where the key of the object includes address, children, direction, and pid.
7. The blockchain cryptocurrency fund flow tracking method according to claim 6, characterized in that, The tree-like fund relationship diagram includes: The nodes list is used to collect all the nodes in the tree-like self-association graph; The edges list is used to collect the edges that connect the nodes.
8. A control system, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to implement, when executing the executable instructions, a blockchain cryptocurrency fund flow tracking method according to any one of claims 1 to 7.